From f9c744327a3be48c93b47bba71a480e1eeb97835 Mon Sep 17 00:00:00 2001 From: Madison Dunitz Date: Thu, 2 Sep 2021 13:18:35 -0400 Subject: [PATCH] Dunitz/2308-remove hosted (#2399) * remove code for and references to czi-hosted * revert client change --- .github/workflows/canary-deploy.yml | 13 - .github/workflows/push_tests.yml | 34 +- .github/workflows/scale-test.yml | 30 -- .gitignore | 4 - MANIFEST_hosted.in | 7 - Makefile | 58 +- backend/czi_hosted/Makefile | 49 -- backend/czi_hosted/__init__.py | 15 - backend/czi_hosted/__main__.py | 14 - backend/czi_hosted/app/__init__.py | 0 backend/czi_hosted/app/app.py | 475 ---------------- backend/czi_hosted/auth/__init__.py | 6 - backend/czi_hosted/auth/auth.py | 91 ---- backend/czi_hosted/auth/auth_none.py | 27 - backend/czi_hosted/auth/auth_oauth.py | 385 ------------- backend/czi_hosted/auth/auth_session.py | 40 -- backend/czi_hosted/auth/auth_test.py | 80 --- backend/czi_hosted/cli/__init__.py | 0 backend/czi_hosted/cli/cli.py | 35 -- backend/czi_hosted/cli/convert_to_cxg.py | 133 ----- backend/czi_hosted/cli/launch.py | 432 --------------- backend/czi_hosted/cli/prepare.py | 274 ---------- backend/czi_hosted/cli/schema.py | 72 --- backend/czi_hosted/cli/upgrade.py | 85 --- backend/czi_hosted/common/__init__.py | 0 .../czi_hosted/common/annotations/__init__.py | 0 .../common/annotations/annotations.py | 110 ---- .../common/annotations/hosted_tiledb.py | 167 ------ .../common/annotations/local_file_csv.py | 192 ------- backend/czi_hosted/common/config/__init__.py | 4 - .../czi_hosted/common/config/app_config.py | 247 --------- .../czi_hosted/common/config/base_config.py | 132 ----- .../czi_hosted/common/config/client_config.py | 121 ----- .../common/config/dataset_config.py | 211 -------- .../common/config/external_config.py | 95 ---- .../czi_hosted/common/config/server_config.py | 387 -------------- backend/czi_hosted/common/corpora.py | 78 --- backend/czi_hosted/common/health.py | 38 -- .../czi_hosted/common/immutable_kvcache.py | 71 --- backend/czi_hosted/common/rest.py | 381 ------------- backend/czi_hosted/common/utils/__init__.py | 0 .../common/utils/corpora_constants.py | 22 - .../czi_hosted/common/utils/cxg_constants.py | 4 - .../common/utils/cxg_generation_utils.py | 178 ------ .../czi_hosted/common/utils/matrix_utils.py | 115 ---- .../common/utils/sanitization_utils.py | 40 -- backend/czi_hosted/common/web/__init__.py | 0 backend/czi_hosted/compute/__init__.py | 0 backend/czi_hosted/compute/diffexp_cxg.py | 199 ------- backend/czi_hosted/converters/__init__.py | 0 .../czi_hosted/converters/h5ad_data_file.py | 250 --------- .../czi_hosted/converters/schema/__init__.py | 0 .../converters/schema/gene_symbol.py | 211 -------- .../schema/hgnc_complete_set.txt.gz | Bin 3562345 -> 0 bytes .../czi_hosted/converters/schema/ontology.py | 86 --- backend/czi_hosted/converters/schema/remix.py | 264 --------- .../schema/schema_definitions/1_0_0.yaml | 95 ---- .../schema/schema_definitions/1_1_0.yaml | 93 ---- .../czi_hosted/converters/schema/validate.py | 236 -------- backend/czi_hosted/converters/to_sparse.py | 81 --- backend/czi_hosted/data_anndata/__init__.py | 0 .../data_anndata/anndata_adaptor.py | 362 ------------- backend/czi_hosted/data_common/__init__.py | 0 .../czi_hosted/data_common/data_adaptor.py | 428 --------------- .../czi_hosted/data_common/matrix_loader.py | 288 ---------- backend/czi_hosted/data_common/rwlock.py | 135 ----- backend/czi_hosted/data_cxg/__init__.py | 0 backend/czi_hosted/data_cxg/cxg_adaptor.py | 470 ---------------- backend/czi_hosted/data_cxg/cxg_util.py | 37 -- backend/czi_hosted/db/__init__.py | 0 backend/czi_hosted/db/cellxgene_orm.py | 58 -- backend/czi_hosted/db/create_db.py | 18 - backend/czi_hosted/db/db_utils.py | 71 --- backend/czi_hosted/default_config.py | 266 --------- .../eb/.ebextensions/database.config | 0 .../.ebextensions/enable_mod_deflate.config | 30 -- .../wsgi_app_group_global.config | 10 - backend/czi_hosted/eb/.gitignore | 5 - backend/czi_hosted/eb/Makefile | 59 -- backend/czi_hosted/eb/README.md | 300 ----------- backend/czi_hosted/eb/__init__.py | 0 backend/czi_hosted/eb/app.py | 190 ------- backend/czi_hosted/eb/check_config.py | 38 -- backend/czi_hosted/eb/check_requirements.py | 98 ---- backend/czi_hosted/eb/config_deploy.yaml | 2 - backend/czi_hosted/requirements-dev.txt | 12 - backend/czi_hosted/requirements-prepare.txt | 4 - backend/czi_hosted/requirements.txt | 24 - backend/server/Makefile | 4 - .../czi_hosted_dataset_config_outline.py | 35 -- .../czi_hosted_server_config_outline.py | 63 --- backend/test/fixtures/database/__init__.py | 79 --- backend/test/test_czi_hosted/__init__.py | 0 backend/test/test_czi_hosted/locust/README.md | 39 -- .../test/test_czi_hosted/locust/__init__.py | 0 backend/test/test_czi_hosted/locust/config.py | 15 - .../test/test_czi_hosted/locust/locustfile.py | 165 ------ .../locust/requirements-locust.txt | 2 - .../test_czi_hosted/performance/__init__.py | 0 .../performance/create_test_matrix.py | 44 -- .../performance_test_annotations_backend.py | 216 -------- .../performance/run_diffexp.py | 116 ---- .../performance/scale_test_annotations.py | 45 -- .../test_czi_hosted/test_database/__init__.py | 0 .../test_database/test_database.py | 63 --- backend/test/test_czi_hosted/unit/__init__.py | 180 ------- .../test_czi_hosted/unit/auth/__init__.py | 0 .../test_czi_hosted/unit/auth/test_auth.py | 168 ------ .../test_czi_hosted/unit/auth/test_oauth.py | 229 -------- .../test/test_czi_hosted/unit/cli/__init__.py | 0 .../test_czi_hosted/unit/cli/test_launch.py | 27 - .../test_czi_hosted/unit/cli/test_prepare.py | 15 - .../test_czi_hosted/unit/cli/test_upgrade.py | 28 - .../test_czi_hosted/unit/common/__init__.py | 0 .../unit/common/config/__init__.py | 274 ---------- .../unit/common/config/test_app_config.py | 220 -------- .../unit/common/config/test_base_config.py | 66 --- .../unit/common/config/test_dataset_config.py | 253 --------- .../common/config/test_external_config.py | 243 --------- .../unit/common/config/test_server_config.py | 324 ----------- .../test_czi_hosted/unit/common/test_api.py | 505 ------------------ .../unit/common/test_corpora.py | 168 ------ .../unit/common/test_nan_rest.py | 65 --- .../test_czi_hosted/unit/common/test_rest.py | 79 --- .../unit/common/test_writable_annotation.py | 317 ----------- .../unit/common/utils/__init__.py | 0 .../common/utils/test_cxg_generation_utils.py | 158 ------ .../unit/common/utils/test_matrix_utils.py | 66 --- .../common/utils/test_sanitization_utils.py | 55 -- .../unit/common/utils/test_utils.py | 34 -- .../test_czi_hosted/unit/compute/__init__.py | 0 .../unit/compute/test_diffexp_cxg.py | 183 ------- .../unit/converters/__init__.py | 0 .../unit/converters/schema/__init__.py | 0 .../converters/schema/test_gene_symbol.py | 61 --- .../unit/converters/schema/test_ontology.py | 128 ----- .../unit/converters/schema/test_remix.py | 257 --------- .../unit/converters/schema/test_validate.py | 434 --------------- .../unit/converters/test_h5ad_data_file.py | 284 ---------- .../unit/data_anndata/__init__.py | 0 .../unit/data_anndata/test_anndata_adaptor.py | 198 ------- .../test_anndata_adaptor_data_load.py | 86 --- .../data_anndata/test_nan_anndata_adaptor.py | 64 --- .../unit/data_common/__init__.py | 0 .../unit/data_common/fbs/__init__.py | 0 .../unit/data_common/fbs/test_matrix.py | 82 --- .../unit/data_common/test_matrix_loader.py | 126 ----- .../test_czi_hosted/unit/data_cxg/__init__.py | 0 .../unit/data_cxg/test_cxg_adaptor.py | 20 - .../test/test_czi_hosted/unit/eb/__init__.py | 0 .../test/test_czi_hosted/unit/eb/test_eb.py | 82 --- client/__tests__/e2e/e2e.test.js | 33 -- setup.cfg | 2 +- setup_hosted.py | 43 -- 154 files changed, 6 insertions(+), 15809 deletions(-) delete mode 100644 .github/workflows/canary-deploy.yml delete mode 100644 .github/workflows/scale-test.yml delete mode 100644 MANIFEST_hosted.in delete mode 100644 backend/czi_hosted/Makefile delete mode 100644 backend/czi_hosted/__init__.py delete mode 100644 backend/czi_hosted/__main__.py delete mode 100644 backend/czi_hosted/app/__init__.py delete mode 100644 backend/czi_hosted/app/app.py delete mode 100644 backend/czi_hosted/auth/__init__.py delete mode 100644 backend/czi_hosted/auth/auth.py delete mode 100644 backend/czi_hosted/auth/auth_none.py delete mode 100644 backend/czi_hosted/auth/auth_oauth.py delete mode 100644 backend/czi_hosted/auth/auth_session.py delete mode 100644 backend/czi_hosted/auth/auth_test.py delete mode 100644 backend/czi_hosted/cli/__init__.py delete mode 100644 backend/czi_hosted/cli/cli.py delete mode 100644 backend/czi_hosted/cli/convert_to_cxg.py delete mode 100644 backend/czi_hosted/cli/launch.py delete mode 100644 backend/czi_hosted/cli/prepare.py delete mode 100644 backend/czi_hosted/cli/schema.py delete mode 100644 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backend/test/test_czi_hosted/unit/data_cxg/test_cxg_adaptor.py delete mode 100644 backend/test/test_czi_hosted/unit/eb/__init__.py delete mode 100644 backend/test/test_czi_hosted/unit/eb/test_eb.py delete mode 100644 setup_hosted.py diff --git a/.github/workflows/canary-deploy.yml b/.github/workflows/canary-deploy.yml deleted file mode 100644 index f8855b92..00000000 --- a/.github/workflows/canary-deploy.yml +++ /dev/null @@ -1,13 +0,0 @@ -name: Deploy canary via single cell infra repo - -on: - push: - branches: main-canary - -jobs: - deploy: - runs-on: ubuntu-latest - steps: - - name: repository dispatch - run: | - curl -XPOST -u czi-sci-single-cell-eng:${{secrets.SCI_GITHUB_TOKEN}} -H "Accept: application/vnd.github.everest-preview+json" -H "Content-Type: application/json" https://api.github.com/repos/chanzuckerberg/single-cell-infra/dispatches --data '{"event_type": "canary-hook"}' diff --git a/.github/workflows/push_tests.yml b/.github/workflows/push_tests.yml index a0ab94b7..6887f5e9 100644 --- a/.github/workflows/push_tests.yml +++ b/.github/workflows/push_tests.yml @@ -36,7 +36,7 @@ jobs: npm install - name: Format with black and lint with flake8 run: | - make lint-servers + make lint-server - name: Lint src with eslint working-directory: ./client run: | @@ -72,36 +72,6 @@ jobs: bash <(curl -s https://codecov.io/bash) -y .codecov.yml -k backend/server -cF backend,python,unitTest cd client && ./node_modules/codecov/bin/codecov --yml=../.codecov.yml --root=../ --gcov-root=../ -C -F frontend,javascript,unitTest - unit-test-czi-hosted: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v2 - - name: Set up Python 3.7 - uses: actions/setup-python@v1 - with: - python-version: 3.7 - - name: Python cache - uses: actions/cache@v1 - with: - path: ~/.cache/pip - key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements*.txt') }} - restore-keys: | - ${{ runner.os }}-pip- - - name: Node cache - uses: actions/cache@v1 - with: - path: ~/.npm - key: ${{ runner.os }}-node-${{ hashFiles('**/package-lock.json') }} - restore-keys: | - ${{ runner.os }}-node- - - name: Install dependencies - run: make pydist-czi-hosted install-dist dev-env-czi-hosted - - name: Unit tests - run: | - make unit-test-czi-hosted - bash <(curl -s https://codecov.io/bash) -y .codecov.yml -k backend/czi-hosted -cF backend,python,unitTest - cd client && ./node_modules/codecov/bin/codecov --yml=../.codecov.yml --root=../ --gcov-root=../ -C -F frontend,javascript,unitTest - smoke-tests: runs-on: macos-latest timeout-minutes: 20 @@ -126,7 +96,7 @@ jobs: restore-keys: | ${{ runner.os }}-node- - name: Install dependencies - run: make pydist-czi-hosted install-dist + run: make pydist install-dist - name: Smoke tests (without annotations feature) run: | cd client && make smoke-test diff --git a/.github/workflows/scale-test.yml b/.github/workflows/scale-test.yml deleted file mode 100644 index a89d93fb..00000000 --- a/.github/workflows/scale-test.yml +++ /dev/null @@ -1,30 +0,0 @@ -name: "Scale test cellxgene APIs for initial loading" - -on: - schedule: - - cron: "0 0 * * Sun" - -jobs: - locust-build: - runs-on: ubuntu-latest - steps: - - uses: actions/checkout@v2 - - name: Set up Python 3.7 - uses: actions/setup-python@v1 - with: - python-version: 3.7 - - name: Install dependencies - run: | - pip install -r backend/test/test_czi_hosted/locust/requirements-locust.txt - - name: Dev Scale Test - run: | - locust -f backend/test/test_czi_hosted/locust/locustfile.py --headless -u 30 -r 10 --host https://api.cellxgene.dev.single-cell.czi.technology/cellxgene/e/ --run-time 5m 2>&1 | tee locust_dev_stats.txt - - name: Slack success webhook - env: - SLACK_WEBHOOK: ${{ secrets.SLACK_WEBHOOK }} - run: | - DEV_STATS=$(tail -n 15 locust_dev_stats.txt) - DEV_MSG="\`\`\`CELLXGENE EXPLORER DEV SCALE TEST RESULTS: ${DEV_STATS}\`\`\`" - curl -X POST -H 'Content-type: application/json' --data "{'text':'${DEV_MSG}'}" $SLACK_WEBHOOK - - diff --git a/.gitignore b/.gitignore index 63ff7069..240d90fa 100644 --- a/.gitignore +++ b/.gitignore @@ -23,10 +23,6 @@ backend/server/common/web/static/* backend/server/common/web/templates/ backend/server/common/web/csp-hashes.json -backend/czi_hosted/common/web/static/* -backend/czi_hosted/common/web/templates/ -backend/czi_hosted/common/web/csp-hashes.json - # eb build artifact.dir artifact.zip diff --git a/MANIFEST_hosted.in b/MANIFEST_hosted.in deleted file mode 100644 index 6f349b1b..00000000 --- a/MANIFEST_hosted.in +++ /dev/null @@ -1,7 +0,0 @@ -recursive-include backend/czi_hosted/common/web/templates * -recursive-include backend/czi_hosted/common/web/static * - -include backend/czi_hosted/requirements.txt -include backend/czi_hosted/requirements-prepare.txt -include backend/czi_hosted/converters/schema/hgnc_complete_set.txt.gz -include backend/czi_hosted/converters/schema/schema_definitions/* diff --git a/Makefile b/Makefile index 0241742e..5cf55de6 100644 --- a/Makefile +++ b/Makefile @@ -2,7 +2,6 @@ include common.mk BUILDDIR := build CLIENTBUILD := $(BUILDDIR)/client -CZIHOSTEDBUILD := $(BUILDDIR)/backend/czi_hosted SERVERBUILD := $(BUILDDIR)/backend/server CLEANFILES := $(BUILDDIR)/ client/build build dist cellxgene.egg-info @@ -10,7 +9,7 @@ PART ?= patch # CLEANING .PHONY: clean -clean: clean-lite clean-czi-hosted clean-server clean-client +clean: clean-lite clean-server clean-client # cleaning the client's node_modules is the longest one, so we avoid that if possible .PHONY: clean-lite @@ -25,9 +24,6 @@ clean-client: clean-server: cd backend/server && $(MAKE) clean -.PHONY: clean-czi-hosted -clean-czi-hosted: - cd backend/czi_hosted && $(MAKE) clean # BUILDING PACKAGE @@ -45,34 +41,18 @@ build: clean build-client cp -r backend/common $(BUILDDIR)/backend/common cp MANIFEST.in README.md setup.cfg setup.py $(BUILDDIR) -.PHONY: build-czi-hosted -build-czi-hosted: clean build-client - git ls-files backend/czi_hosted/ | grep -v 'backend/czi_hosted/test/' | cpio -pdm $(BUILDDIR) - cp -r client/build/ $(CLIENTBUILD) - $(call copy_client_assets,$(CLIENTBUILD),$(CZIHOSTEDBUILD)) - cp -r backend/common $(BUILDDIR)/backend/common - cp backend/__init__.py $(BUILDDIR) - cp backend/__init__.py $(BUILDDIR)/backend - cp MANIFEST_hosted.in README.md setup.cfg setup_hosted.py $(BUILDDIR) - mv $(BUILDDIR)/setup_hosted.py $(BUILDDIR)/setup.py - mv $(BUILDDIR)/MANIFEST_hosted.in $(BUILDDIR)/MANIFEST.in - # If you are actively developing in the server folder use this, dirties the source tree .PHONY: build-for-server-dev build-for-server-dev: clean-server build-client $(call copy_client_assets,client/build,backend/server) -.PHONY: build-for-czi-hosted-dev -build-for-czi-hosted-dev: clean-czi-hosted build-client - $(call copy_client_assets,client/build,backend/czi_hosted) - .PHONY: copy-client-assets copy-client-assets: $(call copy_client_assets,client/build,backend/server) .PHONY: copy-client-assets-czi-hosted copy-client-assets-czi-hosted: - $(call copy_client_assets,client/build,backend/czi_hosted) + $(call copy_client_assets,client/build) # TESTING .PHONY: test @@ -84,17 +64,10 @@ unit-test: unit-test-server unit-test-client unit-test-common .PHONY: test-server test-server: unit-test-server smoke-test -.PHONY: test-czi-hosted -test-czi-hosted: unit-test-czi-hosted smoke-test - .PHONY: unit-test-client unit-test-client: cd client && $(MAKE) unit-test -.PHONY: unit-test-czi-hosted -unit-test-czi-hosted: - cd backend/czi_hosted && $(MAKE) unit-test - .PHONY: unit-test-server unit-test-server: cd backend/server && $(MAKE) unit-test @@ -111,10 +84,6 @@ smoke-test: smoke-test-annotations: cd client && $(MAKE) smoke-test-annotations -.PHONY: test-db -test-db: - cd backend/czi_hosted && $(MAKE) test-db - # FORMATTING CODE .PHONY: fmt @@ -129,19 +98,13 @@ fmt-py: black . .PHONY: lint -lint: lint-servers lint-client +lint: lint-server lint-client -.PHONY: lint-servers -lint-servers: lint-server lint-czi-hosted-server .PHONY: lint-server lint-server: fmt-py flake8 backend/server --per-file-ignores='backend/test/fixtures/dataset_config_outline.py:F821 backend/test/fixtures/server_config_outline.py:F821 backend/server/test/performance/scale_test_annotations.py:E501' -.PHONY: lint-czi-hosted-server -lint-czi-hosted-server: fmt-py - flake8 backend/czi_hosted --per-file-ignores='backend/test/fixtures/czi_hosted_dataset_config_outline.py:F821 backend/test/fixtures/czi_hosted_server_config_outline.py:F821 backend/test/performance/scale_test_annotations.py:E501' - .PHONY: lint-client lint-client: cd client && $(MAKE) lint @@ -153,12 +116,6 @@ pydist: build cd $(BUILDDIR); python setup.py sdist -d ../dist @echo "done" -.PHONY: pydist-czi-hosted -pydist-czi-hosted: build-czi-hosted - cd $(BUILDDIR); python setup.py sdist -d ../dist - @echo "done" - - # RELEASE HELPERS # Create new version to commit to main @@ -208,15 +165,6 @@ dev-env-client: dev-env-server: pip install -r backend/server/requirements-dev.txt -.PHONY: dev-env-czi-hosted -dev-env-czi-hosted: - pip install -r backend/czi_hosted/requirements-dev.txt -# Set PART=[major, minor, patch] as param to make bump. -# This will create a release candidate. (i.e. 0.16.1 -> 0.16.2-rc.0 for a patch bump) -.PHONY: bump-version -bump-version: - bumpversion --config-file .bumpversion.cfg $(PART) - # Increments the release candidate version (i.e. 0.16.2-rc.1 -> 0.16.2-rc.2) .PHONY: bump-release-candidate bump-release-candidate: diff --git a/backend/czi_hosted/Makefile b/backend/czi_hosted/Makefile deleted file mode 100644 index 538c68ff..00000000 --- a/backend/czi_hosted/Makefile +++ /dev/null @@ -1,49 +0,0 @@ -include ../../common.mk - -.PHONY: clean -clean: - rm -f common/web/templates/index.html - rm -rf common/web/static - rm -f common/web/csp-hashes.json - -.PHONY: unit-test -unit-test: create-test-db - PYTHONWARNINGS=ignore:ResourceWarning coverage run \ - --source=app,auth,cli,common,compute,converters,data_anndata,data_common,data_cxg,eb \ - --omit=.coverage,venv \ - -m unittest discover \ - --start-directory ../test/test_czi_hosted/unit \ - --top-level-directory ../.. \ - --verbose; test_result=$$?; \ - $(MAKE) clean-test-db; \ - exit $$test_result \ - - -.PHONY: test-db -test-db: create-test-db - PYTHONWARNINGS=ignore:ResourceWarning coverage run \ - --source=db \ - --omit=.coverage,venv \ - -m unittest discover \ - --start-directory ../test/test_czi_hosted/test_database \ - --top-level-directory ../.. \ - --verbose; test_result=$$?; \ - $(MAKE) clean-test-db; \ - exit $$test_result - -.PHONY: create-test-db -create-test-db: - -docker run -d -p 5432:5432 --name test_db -e POSTGRES_PASSWORD=test_pw postgres - -.PHONY: clean-test-db -clean-test-db: - -docker stop test_db - -docker rm test_db - -.PHONY: test-annotations-performance -test-annotations-performance: - python ../test/test_czi_hosted/performance/performance_test_annotations_backend.py - -.PHONY: test-annotations-scale -test-annotations-scale: - locust -f ../test/test_czi_hosted/performance/scale_test_annotations.py --headless -u 30 -r 10 --host https://api.cellxgene.dev.single-cell.czi.technology/cellxgene/e/ --run-time 5m 2>&1 | tee locust_dev_stats.txt diff --git a/backend/czi_hosted/__init__.py b/backend/czi_hosted/__init__.py deleted file mode 100644 index 053bc062..00000000 --- a/backend/czi_hosted/__init__.py +++ /dev/null @@ -1,15 +0,0 @@ -import logging -import sys -from backend.common.utils.utils import import_plugins - -__version__ = "0.16.7" - - -display_version = "cellxgene v" + __version__ - -try: - import_plugins("backend.czi_hosted.plugins") -except Exception as e: - # Make sure to exit in this case, as the server may not be configured as expected. - logging.critical(f"Error in import_plugins: {str(e)}") - sys.exit(1) diff --git a/backend/czi_hosted/__main__.py b/backend/czi_hosted/__main__.py deleted file mode 100644 index 0ffb94d1..00000000 --- a/backend/czi_hosted/__main__.py +++ /dev/null @@ -1,14 +0,0 @@ -# Work around bug https://github.com/pallets/werkzeug/issues/461 -if __package__ is None: - import sys - from pathlib import Path - - PKG_PATH = Path(__file__).parent - sys.path.insert(0, str(PKG_PATH.parent)) - import backend.czi_hosted # noqa F401 - __package__ = PKG_PATH.name - -# Main thing -from .cli.cli import cli # noqa F402 - -cli() diff --git a/backend/czi_hosted/app/__init__.py b/backend/czi_hosted/app/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/app/app.py b/backend/czi_hosted/app/app.py deleted file mode 100644 index 32a837c2..00000000 --- a/backend/czi_hosted/app/app.py +++ /dev/null @@ -1,475 +0,0 @@ -import datetime -import logging -from functools import wraps -from http import HTTPStatus -from urllib.parse import urlparse -import hashlib -import os - -from flask import ( - Flask, - redirect, - current_app, - make_response, - render_template, - abort, - Blueprint, - request, - send_from_directory, -) -from flask_restful import Api, Resource -from server_timing import Timing as ServerTiming - -import backend.czi_hosted.common.rest as common_rest -from backend.common.utils.data_locator import DataLocator -from backend.common.errors import DatasetAccessError, RequestException -from backend.czi_hosted.common.health import health_check -from backend.common.utils.utils import path_join, StrictJSONEncoder -from backend.czi_hosted.data_common.matrix_loader import MatrixDataLoader - -webbp = Blueprint("webapp", "backend.czi_hosted.common.web", template_folder="templates") - -ONE_WEEK = 7 * 24 * 60 * 60 - - -def _cache_control(always, **cache_kwargs): - """ - Used to easily manage cache control headers on responses. - See Werkzeug for attributes that can be set, eg, no_cache, private, max_age, etc. - https://werkzeug.palletsprojects.com/en/1.0.x/datastructures/#werkzeug.datastructures.ResponseCacheControl - """ - - def inner_cache_control(f): - @wraps(f) - def wrapper(*args, **kwargs): - response = make_response(f(*args, **kwargs)) - if not always and not current_app.app_config.server_config.app__generate_cache_control_headers: - return response - if response.status_code >= 400: - return response - for k, v in cache_kwargs.items(): - setattr(response.cache_control, k, v) - return response - - return wrapper - - return inner_cache_control - - -def cache_control(**cache_kwargs): - """ config driven """ - return _cache_control(False, **cache_kwargs) - - -def cache_control_always(**cache_kwargs): - """ always generate headers, regardless of the config """ - return _cache_control(True, **cache_kwargs) - - -# tell the client not to cache the index.html page so that changes to the app work on redeployment -# note that the bulk of the data needed by the client (datasets) will still be cached -@webbp.route("/", methods=["GET"]) -@cache_control_always(public=True, max_age=0, no_store=True, no_cache=True, must_revalidate=True) -def dataset_index(url_dataroot=None, dataset=None): - app_config = current_app.app_config - server_config = app_config.server_config - if dataset is None: - if app_config.is_multi_dataset(): - return dataroot_index() - else: - location = server_config.single_dataset__datapath - else: - dataroot = None - for key, dataroot_dict in server_config.multi_dataset__dataroot.items(): - if dataroot_dict["base_url"] == url_dataroot: - dataroot = dataroot_dict["dataroot"] - break - if dataroot is None: - abort(HTTPStatus.NOT_FOUND) - location = path_join(dataroot, dataset) - - dataset_config = app_config.get_dataset_config(url_dataroot) - scripts = dataset_config.app__scripts - inline_scripts = dataset_config.app__inline_scripts - - try: - cache_manager = current_app.matrix_data_cache_manager - with cache_manager.data_adaptor(url_dataroot, location, app_config) as data_adaptor: - data_adaptor.set_uri_path(f"{url_dataroot}/{dataset}") - args = {"SCRIPTS": scripts, "INLINE_SCRIPTS": inline_scripts} - return render_template("index.html", **args) - - except DatasetAccessError as e: - return common_rest.abort_and_log( - e.status_code, f"Invalid dataset {dataset}: {e.message}", loglevel=logging.INFO, include_exc_info=True - ) - - -@webbp.errorhandler(RequestException) -def handle_request_exception(error): - return common_rest.abort_and_log(error.status_code, error.message, loglevel=logging.INFO, include_exc_info=True) - - -def get_data_adaptor(url_dataroot=None, dataset=None): - config = current_app.app_config - server_config = config.server_config - dataset_key = None - - if dataset is None: - datapath = server_config.single_dataset__datapath - else: - dataroot = None - for key, dataroot_dict in server_config.multi_dataset__dataroot.items(): - if dataroot_dict["base_url"] == url_dataroot: - dataroot = dataroot_dict["dataroot"] - dataset_key = key - break - - if dataroot is None: - raise DatasetAccessError(f"Invalid dataset {url_dataroot}/{dataset}") - datapath = path_join(dataroot, dataset) - # path_join returns a normalized path. Therefore it is - # sufficient to check that the datapath starts with the - # dataroot to determine that the datapath is under the dataroot. - if not datapath.startswith(dataroot): - raise DatasetAccessError(f"Invalid dataset {url_dataroot}/{dataset}") - - if datapath is None: - return common_rest.abort_and_log(HTTPStatus.BAD_REQUEST, "Invalid dataset NONE", loglevel=logging.INFO) - - cache_manager = current_app.matrix_data_cache_manager - return cache_manager.data_adaptor(dataset_key, datapath, config) - - -def requires_authentication(func): - @wraps(func) - def wrapped_function(self, *args, **kwargs): - auth = current_app.auth - if auth.is_user_authenticated(): - return func(self, *args, **kwargs) - else: - return make_response("not authenticated", HTTPStatus.UNAUTHORIZED) - - return wrapped_function - - -def rest_get_data_adaptor(func): - @wraps(func) - def wrapped_function(self, dataset=None): - try: - with get_data_adaptor(self.url_dataroot, dataset) as data_adaptor: - data_adaptor.set_uri_path(f"{self.url_dataroot}/{dataset}") - return func(self, data_adaptor) - except DatasetAccessError as e: - return common_rest.abort_and_log( - e.status_code, f"Invalid dataset {dataset}: {e.message}", loglevel=logging.INFO, include_exc_info=True - ) - - return wrapped_function - - -def dataroot_test_index(): - # the following index page is meant for testing/debugging purposes - data = '' - data += "Hosted Cellxgene" - data += "

Welcome to cellxgene

" - - config = current_app.app_config - server_config = config.server_config - - auth = server_config.auth - if auth.is_valid_authentication_type(): - if server_config.auth.is_user_authenticated(): - data += f"

Logged in as {auth.get_user_id()} / {auth.get_user_name()} / {auth.get_user_email()}

" - if auth.requires_client_login(): - if server_config.auth.is_user_authenticated(): - data += f"

Logout

" - else: - data += f"

Login

" - - datasets = [] - for dataroot_dict in server_config.multi_dataset__dataroot.values(): - dataroot = dataroot_dict["dataroot"] - url_dataroot = dataroot_dict["base_url"] - locator = DataLocator(dataroot, region_name=server_config.data_locator__s3__region_name) - for fname in locator.ls(): - location = path_join(dataroot, fname) - try: - MatrixDataLoader(location, app_config=config) - datasets.append((url_dataroot, fname)) - except DatasetAccessError: - # skip over invalid datasets - pass - - data += "
Select one of these datasets...
" - data += "" - data += "" - - return make_response(data) - - -def dataroot_index(): - # Handle the base url for the cellxgene server when running in multi dataset mode - config = current_app.app_config - if not config.server_config.multi_dataset__index: - abort(HTTPStatus.NOT_FOUND) - elif config.server_config.multi_dataset__index is True: - return dataroot_test_index() - else: - return redirect(config.server_config.multi_dataset__index) - - -class HealthAPI(Resource): - @cache_control(no_store=True) - def get(self): - config = current_app.app_config - return health_check(config) - - -class DatasetResource(Resource): - """Base class for all Resources that act on datasets.""" - - def __init__(self, url_dataroot): - super().__init__() - self.url_dataroot = url_dataroot - - -class SchemaAPI(DatasetResource): - # TODO @mdunitz separate dataset schema and user schema - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.schema_get(data_adaptor) - - -class ConfigAPI(DatasetResource): - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.config_get(current_app.app_config, data_adaptor) - - -class UserInfoAPI(DatasetResource): - @cache_control_always(no_store=True) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.userinfo_get(current_app.app_config, data_adaptor) - - -class AnnotationsObsAPI(DatasetResource): - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.annotations_obs_get(request, data_adaptor) - - @requires_authentication - @cache_control(no_store=True) - @rest_get_data_adaptor - def put(self, data_adaptor): - return common_rest.annotations_obs_put(request, data_adaptor) - - -class AnnotationsVarAPI(DatasetResource): - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.annotations_var_get(request, data_adaptor) - - -class DataVarAPI(DatasetResource): - @cache_control(no_store=True) - @rest_get_data_adaptor - def put(self, data_adaptor): - return common_rest.data_var_put(request, data_adaptor) - - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.data_var_get(request, data_adaptor) - - -class ColorsAPI(DatasetResource): - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.colors_get(data_adaptor) - - -class DiffExpObsAPI(DatasetResource): - @cache_control(no_store=True) - @rest_get_data_adaptor - def post(self, data_adaptor): - return common_rest.diffexp_obs_post(request, data_adaptor) - - -class LayoutObsAPI(DatasetResource): - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.layout_obs_get(request, data_adaptor) - - -class GenesetsAPI(DatasetResource): - @cache_control(public=True, max_age=ONE_WEEK) - @rest_get_data_adaptor - def get(self, data_adaptor): - return common_rest.genesets_get(request, data_adaptor) - - -class SummarizeVarAPI(DatasetResource): - @rest_get_data_adaptor - @cache_control(public=True, max_age=ONE_WEEK) - def get(self, data_adaptor): - return common_rest.summarize_var_get(request, data_adaptor) - - @rest_get_data_adaptor - @cache_control(no_store=True) - def post(self, data_adaptor): - return common_rest.summarize_var_post(request, data_adaptor) - - -def get_api_base_resources(bp_base): - """Add resources that are accessed from the api_base_url""" - api = Api(bp_base) - - # Diagnostics routes - api.add_resource(HealthAPI, "/health") - return api - - -def get_api_dataroot_resources(bp_dataroot, url_dataroot=None): - """Add resources that refer to a dataset""" - api = Api(bp_dataroot) - - def add_resource(resource, url): - """convenience function to make the outer function less verbose""" - api.add_resource(resource, url, resource_class_args=(url_dataroot,)) - - # Initialization routes - add_resource(SchemaAPI, "/schema") - add_resource(ConfigAPI, "/config") - add_resource(UserInfoAPI, "/userinfo") - # Data routes - add_resource(AnnotationsObsAPI, "/annotations/obs") - add_resource(AnnotationsVarAPI, "/annotations/var") - add_resource(DataVarAPI, "/data/var") - add_resource(GenesetsAPI, "/genesets") - add_resource(SummarizeVarAPI, "/summarize/var") - # Display routes - add_resource(ColorsAPI, "/colors") - # Computation routes - add_resource(DiffExpObsAPI, "/diffexp/obs") - add_resource(LayoutObsAPI, "/layout/obs") - return api - - -def handle_api_base_url(app, app_config): - """If an api_base_url is provided, then an inline script is generated to - handle the new API prefix""" - api_base_url = app_config.server_config.get_api_base_url() - if not api_base_url: - return - - sha256 = hashlib.sha256(api_base_url.encode()).hexdigest() - script_name = f"api_base_url-{sha256}.js" - script_path = os.path.join(app.root_path, "../common/web/templates", script_name) - with open(script_path, "w") as fout: - fout.write("window.CELLXGENE.API.prefix = `" + api_base_url + "${location.pathname}api/`;\n") - - dataset_configs = [app_config.default_dataset_config] + list(app_config.dataroot_config.values()) - for dataset_config in dataset_configs: - inline_scripts = dataset_config.app__inline_scripts - inline_scripts.append(script_name) - - -class Server: - @staticmethod - def _before_adding_routes(app, app_config): - """ will be called before routes are added, during __init__. Subclass protocol """ - pass - - def __init__(self, app_config): - self.app = Flask(__name__, static_folder=None) - handle_api_base_url(self.app, app_config) - self._before_adding_routes(self.app, app_config) - self.app.json_encoder = StrictJSONEncoder - server_config = app_config.server_config - if server_config.app__server_timing_headers: - ServerTiming(self.app, force_debug=True) - - # enable session data - self.app.permanent_session_lifetime = datetime.timedelta(days=50 * 365) - - # Config - secret_key = server_config.app__flask_secret_key - self.app.config.update(SECRET_KEY=secret_key) - - self.app.register_blueprint(webbp) - - api_version = "/api/v0.2" - api_base_url = server_config.get_api_base_url() - api_path = "/" - if api_base_url: - parse = urlparse(api_base_url) - api_path = parse.path - - bp_base = Blueprint("bp_base", __name__, url_prefix=api_path) - base_resources = get_api_base_resources(bp_base) - self.app.register_blueprint(base_resources.blueprint) - - if app_config.is_multi_dataset(): - # NOTE: These routes only allow the dataset to be in the directory - # of the dataroot, and not a subdirectory. We may want to change - # the route format at some point - for dataroot_dict in server_config.multi_dataset__dataroot.values(): - url_dataroot = dataroot_dict["base_url"] - bp_dataroot = Blueprint( - f"api_dataset_{url_dataroot}", - __name__, - url_prefix=f"{api_path}/{url_dataroot}/" + api_version, - ) - dataroot_resources = get_api_dataroot_resources(bp_dataroot, url_dataroot) - self.app.register_blueprint(dataroot_resources.blueprint) - - self.app.add_url_rule( - f"/{url_dataroot}/", - f"dataset_index_{url_dataroot}", - lambda dataset, url_dataroot=url_dataroot: dataset_index(url_dataroot, dataset), - methods=["GET"], - ) - self.app.add_url_rule( - f"/{url_dataroot}//", - f"dataset_index_{url_dataroot}/", - lambda dataset, url_dataroot=url_dataroot: dataset_index(url_dataroot, dataset), - methods=["GET"], - ) - self.app.add_url_rule( - f"/{url_dataroot}//static/", - f"static_assets_{url_dataroot}", - view_func=lambda dataset, filename: send_from_directory("../common/web/static", filename), - methods=["GET"], - ) - - else: - bp_api = Blueprint("api", __name__, url_prefix=f"{api_path}{api_version}") - resources = get_api_dataroot_resources(bp_api) - self.app.register_blueprint(resources.blueprint) - self.app.add_url_rule( - "/static/", - "static_assets", - view_func=lambda filename: send_from_directory("../common/web/static", filename), - methods=["GET"], - ) - - self.app.matrix_data_cache_manager = server_config.matrix_data_cache_manager - self.app.app_config = app_config - - auth = server_config.auth - self.app.auth = auth - if auth and auth.requires_client_login(): - auth.add_url_rules(self.app) - auth.complete_setup(self.app) diff --git a/backend/czi_hosted/auth/__init__.py b/backend/czi_hosted/auth/__init__.py deleted file mode 100644 index 5e24ac8f..00000000 --- a/backend/czi_hosted/auth/__init__.py +++ /dev/null @@ -1,6 +0,0 @@ -# import the built in auth types so they can be registered - -import backend.czi_hosted.auth.auth_test # noqa: F401 -import backend.czi_hosted.auth.auth_session # noqa: F401 -import backend.czi_hosted.auth.auth_oauth # noqa: F401 -import backend.czi_hosted.auth.auth_none # noqa: F401 diff --git a/backend/czi_hosted/auth/auth.py b/backend/czi_hosted/auth/auth.py deleted file mode 100644 index 03184e8d..00000000 --- a/backend/czi_hosted/auth/auth.py +++ /dev/null @@ -1,91 +0,0 @@ -from abc import ABC, abstractmethod - - -class AuthTypeBase(ABC): - """Base type for all authentication types.""" - - def __init__(self): - super().__init__() - - @abstractmethod - def is_valid_authentication_type(self): - """Return True if the auth type is valid, e.g. it can return userinfo and username. - (AuthTypeNone is the only one type that returns False)""" - pass - - def requires_client_login(self): - """Return True if the user needs to login from the client (e.g. Login button is shown)""" - return False - - @abstractmethod - def complete_setup(self, app): - """complete any setup that may be needed by this auth type. The Flask app is passed in. - This is the last auth function called before the server starts to run.""" - pass - - @abstractmethod - def is_user_authenticated(self): - """Return True if the user is authenticated""" - pass - - @abstractmethod - def get_user_id(self): - """Return the id for this user (string)""" - pass - - @abstractmethod - def get_user_name(self): - """Return the name of the user (string)""" - pass - - @abstractmethod - def get_user_email(self): - """Return the name of the user (string)""" - pass - - def get_user_picture(self): - """Return the location to the user's picture""" - return None - - -class AuthTypeClientBase(AuthTypeBase): - """Base type for all authentication types that require the client to login""" - - def __init__(self): - super().__init__() - - def requires_client_login(self): - return True - - @abstractmethod - def add_url_rules(self, selfapp): - """Add url rules to the app (like /login, /logout, etc)""" - pass - - @abstractmethod - def get_login_url(self, data_adaptor): - """Return the url for the login route""" - pass - - @abstractmethod - def get_logout_url(self, data_adaptor): - """Return the url for the logout route""" - pass - - -class AuthTypeFactory: - """Factory class to create an authentication type""" - - auth_types = {} - - @staticmethod - def register(name, auth_type): - assert issubclass(auth_type, AuthTypeBase) - AuthTypeFactory.auth_types[name] = auth_type - - @staticmethod - def create(name, app_config): - auth_type = AuthTypeFactory.auth_types.get(name) - if auth_type is None: - return None - return auth_type(app_config) diff --git a/backend/czi_hosted/auth/auth_none.py b/backend/czi_hosted/auth/auth_none.py deleted file mode 100644 index 491bed4b..00000000 --- a/backend/czi_hosted/auth/auth_none.py +++ /dev/null @@ -1,27 +0,0 @@ -from backend.czi_hosted.auth.auth import AuthTypeBase, AuthTypeFactory - - -class AuthTypeNone(AuthTypeBase): - def __init__(self, app_config): - super().__init__() - - def is_valid_authentication_type(self): - return False - - def complete_setup(self, app): - pass - - def is_user_authenticated(self): - return True - - def get_user_id(self): - return None - - def get_user_name(self): - return None - - def get_user_email(self): - return None - - -AuthTypeFactory.register(None, AuthTypeNone) diff --git a/backend/czi_hosted/auth/auth_oauth.py b/backend/czi_hosted/auth/auth_oauth.py deleted file mode 100644 index 74d09432..00000000 --- a/backend/czi_hosted/auth/auth_oauth.py +++ /dev/null @@ -1,385 +0,0 @@ -from flask import session, request, redirect, current_app, after_this_request, has_request_context, g -from backend.czi_hosted.auth.auth import AuthTypeClientBase, AuthTypeFactory -from backend.common.errors import AuthenticationError, ConfigurationError -from urllib.parse import urlencode, urlparse -import json -import requests -import base64 - -# It is not required to have authlib or jose. -# However, it is a configuration error to use this auth type if they are not installed. -missingimport = [] -try: - from authlib.integrations.flask_client import OAuth -except ModuleNotFoundError: - missingimport.append("authlib") - -try: - from jose import jwt - from jose.exceptions import ExpiredSignatureError, JWTError, JWTClaimsError -except ModuleNotFoundError: - missingimport.append("jose") - - -class Tokens: - """Simple class to represent the tokens that are saved/restored from the cookie""" - - def __init__(self, access_token, id_token, refresh_token, expires_at, **kwargs): - self.access_token = access_token - self.id_token = id_token - self.refresh_token = refresh_token - self.expires_at = expires_at - - # expires_at may be None after a token refresh, and so it is not checked here - if not (access_token and id_token and refresh_token): - raise KeyError(str(self.__dict__)) - - -class AuthTypeOAuth(AuthTypeClientBase): - """An authentication type for oauth2 logins.""" - - CXG_TOKENS = "auth_tokens" - - def __init__(self, server_config): - super().__init__() - if missingimport: - raise ConfigurationError(f"oauth requires these modules: {', '.join(missingimport)}") - self.algorithms = ["RS256"] - self.oauth_api_base_url = server_config.authentication__params_oauth__oauth_api_base_url - self.client_id = server_config.authentication__params_oauth__client_id - self.client_secret = server_config.authentication__params_oauth__client_secret - self.session_cookie = server_config.authentication__params_oauth__session_cookie - self.cookie_params = server_config.authentication__params_oauth__cookie - self.jwt_decode_options = server_config.authentication__params_oauth__jwt_decode_options - - self._validate_cookie_params() - self._validate_jwt_decode_options() - - self.api_base_url = server_config.get_api_base_url() - self.web_base_url = server_config.get_web_base_url() - if self.api_base_url is None: - raise ConfigurationError("oauth requires the app__api_base_url to be set") - - # set the audience - self.audience = self.client_id - - # load the jwks (JSON Web Key Set). - # The JSON Web Key Set (JWKS) is a set of keys which contains the public keys used to verify - # any JSON Web Token (JWT) issued by the authorization server and signed using the RS256 - try: - jwksloc = f"{self.oauth_api_base_url}/.well-known/jwks.json" - jwksurl = requests.get(jwksloc) - self.jwks = jwksurl.json() - except Exception: - raise ConfigurationError( - f"error in oauth, api_url_base: {self.oauth_api_base_url}, cannot access {jwksloc}" - ) - - def _validate_cookie_params(self): - """check the cookie_params, and raise a ConfigurationError if there is something wrong""" - if self.session_cookie: - return - - if not isinstance(self.cookie_params, dict): - raise ConfigurationError("either session_cookie or cookie must be set") - valid_keys = {"key", "max_age", "expires", "path", "domain", "secure", "httponly", "samesite"} - keys = set(self.cookie_params.keys()) - unknown = keys - valid_keys - if unknown: - raise ConfigurationError(f"unexpected key in cookie params: {', '.join(unknown)}") - if "key" not in keys: - raise ConfigurationError("must have a key (name) in the cookie params") - - def _validate_jwt_decode_options(self): - """check the jwt_decode_options, and raise a ConfigurationError if there is something wrong""" - if self.jwt_decode_options is None: - self.jwt_decode_options = {} - return - - valid_keys = { - "verify_signature", - "verify_aud", - "verify_iat", - "verify_exp", - "verify_nbf", - "verify_iss", - "verify_sub", - "verify_jti", - "verify_at_hash", - "leeway", - } - keys = set(self.jwt_decode_options.keys()) - unknown = keys - valid_keys - if unknown: - raise ConfigurationError(f"unexpected key in jwt_decode_options: {', '.join(unknown)}") - - def is_valid_authentication_type(self): - return True - - def requires_client_login(self): - return True - - def add_url_rules(self, app): - parse = urlparse(self.api_base_url) - app.add_url_rule(f"{parse.path}/login", "login", self.login, methods=["GET"]) - app.add_url_rule(f"{parse.path}/logout", "logout", self.logout, methods=["GET"]) - app.add_url_rule(f"{parse.path}/logout_redirect", "logout_redirect", self.logout_redirect, methods=["GET"]) - app.add_url_rule(f"{parse.path}/oauth2/callback", "callback", self.callback, methods=["GET"]) - - def complete_setup(self, flask_app): - self.oauth = OAuth(flask_app) - - self.client = self.oauth.register( - "auth0", - client_id=self.client_id, - client_secret=self.client_secret, - api_base_url=self.oauth_api_base_url, - refresh_token_url=f"{self.oauth_api_base_url}/oauth/token", - access_token_url=f"{self.oauth_api_base_url}/oauth/token", - authorize_url=f"{self.oauth_api_base_url}/authorize", - client_kwargs={"scope": "openid profile email offline_access"}, - ) - - def is_user_authenticated(self): - payload = self.get_userinfo() - return payload is not None - - def get_user_id(self): - payload = self.get_userinfo() - return payload.get("sub") if payload else None - - def get_user_name(self): - payload = self.get_userinfo() - return payload.get("name") if payload else None - - def get_user_email(self): - payload = self.get_userinfo() - return payload.get("email") if payload else None - - def get_user_picture(self): - payload = self.get_userinfo() - return payload.get("picture") if payload else None - - def update_response(self, response): - response.cache_control.update(dict(public=True, max_age=0, no_store=True, no_cache=True, must_revalidate=True)) - - def login(self): - callbackurl = f"{self.api_base_url}/oauth2/callback" - return_path = request.args.get("dataset", "") - return_to = f"{self.web_base_url}/{return_path}" - # save the return path in the session cookie, accessed in the callback function - session["oauth_callback_redirect"] = return_to - response = self.client.authorize_redirect(redirect_uri=callbackurl) - self.update_response(response) - return response - - def logout(self): - """ - We would like for the user to remain on the same dataset after logout. oauth requires that - the redirect `returnTo` path be whitelisted by the oauth server, therefore a level of - indirection is used. We first redirect to a single path "logout_redirect", and logout_redirect - will redirect the user's browser back to the current page. - """ - self.remove_tokens() - redirect_path = request.args.get("dataset", "") - redirect_to = f"{self.web_base_url}/{redirect_path}" - session["oauth_logout_redirect"] = redirect_to - - return_to = f"{self.api_base_url}/logout_redirect" - params = {"returnTo": return_to, "client_id": self.client_id} - response = redirect(self.client.api_base_url + "/v2/logout?" + urlencode(params)) - self.update_response(response) - return response - - def logout_redirect(self): - oauth_logout_redirect = session.pop("oauth_logout_redirect", "/") - response = redirect(oauth_logout_redirect) - self.update_response(response) - return response - - def callback(self): - data = self.client.authorize_access_token() - tokens = Tokens( - access_token=data.get("access_token"), - id_token=data.get("id_token"), - refresh_token=data.get("refresh_token"), - expires_at=data.get("expires_at"), - ) - self.save_tokens(tokens) - oauth_callback_redirect = session.pop("oauth_callback_redirect", "/") - response = redirect(oauth_callback_redirect) - self.update_response(response) - return response - - def get_tokens(self): - """Extract the tokens from the cookie, and store them in the flask global context""" - if "tokens" in g: - return g.tokens - - try: - if self.session_cookie: - value = session.get(self.CXG_TOKENS) - if value: - g.tokens = Tokens(**value) - else: - return None - else: - value = request.cookies.get(self.cookie_params["key"]) - if value is None: - return None - value = base64.b64decode(value) - value = json.loads(value) - g.tokens = Tokens(**value) - - except Exception: - # there are many types of exceptions that can be raise in the above section. - # It is impractical to list all the exceptions here, since that would be brittle. - # If an exception occurs, then return None, meaning that no token could be retrieved. - current_app.logger.warning(f"auth cookie is in the wrong format: {str(value)}") - g.pop("tokens", None) - return None - - return g.tokens - - def save_tokens(self, tokens): - g.tokens = tokens - if self.session_cookie: - session[self.CXG_TOKENS] = tokens.__dict__ - else: - - @after_this_request - def set_cookie(response): - args = self.cookie_params.copy() - value = base64.b64encode(json.dumps(tokens.__dict__).encode("utf-8")) - del args["key"] - try: - response.set_cookie(self.cookie_params["key"], value, **args) - except Exception as e: - raise AuthenticationError(f"unable to set_cookie {self.cookie_params}") from e - return response - - def remove_tokens(self): - g.pop("tokens", None) - if self.session_cookie: - if self.CXG_TOKENS in session: - del session[self.CXG_TOKENS] - else: - - @after_this_request - def remove_cookie(response): - response.set_cookie(self.cookie_params["key"], "", expires=0) - self.update_response(response) - return response - - def get_login_url(self, data_adaptor): - """Return the url for the login route""" - if data_adaptor and current_app.app_config.is_multi_dataset(): - return f"{self.api_base_url}/login?dataset={data_adaptor.uri_path}/" - else: - return f"{self.api_base_url}/login" - - def get_logout_url(self, data_adaptor): - """Return the url for the logout route""" - if data_adaptor and current_app.app_config.is_multi_dataset(): - return f"{self.api_base_url}/logout?dataset={data_adaptor.uri_path}/" - else: - return f"{self.api_base_url}/logout" - - def check_jwt_payload(self, id_token): - try: - unverified_header = jwt.get_unverified_header(id_token) - except JWTError: - return None - - rsa_key = {} - for key in self.jwks["keys"]: - if key["kid"] == unverified_header["kid"]: - rsa_key = { - "kty": key["kty"], - "kid": key["kid"], - "use": key["use"], - "n": key.get("n"), - "e": key.get("e"), - } - if rsa_key: - try: - payload = jwt.decode( - id_token, - rsa_key, - algorithms=self.algorithms, - audience=self.audience, - issuer=self.oauth_api_base_url + "/", - options=self.jwt_decode_options, - ) - return payload - - except ExpiredSignatureError: - # This exception is handled in get_userinfo - raise - except JWTClaimsError as e: - raise AuthenticationError(f"invalid claims {str(e)}") from e - except JWTError as e: - raise AuthenticationError(f"invalid signature: {str(e)}") from e - - raise AuthenticationError("Unable to find the appropriate key") - - def get_userinfo(self): - if not has_request_context(): - return None - - # check if the userinfo has been retrieved already in this request - if "userinfo" in g: - return g.get("userinfo") - - # if there is no id_token, return None (user is not authenticated) - tokens = self.get_tokens() - - if tokens is None or tokens.id_token is None: - return None - - try: - # check the jwt payload. This raises an AuthenticationError if the token is not valid. - # It the token has expired, we attempt to refresh the token - g.userinfo = self.check_jwt_payload(tokens.id_token) - return g.userinfo - - except ExpiredSignatureError: - tokens = self.refresh_expired_token(tokens.refresh_token) - if tokens is None or tokens.id_token is None: - return None - else: - try: - g.userinfo = self.check_jwt_payload(tokens.id_token) - return g.userinfo - except JWTError as e: - raise AuthenticationError(f"error during token refresh: {str(e)}") from e - - except AuthenticationError: - self.remove_tokens() - raise - - def refresh_expired_token(self, refresh_token): - params = { - "grant_type": "refresh_token", - "client_id": self.client_id, - "refresh_token": refresh_token, - "client_secret": self.client_secret, - } - headers = {"content-type": "application/x-www-form-urlencoded"} - request = requests.post(f"{self.oauth_api_base_url}/oauth/token", urlencode(params), headers=headers) - if request.status_code != 200: - # unable to refresh the token, log the user out - self.remove_tokens() - return None - data = request.json() - tokens = Tokens( - access_token=data.get("access_token"), - id_token=data.get("id_token"), - refresh_token=data.get("refresh_token", refresh_token), - expires_at=data.get("expires_at"), - ) - self.save_tokens(tokens) - return tokens - - -AuthTypeFactory.register("oauth", AuthTypeOAuth) diff --git a/backend/czi_hosted/auth/auth_session.py b/backend/czi_hosted/auth/auth_session.py deleted file mode 100644 index 4e9818e4..00000000 --- a/backend/czi_hosted/auth/auth_session.py +++ /dev/null @@ -1,40 +0,0 @@ -from flask import session -from uuid import uuid4 - -from backend.czi_hosted.auth.auth import AuthTypeBase, AuthTypeFactory - - -class AuthTypeSession(AuthTypeBase): - """Session based authentication. The user is always logged. The user id is a random number - associated with the session. This is a good choice for desktop servers.""" - - # key in the session token for userid - CXGUID = "cxguid" - - def __init__(self, app_config): - super().__init__() - - def is_valid_authentication_type(self): - return True - - def complete_setup(self, app): - pass - - def is_user_authenticated(self): - # always authenticated - return True - - def get_user_id(self): - if self.CXGUID not in session: - session[self.CXGUID] = uuid4().hex - session.permanent = True - return session[self.CXGUID] - - def get_user_name(self): - return "anonymous" - - def get_user_email(self): - return None - - -AuthTypeFactory.register("session", AuthTypeSession) diff --git a/backend/czi_hosted/auth/auth_test.py b/backend/czi_hosted/auth/auth_test.py deleted file mode 100644 index 40a2af0b..00000000 --- a/backend/czi_hosted/auth/auth_test.py +++ /dev/null @@ -1,80 +0,0 @@ -from flask import session, request, redirect, current_app - -from backend.czi_hosted.auth.auth import AuthTypeClientBase, AuthTypeFactory - - -class AuthTypeTest(AuthTypeClientBase): - """An authentication type for testing client based logins. When the login route is accessed - the user is automatically logged in with a default or configured username""" - - # key in session token with userid and username - CXGUID = "cxguid_test" - CXGUNAME = "cxguname_test" - CXGUEMAIL = "cxguemail_test" - CXGUPICTURE = "cxgupicture_test" - - def __init__(self, app_config): - super().__init__() - self.user_name = "test_account" - self.user_id = "id0001" - self.user_email = "test_account@test.com" - self.user_picture = None - - def is_valid_authentication_type(self): - return True - - def requires_client_login(self): - return True - - def add_url_rules(self, app): - app.add_url_rule("/login", "login", self.login, methods=["GET"]) - app.add_url_rule("/logout", "logout", self.logout, methods=["GET"]) - - def complete_setup(self, app): - pass - - def is_user_authenticated(self): - return self.CXGUID in session - - def get_user_id(self): - return session.get(self.CXGUID) - - def get_user_name(self): - return session.get(self.CXGUNAME) - - def get_user_email(self): - return session.get(self.CXGUEMAIL) - - def get_user_picture(self): - return session.get(self.CXGUPICTURE) - - def login(self): - args = request.args - return_to = args.get("dataset", "/") - session[self.CXGUID] = args.get("userid", self.user_id) - session[self.CXGUNAME] = args.get("username", self.user_name) - session[self.CXGUEMAIL] = args.get("email", self.user_email) - session[self.CXGUPICTURE] = args.get("picture", self.user_picture) - return redirect(return_to) - - def logout(self): - session.clear() - return_to = request.args.get("dataset", "/") - return redirect(return_to) - - def get_login_url(self, data_adaptor): - """Return the url for the login route""" - if current_app.app_config.is_multi_dataset(): - return f"/login?dataset={data_adaptor.uri_path}" - else: - return "/login" - - def get_logout_url(self, data_adaptor): - """Return the url for the logout route""" - if current_app.app_config.is_multi_dataset(): - return f"/logout?dataset={data_adaptor.uri_path}" - else: - return "/logout" - - -AuthTypeFactory.register("test", AuthTypeTest) diff --git a/backend/czi_hosted/cli/__init__.py b/backend/czi_hosted/cli/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/cli/cli.py b/backend/czi_hosted/cli/cli.py deleted file mode 100644 index f8f7fde6..00000000 --- a/backend/czi_hosted/cli/cli.py +++ /dev/null @@ -1,35 +0,0 @@ -import click - -from .convert_to_cxg import convert_to_cxg -from .launch import launch -from .prepare import prepare -from .upgrade import log_upgrade_check -from .schema import schema_cli -from .. import __version__ - - -@click.group( - name="cellxgene", - subcommand_metavar="COMMAND ", - options_metavar="", - context_settings=dict(max_content_width=85, help_option_names=["-h", "--help"]), -) -@click.help_option("--help", "-h", help="Show this message and exit.") -@click.version_option( - version=__version__, - prog_name="cellxgene", - message="[%(prog)s] Version %(version)s", - help="Show the software version and exit.", -) -@click.option( - "--upgrade-check/--no-upgrade-check", default=True, show_default=True, help="Check for release upgrades on start.", -) -def cli(upgrade_check): - if upgrade_check: - log_upgrade_check() - - -cli.add_command(launch) -cli.add_command(prepare) -cli.add_command(convert_to_cxg) -cli.add_command(schema_cli) diff --git a/backend/czi_hosted/cli/convert_to_cxg.py b/backend/czi_hosted/cli/convert_to_cxg.py deleted file mode 100644 index 8c5ce2e6..00000000 --- a/backend/czi_hosted/cli/convert_to_cxg.py +++ /dev/null @@ -1,133 +0,0 @@ -from os import path - -import click - -from backend.czi_hosted.converters.h5ad_data_file import H5ADDataFile - - -@click.command( - name="convert", - short_help="Converts an H5AD dataset to the CXG format.", - help="Converts an H5AD dataset to the CXG format. The CXG format is a cellxgene-private data format " - "that has performance and access characteristics amenable to a multi-dataset, multi-user serving " - "environment. You will be able to launch the cellxgene using the `cellxgene launch` command as " - "usually with the generated CXG file.", -) -@click.argument( - "input-file", nargs=1, type=click.Path(exists=True, dir_okay=False), -) -@click.option( - "-o", - "--output-directory", - help="Name of the output CXG directory. If not provided, will default to be the input filename with a " - "CXG extension.", -) -@click.option( - "-b", - "--backed", - help="When true, loads the H5AD in file backed mode. This will cause the conversion to be slower, " - "but will use less memory.", - default=False, - show_default=True, - is_flag=True, -) -@click.option( - "-t", - "--title", - help="Human readable dataset title that will be included as metadata about the CXG file. If omitted, " - "the dataset title will be the filename.", -) -@click.option( - "-a", - "--about", - help="A fully qualified URL that provides more information about the dataset and will be included as " - "metadata about the CXG file.", -) -@click.option( - "-s", - "--sparse-threshold", - help="If the dataset's percent of non-zero values falls belows the specified threshold, then the X " - "array of the dataset will be sparse. Since the default value is 0.0, the default will be to " - "convert to dense array.", - default=0.0, - show_default=True, -) -@click.option( - "--obs-names", - help="Name to a column in the obs dataframe that will be used as the index for the dataframe instead of " - "the one designated by the dataframe generated-index.", -) -@click.option( - "--var-names", - help="Name to a column in the var dataframe that will be used as the index for the dataframe instead of " - "the one designated by the dataframe generated-index.", -) -@click.option( - "--disable-custom-colors", - help="When set, conversion process will not extract scanpy-compatible category colors from the H5AD file.", - default=False, - show_default=True, - is_flag=True, -) -@click.option( - "--disable-corpora-schema", - help="When set, conversion process will neither extract nor store Corpora schema information. See " - "https://github.com/chanzuckerberg/corpora-data-portal/blob/main/backend/schema/corpora_schema.md for more " - "information.", - default=False, - show_default=True, - is_flag=True, -) -@click.option( - "--overwrite", - help="When set to true, will overwrite the output file if the output file already exists.", - default=False, - show_default=True, - is_flag=True, -) -@click.help_option("--help", "-h", help="Show this message and exit.") -def convert_to_cxg( - input_file, - output_directory, - backed, - title, - about, - sparse_threshold, - obs_names, - var_names, - disable_custom_colors, - disable_corpora_schema, - overwrite, -): - """ - Convert a dataset file into CXG. - """ - - h5ad_data_file = H5ADDataFile( - input_file, backed, title, about, obs_names, var_names, use_corpora_schema=not disable_corpora_schema - ) - - # Get the directory that will hold all the CXG files - cxg_output_container = get_output_directory(input_file, output_directory, overwrite) - - h5ad_data_file.to_cxg( - cxg_output_container, sparse_threshold, convert_anndata_colors_to_cxg_colors=not disable_custom_colors - ) - - -def get_output_directory(input_filename, output_directory, should_overwrite): - """ - Get the name of the CXG output directory to be created/populated during the dataset conversion. - """ - - if output_directory and (not path.isdir(output_directory) or (path.isdir(output_directory) and should_overwrite)): - if output_directory.endswith(".cxg"): - return output_directory - return output_directory + ".cxg" - if output_directory and path.isdir(output_directory) and not should_overwrite: - raise click.BadParameter( - f"Output directory {output_directory} already exists. If you'd like to overwrite, then run the command " - f"with the --overwrite flag." - ) - - return path.splitext(input_filename)[0] + ".cxg" diff --git a/backend/czi_hosted/cli/launch.py b/backend/czi_hosted/cli/launch.py deleted file mode 100644 index dd025ffc..00000000 --- a/backend/czi_hosted/cli/launch.py +++ /dev/null @@ -1,432 +0,0 @@ -import errno -import functools -import logging -import sys -import webbrowser -import os -import click -from flask_compress import Compress -from flask_cors import CORS - -from backend.czi_hosted.default_config import default_config -from backend.czi_hosted.app.app import Server -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.errors import DatasetAccessError, ConfigurationError -from backend.common.utils.utils import sort_options - - -DEFAULT_CONFIG = AppConfig() - - -def annotation_args(func): - @click.option( - "--disable-annotations", - is_flag=True, - default=not DEFAULT_CONFIG.default_dataset_config.user_annotations__enable, - show_default=True, - help="Disable user annotation of data.", - ) - @click.option( - "--annotations-file", - default=DEFAULT_CONFIG.default_dataset_config.user_annotations__local_file_csv__file, - show_default=True, - multiple=False, - metavar="", - help="CSV file to initialize editing of existing annotations; will be altered in-place. " - "Incompatible with --annotations-dir.", - ) - @click.option( - "--annotations-dir", - default=DEFAULT_CONFIG.default_dataset_config.user_annotations__local_file_csv__directory, - show_default=False, - multiple=False, - metavar="", - help="Directory of where to save output annotations; filename will be specified in the application. " - "Incompatible with --annotations-file.", - ) - @functools.wraps(func) - def wrapper(*args, **kwargs): - return func(*args, **kwargs) - - return wrapper - - -def config_args(func): - @click.option( - "--max-category-items", - default=DEFAULT_CONFIG.default_dataset_config.presentation__max_categories, - metavar="", - show_default=True, - help="Will not display categories with more distinct values than specified.", - ) - @click.option( - "--disable-custom-colors", - is_flag=True, - default=False, - show_default=False, - help="Disable user-defined category-label colors drawn from source data file.", - ) - @click.option( - "--diffexp-lfc-cutoff", - "-de", - default=DEFAULT_CONFIG.default_dataset_config.diffexp__lfc_cutoff, - show_default=True, - metavar="", - help="Minimum log fold change threshold for differential expression.", - ) - @click.option( - "--disable-diffexp", - is_flag=True, - default=not DEFAULT_CONFIG.default_dataset_config.diffexp__enable, - show_default=False, - help="Disable on-demand differential expression.", - ) - @click.option( - "--embedding", - "-e", - default=DEFAULT_CONFIG.default_dataset_config.embeddings__names, - multiple=True, - show_default=False, - metavar="", - help="Embedding name, eg, 'umap'. Repeat option for multiple embeddings. Defaults to all.", - ) - @functools.wraps(func) - def wrapper(*args, **kwargs): - return func(*args, **kwargs) - - return wrapper - - -def dataset_args(func): - @click.option( - "--obs-names", - "-obs", - default=DEFAULT_CONFIG.server_config.single_dataset__obs_names, - metavar="", - help="Name of annotation field to use for observations. If not specified cellxgene will use the the obs index.", - ) - @click.option( - "--var-names", - "-var", - default=DEFAULT_CONFIG.server_config.single_dataset__var_names, - metavar="", - help="Name of annotation to use for variables. If not specified cellxgene will use the the var index.", - ) - @click.option( - "--backed", - "-b", - is_flag=True, - default=DEFAULT_CONFIG.server_config.adaptor__anndata_adaptor__backed, - show_default=False, - help="Load anndata in file-backed mode. " "This may save memory, but may result in slower overall performance.", - ) - @click.option( - "--title", - "-t", - default=DEFAULT_CONFIG.server_config.single_dataset__title, - metavar="", - help="Title to display. If omitted will use file name.", - ) - @click.option( - "--about", - default=DEFAULT_CONFIG.server_config.single_dataset__about, - metavar="", - help="URL providing more information about the dataset (hint: must be a fully specified absolute URL).", - ) - @functools.wraps(func) - def wrapper(*args, **kwargs): - return func(*args, **kwargs) - - return wrapper - - -def server_args(func): - @click.option( - "--debug", - "-d", - is_flag=True, - default=DEFAULT_CONFIG.server_config.app__debug, - show_default=True, - help="Run in debug mode. This is helpful for cellxgene developers, " - "or when you want more information about an error condition.", - ) - @click.option( - "--verbose", - "-v", - is_flag=True, - default=DEFAULT_CONFIG.server_config.app__verbose, - show_default=True, - help="Provide verbose output, including warnings and all server requests.", - ) - @click.option( - "--port", - "-p", - metavar="", - default=DEFAULT_CONFIG.server_config.app__port, - type=int, - show_default=True, - help="Port to run server on. If not specified cellxgene will find an available port.", - ) - @click.option( - "--host", - metavar="", - default=DEFAULT_CONFIG.server_config.app__host, - show_default=False, - help="Host IP address. By default cellxgene will use localhost (e.g. 127.0.0.1).", - ) - @click.option( - "--scripts", - "-s", - default=DEFAULT_CONFIG.default_dataset_config.app__scripts, - multiple=True, - metavar="", - help="Additional script files to include in HTML page. If not specified, " - "no additional script files will be included.", - show_default=False, - ) - @functools.wraps(func) - def wrapper(*args, **kwargs): - return func(*args, **kwargs) - - return wrapper - - -def launch_args(func): - @annotation_args - @config_args - @dataset_args - @server_args - @click.option( - "--dataroot", - default=DEFAULT_CONFIG.server_config.multi_dataset__dataroot, - metavar="", - help="Enable cellxgene to serve multiple files. Supply path (local directory or URL)" - " to folder containing H5AD and/or CXG datasets.", - hidden=True, - ) # TODO, unhide when dataroot is supported) - @click.argument("datapath", required=False, metavar="") - @click.option( - "--open", - "-o", - "open_browser", - is_flag=True, - default=DEFAULT_CONFIG.server_config.app__open_browser, - show_default=True, - help="Open web browser after launch.", - ) - @click.option( - "--config-file", - "-c", - "config_file", - default=None, - show_default=True, - help="Location to yaml file with configuration settings", - ) - @click.option( - "--dump-default-config", - "dump_default_config", - is_flag=True, - default=False, - show_default=True, - help="Print default configuration settings and exit", - ) - @click.help_option("--help", "-h", help="Show this message and exit.") - @functools.wraps(func) - def wrapper(*args, **kwargs): - return func(*args, **kwargs) - - return wrapper - - -def handle_scripts(scripts): - if scripts: - click.echo( - r""" - / / /\ \ \__ _ _ __ _ __ (_)_ __ __ _ - \ \/ \/ / _` | '__| '_ \| | '_ \ / _` | - \ /\ / (_| | | | | | | | | | | (_| | - \/ \/ \__,_|_| |_| |_|_|_| |_|\__, | - |___/ - The --scripts flag is intended for developers to include google analytics etc. You could be opening yourself to a - security risk by including the --scripts flag. Make sure you trust the scripts that you are including. - """ - ) - scripts_pretty = ", ".join(scripts) - click.confirm(f"Are you sure you want to inject these scripts: {scripts_pretty}?", abort=True) - - -class CliLaunchServer(Server): - """ - the CLI runs a local web server, and needs to enable a few more features. - """ - - def __init__(self, app_config): - super().__init__(app_config) - - @staticmethod - def _before_adding_routes(app, app_config): - app.config["COMPRESS_MIMETYPES"] = [ - "text/html", - "text/css", - "text/xml", - "application/json", - "application/javascript", - "application/octet-stream", - ] - Compress(app) - if app_config.server_config.app__debug: - CORS(app, supports_credentials=True) - - -@sort_options -@click.command( - short_help="Launch the cellxgene data viewer. " "Run `cellxgene launch --help` for more information.", - options_metavar="", -) -@launch_args -def launch( - datapath, - dataroot, - verbose, - debug, - open_browser, - port, - host, - embedding, - obs_names, - var_names, - max_category_items, - disable_custom_colors, - diffexp_lfc_cutoff, - title, - scripts, - about, - disable_annotations, - annotations_file, - annotations_dir, - backed, - disable_diffexp, - config_file, - dump_default_config, -): - """Launch the cellxgene data viewer. - This web app lets you explore single-cell expression data. - Data must be in a format that cellxgene expects. - Read the "getting started" guide to learn more: - https://chanzuckerberg.github.io/cellxgene/getting-started.html - - Examples: - - > cellxgene launch example-dataset/pbmc3k.h5ad --title pbmc3k - - > cellxgene launch --title - - > cellxgene launch """ - - # TODO Examples to provide when "--dataroot" is unhidden - # > cellxgene launch --dataroot example-dataset/ - # - # > cellxgene launch --dataroot - - if dump_default_config: - print(default_config) - sys.exit(0) - # Startup message - click.echo("[cellxgene] Starting the CLI...") - - # app config - app_config = AppConfig() - server_config = app_config.server_config - - try: - if config_file: - app_config.update_from_config_file(config_file) - - # Determine which config options were give on the command line. - # Those will override the ones provided in the config file (if provided). - cli_config = AppConfig() - cli_config.update_server_config( - app__verbose=verbose, - app__debug=debug, - app__host=host, - app__port=port, - app__open_browser=open_browser, - single_dataset__datapath=datapath, - single_dataset__title=title, - single_dataset__about=about, - single_dataset__obs_names=obs_names, - single_dataset__var_names=var_names, - multi_dataset__dataroot=dataroot, - adaptor__anndata_adaptor__backed=backed, - ) - cli_config.update_default_dataset_config( - app__scripts=scripts, - user_annotations__enable=not disable_annotations, - user_annotations__local_file_csv__file=annotations_file, - user_annotations__local_file_csv__directory=annotations_dir, - presentation__max_categories=max_category_items, - presentation__custom_colors=not disable_custom_colors, - embeddings__names=embedding, - diffexp__enable=not disable_diffexp, - diffexp__lfc_cutoff=diffexp_lfc_cutoff, - ) - - diff = cli_config.server_config.changes_from_default() - changes = {key: val for key, val, _ in diff} - app_config.update_server_config(**changes) - - diff = cli_config.default_dataset_config.changes_from_default() - changes = {key: val for key, val, _ in diff} - app_config.update_default_dataset_config(**changes) - - # process the configuration - # any errors will be thrown as an exception. - # any info messages will be passed to the messagefn function. - - def messagefn(message): - click.echo("[cellxgene] " + message) - - # Use a default secret if one is not provided - if not server_config.app__flask_secret_key: - app_config.update_server_config(app__flask_secret_key="SparkleAndShine") - - app_config.complete_config(messagefn) - - except (ConfigurationError, DatasetAccessError) as e: - raise click.ClickException(e) - - handle_scripts(scripts) - - # create the server - server = CliLaunchServer(app_config) - - if not server_config.app__verbose: - log = logging.getLogger("werkzeug") - log.setLevel(logging.ERROR) - - cellxgene_url = f"http://{app_config.server_config.app__host}:{app_config.server_config.app__port}" - if server_config.app__open_browser: - click.echo(f"[cellxgene] Launching! Opening your browser to {cellxgene_url} now.") - webbrowser.open(cellxgene_url) - else: - click.echo(f"[cellxgene] Launching! Please go to {cellxgene_url} in your browser.") - - click.echo("[cellxgene] Type CTRL-C at any time to exit.") - - if not server_config.app__verbose: - f = open(os.devnull, "w") - sys.stdout = f - - try: - server.app.run( - host=server_config.app__host, - debug=server_config.app__debug, - port=server_config.app__port, - threaded=not server_config.app__debug, - use_debugger=False, - use_reloader=False, - ) - except OSError as e: - if e.errno == errno.EADDRINUSE: - raise click.ClickException("Port is in use, please specify an open port using the --port flag.") from e - raise diff --git a/backend/czi_hosted/cli/prepare.py b/backend/czi_hosted/cli/prepare.py deleted file mode 100644 index 5b6b467e..00000000 --- a/backend/czi_hosted/cli/prepare.py +++ /dev/null @@ -1,274 +0,0 @@ -from os.path import expanduser, isdir, isfile, sep, splitext - -import click -import pandas as pd -from numpy import ndarray, unique -from scipy.sparse.csc import csc_matrix - -from backend.common.utils.utils import sort_options - - -@sort_options -@click.command( - short_help="Preprocess data for use with cellxgene. " "Run `cellxgene prepare --help` for more information.", - options_metavar="", -) -@click.argument("data", nargs=1, metavar="", required=True) -@click.option( - "--embedding", - "-e", - default=["umap", "tsne"], - multiple=True, - type=click.Choice(["umap", "tsne"]), - help="Embedding algorithm(s). Repeat option for multiple embeddings.", - show_default=True, -) -@click.option( - "--recipe", "-r", default="none", type=click.Choice(["none", "seurat", "zheng17"]), show_default=True, -) -@click.option("--output", "-o", default="", help="Save a new file to filename.", metavar="") -@click.option("--plotting", "-p", default=False, is_flag=True, help="Generate plots.", show_default=True) -@click.option("--sparse", default=False, is_flag=True, help="Force sparsity.", show_default=True) -@click.option("--overwrite", default=False, is_flag=True, help="Allow file overwriting.", show_default=True) -@click.option("--set-obs-names", default="", help="Named field to set as index for obs.", metavar="") -@click.option("--set-var-names", default="", help="Named field to set as index for var.", metavar="") -@click.option( - "--skip-qc", - default=False, - is_flag=True, - help="Do not run quality control metrics. By default cellxgene runs them " - "(saved to adata.obs and adata.var; see scanpy.pp.calculate_qc_metrics for details).", -) -@click.option( - "--make-obs-names-unique/--no-make-obs-names-unique", - default=True, - help="Ensure obs index is unique.", - show_default=True, -) -@click.option( - "--make-var-names-unique/--no-make-var-names-unique", - default=True, - help="Ensure var index is unique.", - show_default=True, -) -@click.help_option("--help", "-h", help="Show this message and exit.") -def prepare( - data, - embedding, - recipe, - output, - plotting, - sparse, - overwrite, - set_obs_names, - set_var_names, - skip_qc, - make_obs_names_unique, - make_var_names_unique, -): - """ - Preprocess data for use with cellxgene. - This tool runs a series of scanpy routines for preparing a dataset for use - with cellxgene. It loads data from different formats - (h5ad, loom, or a 10x directory), runs dimensionality reduction, - computes nearest neighbors, computes an embedding, performs clustering, - and saves the results. Includes additional options for naming annotations, - ensuring sparsity, and plotting results. - """ - - # collect slow imports here to make CLI startup more responsive - click.echo("[cellxgene] Starting CLI...") - try: - import matplotlib - - matplotlib.use("Agg") - import scanpy as sc - except ImportError: - raise click.ClickException( - "[cellxgene] cellxgene prepare has not been installed. Please run `pip install 'cellxgene[prepare]'` " - "to install the necessary requirements." - ) - - # scanpy settings - sc.settings.verbosity = 0 - sc.settings.autosave = True - - # check args - if sparse and not recipe == "none": - raise click.UsageError("Cannot use a recipe when forcing sparsity") - - output = expanduser(output) - - if not output: - click.echo( - "Warning: No file will be saved, to save the results of cellxgene prepare include " - "--output to save output to a new file" - ) - if isfile(output) and not overwrite: - raise click.UsageError(f"Cannot overwrite existing file {output}, try using the flag --overwrite") - - def load_data(data): - if isfile(data): - name, extension = splitext(data) - if extension == ".h5ad": - adata = sc.read_h5ad(data) - elif extension == ".loom": - adata = sc.read_loom(data) - else: - raise click.FileError(data, hint="does not have a valid extension [.h5ad | .loom]") - elif isdir(data): - if not data.endswith(sep): - data += sep - adata = sc.read_10x_mtx(data) - else: - raise click.FileError(data, hint="not a valid file or path") - - if not set_obs_names == "": - if set_obs_names not in adata.obs_keys(): - raise click.UsageError(f"obs {set_obs_names} not found, options are: {adata.obs_keys()}") - adata.obs_names = adata.obs[set_obs_names] - if not set_var_names == "": - if set_var_names not in adata.var_keys(): - raise click.UsageError(f"var {set_var_names} not found, options are: {adata.var_keys()}") - adata.var_names = adata.var[set_var_names] - if make_obs_names_unique: - adata.obs.index = make_index_unique(adata.obs.index) - if make_var_names_unique: - adata.var.index = make_index_unique(adata.var.index) - if not adata._obs.index.is_unique: - click.echo("Warning: obs index is not unique") - if not adata._var.index.is_unique: - click.echo("Warning: var index is not unique") - return adata - - def calculate_qc_metrics(adata): - if not skip_qc: - sc.pp.calculate_qc_metrics(adata, inplace=True) - return adata - - def make_sparse(adata): - if (type(adata.X) is ndarray) and sparse: - adata.X = csc_matrix(adata.X) - - def run_recipe(adata): - if recipe == "seurat": - sc.pp.recipe_seurat(adata) - elif recipe == "zheng17": - sc.pp.recipe_zheng17(adata) - else: - sc.pp.filter_cells(adata, min_genes=5) - sc.pp.filter_genes(adata, min_cells=25) - if sparse: - sc.pp.scale(adata, zero_center=False) - else: - sc.pp.scale(adata) - - def run_pca(adata): - if sparse: - sc.pp.pca(adata, svd_solver="arpack", zero_center=False) - else: - sc.pp.pca(adata, svd_solver="arpack") - - def run_neighbors(adata): - sc.pp.neighbors(adata) - - def run_louvain(adata): - sc.tl.louvain(adata) - - def run_embedding(adata): - if len(unique(adata.obs["louvain"].values)) < 10: - palette = "tab10" - else: - palette = "tab20" - - if "umap" in embedding: - sc.tl.umap(adata) - if plotting: - sc.pl.umap(adata, color="louvain", palette=palette, save="_louvain") - - if "tsne" in embedding: - sc.tl.tsne(adata) - if plotting: - sc.pl.tsne(adata, color="louvain", palette=palette, save="_louvain") - - def show_step(item): - if not skip_qc: - qc_name = "Calculating QC metrics" - else: - qc_name = "Skipping QC" - names = { - "calculate_qc_metrics": qc_name, - "make_sparse": "Ensuring sparsity", - "run_recipe": f'Running preprocessing recipe "{recipe}"', - "run_pca": "Running PCA", - "run_neighbors": "Calculating neighbors", - "run_louvain": "Calculating clusters", - "run_embedding": "Computing embedding", - } - if item is not None: - return names[item.__name__] - - steps = [calculate_qc_metrics, make_sparse, run_recipe, run_pca, run_neighbors, run_louvain, run_embedding] - - click.echo(f"[cellxgene] Loading data from {data}, please wait...") - adata = load_data(data) - - click.echo("[cellxgene] Beginning preprocessing...") - with click.progressbar(steps, label="[cellxgene] Progress", show_eta=False, item_show_func=show_step) as bar: - for step in bar: - step(adata) - - # saving - if not output == "": - click.echo(f"[cellxgene] Saving results to {output}...") - adata.write(output) - - click.echo("[cellxgene] Success!") - - -# TODO (mweiden): remove this once this issue is resolved https://github.com/theislab/anndata/issues/344 -# Note: tentative solution here https://github.com/theislab/anndata/pull/345 -def make_index_unique(index: pd.Index, join: str = "-"): - """ - Makes the index unique by appending a number string to each duplicate index element: '1', '2', etc. - - If a tentative name created by the algorithm already exists in the index, it tries the next integer in the sequence. - - The first occurrence of a non-unique value is ignored. - Parameters - ---------- - join - The connecting string between name and integer. - Examples - -------- - >>> from anndata import AnnData - >>> adata1 = AnnData(np.ones((3, 2)), dict(obs_names=['a', 'b', 'c'])) - >>> adata2 = AnnData(np.zeros((3, 2)), dict(obs_names=['d', 'b', 'b'])) - >>> adata = adata1.concatenate(adata2) - >>> adata.obs_names - Index(['a', 'b', 'c', 'd', 'b', 'b'], dtype='object') - >>> adata.obs_names_make_unique() - >>> adata.obs_names - Index(['a', 'b', 'c', 'd', 'b-1', 'b-2'], dtype='object') - """ - if index.is_unique: - return index - from collections import defaultdict - - values = index.values - values_set = set(values) - indices_dup = index.duplicated(keep="first") - values_dup = values[indices_dup] - counter = defaultdict(lambda: 0) - for i, v in enumerate(values_dup): - while True: - counter[v] += 1 - tentative_new_name = v + join + str(counter[v]) - if tentative_new_name not in values_set: - values_set.add(tentative_new_name) - values_dup[i] = tentative_new_name - break - - values[indices_dup] = values_dup - index = pd.Index(values) - return index diff --git a/backend/czi_hosted/cli/schema.py b/backend/czi_hosted/cli/schema.py deleted file mode 100644 index 8e26ff5a..00000000 --- a/backend/czi_hosted/cli/schema.py +++ /dev/null @@ -1,72 +0,0 @@ -import click - -from backend.czi_hosted.converters.schema import remix, validate - - -@click.group( - name="schema", - subcommand_metavar="COMMAND ", - short_help="Apply and validate the cellxgene data integration schema to an h5ad file.", - context_settings=dict(max_content_width=85, help_option_names=["-h", "--help"]), -) -def schema_cli(): - try: - import scanpy # noqa: F401 - except ImportError: - raise click.ClickException( - "[cellxgene] cellxgene schema requires scanpy" - ) - - -@click.command( - name="apply", - short_help="(experimental) Apply the cellxgene data integration schema to an h5ad.", - help="(experimental) Using a yaml file that describes schema values to insert or convert and in input " - "h5ad file, apply the schema changes and create a new, conforming h5ad.", -) -@click.option( - "--source-h5ad", - help="Input h5ad file.", - nargs=1, - required=True, - type=click.Path(exists=True, dir_okay=False), -) -@click.option( - "--remix-config", - help="Config yaml with information on how to apply the schema.", - nargs=1, - required=True, - type=click.Path(exists=True, dir_okay=False), -) -@click.option( - "--output-filename", - help="Filename for the new, schema-conforming h5ad file.", - required=True, - nargs=1 -) -def schema_apply(source_h5ad, remix_config, output_filename): - remix.apply_schema(source_h5ad, remix_config, output_filename) - - -@click.command( - name="validate", - short_help="(experimental) Check that an h5ad follows the cellxgene data integration schema.", -) -@click.argument( - "h5ad", - nargs=1, - type=click.Path(exists=True, dir_okay=False), -) -@click.option( - "--shallow", - help="When true, just check that the correct version information is present.", - default=False, - show_default=True, - is_flag=True, -) -def schema_validate(h5ad, shallow): - validate.validate(h5ad, shallow) - - -schema_cli.add_command(schema_apply) -schema_cli.add_command(schema_validate) diff --git a/backend/czi_hosted/cli/upgrade.py b/backend/czi_hosted/cli/upgrade.py deleted file mode 100644 index 222d7e81..00000000 --- a/backend/czi_hosted/cli/upgrade.py +++ /dev/null @@ -1,85 +0,0 @@ -import re - -import click -import requests -from requests.exceptions import ConnectionError - -from .. import __version__ - -# Official SemVer regex: https://semver.org/ -SEMVER_FORMAT = re.compile( - r"^(?P0|[1-9]\d*)\.(?P0|[1-9]\d*)\.(?P0|[1-9]\d*)(?:-(?P(?:0|[1-9]\d*|\d*[" - r"a-zA-Z-][0-9a-zA-Z-]*)(?:\.(?:0|[1-9]\d*|\d*[a-zA-Z-][0-9a-zA-Z-]*))*))?(?:\+(?P[0-9a-zA-Z-]+(" - r"?:\.[0-9a-zA-Z-]+)*))?$" -) - - -def log_upgrade_check(): - # Sanity-check that the CLI version is a properly-formatted SemVer string - assert validate_version_str(__version__, release_only=False) - - # Get the current latest release - try: - release_tag_generator = (r["tag_name"] for r in _request_cellxgene_releases()) - latest_release = next(release_tag_generator, lambda tag_name: validate_version_str(tag_name)) - if version_gt(latest_release, __version__): - click.echo(f"There's a new version of cellxgene available ({latest_release})!", err=True) - click.echo("To upgrade, run the following: pip install --upgrade cellxgene\n", err=True) - except (ConnectionError, RateLimitException): - click.echo("Upgrade check failed.\n") - - -class RateLimitException(Exception): - """ - Github API Rate Limit Exception - """ - - -def _request_cellxgene_releases(): - def raise_on_rate_limit(response): - if response.status_code == 403 and res.headers.get("X-RateLimit-Remaining") == "0": - raise RateLimitException - - url = "https://api.github.com/repos/chanzuckerberg/cellxgene/releases" - res = requests.get(url) - raise_on_rate_limit(res) - for release in res.json(): - yield release - while "next" in res.links.keys(): - res = requests.get(res.links["next"]["url"]) - raise_on_rate_limit(res) - for release in res.json(): - yield release - - -def validate_version_str(version_str, release_only=True): - """ - Test if a string conforms to SemVer format (https://semver.org/) - :param version_str: a string to be validated - :param release_only: only declare releases (not prereleases) valid - :return: True if the version string is of a valid SemVer format else False - """ - match = SEMVER_FORMAT.match(version_str) - has_match = match is not None - if has_match and release_only: - return not match.group("prerelease") - return has_match - - -def split_version(version_string): - """ - Split a SemVer-formatted string into its component integers - :param version_string: a SemVer string to be split - :return: an array of three integers - """ - match = SEMVER_FORMAT.match(version_string) - return [int(match.group(group)) for group in ["major", "minor", "patch"]] - - -def version_gt(left_version, right_version): - for left, right in zip(split_version(left_version), split_version(right_version)): - if left > right: - return True - elif right > left: - return False - return False diff --git a/backend/czi_hosted/common/__init__.py b/backend/czi_hosted/common/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/common/annotations/__init__.py b/backend/czi_hosted/common/annotations/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/common/annotations/annotations.py b/backend/czi_hosted/common/annotations/annotations.py deleted file mode 100644 index 87851f03..00000000 --- a/backend/czi_hosted/common/annotations/annotations.py +++ /dev/null @@ -1,110 +0,0 @@ -import os - -from flask import current_app, has_request_context - -from backend.common.errors import DisabledFeatureError -from backend.common.utils.type_conversion_utils import get_schema_type_hint_of_array -from backend.common.genesets import write_gene_sets_tidycsv, read_gene_sets_tidycsv, validate_gene_sets -from backend.common.utils.data_locator import DataLocator -from backend.common.utils.utils import path_join - - -class Annotations: - """baseclass for annotations and genesets""" - - def __init__(self, config={}): - self.config = config - - def user_annotations_enabled(self): - return self.config.get("user-annotations", False) - - def check_user_annotations_enabled(self): - if not self.user_annotations_enabled(): - raise DisabledFeatureError("User annotations are disabled.") - - def get_schema(self, data_adaptor): - schema = [] - labels = self.read_labels(data_adaptor) - if labels is not None and not labels.empty: - for col in labels.columns: - col_schema = dict(name=col, writable=True) - col_schema.update(get_schema_type_hint_of_array(labels[col])) - schema.append(col_schema) - - return schema - - def set_collection(self, name): - """set or create a new annotation collection""" - raise NotImplementedError - - def read_labels(self, data_adaptor): - """Return the labels as a pandas.DataFrame""" - raise NotImplementedError - - def write_labels(self, df, data_adaptor): - """Write the labels (df) to a persistent storage such that it can later be read""" - raise NotImplementedError - - def update_parameters(self, parameters, data_adaptor): - """Update configuration parameters that describe information about the annotations feature""" - params = {} - params["annotations_genesets_readonly"] = True - params["annotations_genesets_name_is_read_only"] = True - parameters.update(params) - - @staticmethod - def gene_sets_to_csv(genesets): - """ - Convert the internal genesets format (returned by read_gene_set) into - the simple Tidy CSV. - """ - from io import StringIO - - if isinstance(genesets, dict): - genesets = genesets.values() - - with StringIO() as sio: - write_gene_sets_tidycsv(sio, genesets) - return sio.getvalue() - - @staticmethod - def gene_sets_to_response(genesets): - """ - Convert the internal genesets format (returned by read_gene_set) into - the dict expected by the JSON REST API - """ - return list(genesets.values()) - - def read_gene_sets(self, data_adaptor, context=None): - if has_request_context(): - if not current_app.auth.is_user_authenticated(): - return ({}, 0) - - gene_sets_uri_or_path = dataset_uri_to_geneset_uri(data_adaptor.data_locator.uri_or_path) - - server_config = data_adaptor.server_config - region_name = None if server_config is None else server_config.data_locator__s3__region_name - gene_sets_locator = DataLocator(gene_sets_uri_or_path, region_name=region_name) - if not gene_sets_locator.exists(): - return ({}, 0) - - gene_sets = read_gene_sets_tidycsv(gene_sets_locator, context) - schema = data_adaptor.get_schema() - var_index = schema["annotations"]["var"].get("index", "index") - var_names = set(data_adaptor.query_var_array(var_index)) - - gene_sets = validate_gene_sets(gene_sets, var_names) - return (gene_sets, 0) - - -def dataset_uri_to_geneset_uri(data_uri_or_path): - """given a dataset URI, return the associated gene set URI""" - data_basename = os.path.basename(data_uri_or_path) - base, ext = os.path.splitext(data_basename) - if ext is not None: # strip extension, if any - data_basename = base - - genesets_basename = f"{data_basename}-genesets.csv" - gene_sets_uri_or_path = path_join(data_uri_or_path, "..", genesets_basename) - - return gene_sets_uri_or_path diff --git a/backend/czi_hosted/common/annotations/hosted_tiledb.py b/backend/czi_hosted/common/annotations/hosted_tiledb.py deleted file mode 100644 index 733185a3..00000000 --- a/backend/czi_hosted/common/annotations/hosted_tiledb.py +++ /dev/null @@ -1,167 +0,0 @@ -import json -import os -import re -import time - -import pandas as pd -import tiledb -from flask import current_app - -from backend.czi_hosted.common.annotations.annotations import Annotations -from backend.common.errors import AnnotationCategoryNameError -from backend.czi_hosted.common.utils.sanitization_utils import sanitize_values_in_list -from backend.common.utils.type_conversion_utils import get_dtypes_and_schemas_of_dataframe, get_encoding_dtype_of_array -from backend.czi_hosted.db.cellxgene_orm import Annotation - - -class AnnotationsHostedTileDB(Annotations): - CXG_ANNO_COLLECTION = "cxg_anno_collection" - - def __init__(self, config, directory_path, db): - super().__init__(config) - self.db = db - if directory_path[-1] == "/": - self.directory_path = directory_path - else: - self.directory_path = directory_path + "/" - - def check_category_names(self, df): - original_category_names = df.keys().to_list() - sanitized_category_names = set(sanitize_values_in_list(original_category_names).values()) - unsanitary_original_category_names = set(original_category_names).difference(sanitized_category_names) - if unsanitary_original_category_names: - raise AnnotationCategoryNameError( - f"{unsanitary_original_category_names} are not valid category names, please resubmit" - ) - - def get_user_name(self): - return current_app.auth.get_user_name() - - def get_user_id(self): - return current_app.auth.get_user_id() - - def is_safe_collection_name(self, name): - """ - return true if this is a safe collection name - this is ultra conservative. If we want to allow full legal file name syntax, - we could look at modules like `pathvalidate` - """ - if name is None: - return False - return re.match(r"^[\w\-]+$", name) is not None - - def set_collection(self, name): - self.CXG_ANNO_COLLECTION = name - - def read_labels(self, data_adaptor): - user_id = self.get_user_id() - if user_id is None: - return - dataset_name = data_adaptor.get_location() - dataset_id = self.db.get_or_create_dataset(dataset_name) - - annotation_object = self.db.query_for_most_recent( - Annotation, [Annotation.user_id == user_id, Annotation.dataset_id == dataset_id] - ) - if annotation_object: - if annotation_object.tiledb_uri == "": - # this mean the user has removed all the categories. - return None - try: - df = tiledb.open(annotation_object.tiledb_uri) - except tiledb.TileDBError: - # don't crash if the annotations file is missing or can't be read. - current_app.logger.warning(f"Cannot read annotation file: {annotation_object.tiledb_uri}") - return None - pandas_df = self.convert_to_pandas_df(df, annotation_object.schema_hints) - return pandas_df - else: - return None - - def convert_to_pandas_df(self, tileDBArray, schema_hints): - repr_meta = None - index_dims = None - schema_hints = json.loads(schema_hints) - - if "__pandas_attribute_repr" in tileDBArray.meta: - # backwards compatibility... unsure if necessary at this point - repr_meta = json.loads(tileDBArray.meta["__pandas_attribute_repr"]) - if "__pandas_index_dims" in tileDBArray.meta: - index_dims = json.loads(tileDBArray.meta["__pandas_index_dims"]) - - data = tileDBArray[:] - indexes = list() - - for col_name, col_val in data.items(): - # If the column values are byte literals, decode them - if isinstance(col_val[0], bytes): - col_val = [value.decode("utf-8") for value in col_val] - - if schema_hints and col_name in schema_hints: - type = schema_hints.get(col_name).get("type") - if type and type == "categorical": - new_col = pd.Series(col_val, dtype="category") - data[col_name] = new_col - elif repr_meta and col_name in repr_meta: - new_col = pd.Series(col_val, dtype=repr_meta[col_name]) - data[col_name] = new_col - elif index_dims and col_name in index_dims: - new_col = pd.Series(col_val, dtype=index_dims[col_name]) - data[col_name] = new_col - indexes.append(col_name) - - new_df = pd.DataFrame.from_dict(data) - if len(indexes) > 0: - new_df.set_index(indexes, inplace=True) - - return new_df - - def write_labels(self, df, data_adaptor): - auth_user_id = self.get_user_id() - user_name = self.get_user_name() - timestamp = time.time() - dataset_location = data_adaptor.get_location() - dataset_id = self.db.get_or_create_dataset(dataset_location) - dataset_name = data_adaptor.get_title() - user_id = self.db.get_or_create_user(auth_user_id) - """ - NOTE: The uri contains the dataset name, user name and a timestamp as a convenience for debugging purposes. - People may have the same name and time.time() can be server dependent. - See - https://docs.python.org/2/library/time.html#time.time - - The annotations objects in the database should be used as the source of truth about who an annotation belongs - to (for authorization purposes) and what time it was created (for garbage collection). - """ - uri = f"{self.directory_path}{dataset_name}/{user_name}/{timestamp}" - if uri.startswith("s3://"): - pass - else: - os.makedirs(uri, exist_ok=True) - _, dataframe_schema_type_hints = get_dtypes_and_schemas_of_dataframe(df) - if not df.empty: - self.check_category_names(df) - # convert to tiledb datatypes - - for col in df: - df[col] = df[col].astype(get_encoding_dtype_of_array(df[col])) - tiledb.from_pandas(uri, df, sparse=True) - else: - uri = "" - - annotation = Annotation( - tiledb_uri=uri, - user_id=user_id, - dataset_id=str(dataset_id), - schema_hints=json.dumps(dataframe_schema_type_hints), - ) - self.db.session.add(annotation) - self.db.session.commit() - - def update_parameters(self, parameters, data_adaptor): - super().update_parameters(parameters, data_adaptor) - - params = {} - params["annotations"] = True - params["user_annotation_collection_name_enabled"] = False - - parameters.update(params) diff --git a/backend/czi_hosted/common/annotations/local_file_csv.py b/backend/czi_hosted/common/annotations/local_file_csv.py deleted file mode 100644 index 6a5d3a16..00000000 --- a/backend/czi_hosted/common/annotations/local_file_csv.py +++ /dev/null @@ -1,192 +0,0 @@ -import base64 -import os -import re -import threading -from datetime import datetime -from hashlib import blake2b - -import pandas as pd -from flask import session, has_request_context, current_app - -from backend.czi_hosted import __version__ as cellxgene_version -from backend.czi_hosted.common.annotations.annotations import Annotations -from backend.common.errors import AnnotationsError - - -class AnnotationsLocalFile(Annotations): - CXG_ANNO_COLLECTION = "cxg_anno_collection" - - def __init__(self, config, output_dir, output_file): - super().__init__(config) - self.output_dir = output_dir - self.output_file = output_file - # lock used to protect label file write ops - self.label_lock = threading.RLock() - - # cache the most recent annotations - self.last_fname = None - self.last_labels = None - - def is_safe_collection_name(self, name): - """ - return true if this is a safe collection name - this is ultra conservative. If we want to allow full legal file name syntax, - we could look at modules like `pathvalidate` - """ - if name is None: - return False - return re.match(r"^[\w\-]+$", name) is not None - - def set_collection(self, name): - session[self.CXG_ANNO_COLLECTION] = name - session.permanent = True - - def get_collection(self): - if session is None: - return None - return session.get(self.CXG_ANNO_COLLECTION) - - def read_labels(self, data_adaptor): - if has_request_context(): - if not current_app.auth.is_user_authenticated(): - return pd.DataFrame() - - fname = self._get_filename(data_adaptor) - with self.label_lock: - if fname is not None and os.path.exists(fname) and os.path.getsize(fname) > 0: - # returned the cached labels if possible, otherwise read them from the file - if fname == self.last_fname: - return self.last_labels - else: - labels = pd.read_csv( - fname, dtype="category", index_col=0, header=0, comment="#", keep_default_na=False - ) - # update the cache - self.last_fname = fname - self.last_labels = labels - return labels - else: - return pd.DataFrame() - - def write_labels(self, df, data_adaptor): - # update our internal state and save it. Multi-threading often enabled, - # so treat this as a critical section. - with self.label_lock: - lastmod = data_adaptor.get_last_mod_time() - lastmodstr = "'unknown'" if lastmod is None else lastmod.isoformat(timespec="seconds") - header = ( - f"# Annotations generated on {datetime.now().isoformat(timespec='seconds')} " - f"using cellxgene version {cellxgene_version}\n" - f"# Input data file was {data_adaptor.get_location()}, " - f"which was last modified on {lastmodstr}\n" - ) - - fname = self._get_filename(data_adaptor) - self._backup(fname) - if not df.empty: - with open(fname, "w", newline="") as f: - if header is not None: - f.write(header) - df.to_csv(f) - else: - open(fname, "w").close() - - # update the cache - self.last_fname = fname - self.last_labels = df - - def _get_userdata_idhash(self, data_adaptor): - """ - Return a short hash that weakly identifies the user and dataset. - Used to create safe annotations output file names. - """ - uid = current_app.auth.get_user_id() - id = (uid + data_adaptor.get_location()).encode() - idhash = base64.b32encode(blake2b(id, digest_size=5).digest()).decode("utf-8") - return idhash - - def _get_output_dir(self): - if self.output_dir: - return self.output_dir - - if self.output_file: - return os.path.dirname(self.path.abspath(self.output_dir)) - - return os.getcwd() - - def _get_filename(self, data_adaptor): - """return the current annotation file name""" - if self.output_file: - return self.output_file - - # we need to generate a file name, which we can only do if we have a UID and collection name - if session is None: - raise AnnotationsError("unable to determine file name for annotations") - - collection = self.get_collection() - if collection is None: - return None - - if data_adaptor is None: - raise AnnotationsError("unable to determine file name for annotations") - - idhash = self._get_userdata_idhash(data_adaptor) - return os.path.join(self._get_output_dir(), f"{collection}-{idhash}.csv") - - def _backup(self, fname, max_backups=9): - """ - save N backups of file to backup_dir. - 1. fname -> backup_dir/fname-TIME - 2. delete excess files in backup_dir - """ - root, ext = os.path.splitext(fname) - backup_dir = f"{root}-backups" - - # Make sure there is work to do - if not os.path.exists(fname): - return - - # Ensure backup_dir exists - if not os.path.exists(backup_dir): - os.mkdir(backup_dir) - - # Save current file to backup_dir - fname_base = os.path.basename(fname) - fname_base_root, fname_base_ext = os.path.splitext(fname_base) - # don't use ISO standard time format, as it contains characters illegal on some filesytems. - nowish = datetime.now().strftime("%Y-%m-%dT%H-%M-%S") - backup_fname = os.path.join(backup_dir, f"{fname_base_root}-{nowish}{fname_base_ext}") - if os.path.exists(backup_fname): - os.remove(backup_fname) - os.rename(fname, backup_fname) - - # prune the backup_dir to max number of backup files, keeping the most recent backups - backups = list(filter(lambda s: s.startswith(fname_base_root), os.listdir(backup_dir))) - excess_count = len(backups) - max_backups - if excess_count > 0: - backups.sort() - for bu in backups[0:excess_count]: - os.remove(os.path.join(backup_dir, bu)) - - def update_parameters(self, parameters, data_adaptor): - super().update_parameters(parameters, data_adaptor) - - params = {} - params["annotations"] = True - params["user_annotation_collection_name_enabled"] = True - - if self.output_file is not None: - # user has hard-wired the name of the annotation data collection - fname = os.path.basename(self.output_file) - collection_fname = os.path.splitext(fname)[0] - params["annotations-data-collection-is-read-only"] = True - params["annotations-data-collection-name"] = collection_fname - - elif session is not None: - collection = self.get_collection() - if current_app.auth.is_user_authenticated(): - params["annotations-user-data-idhash"] = self._get_userdata_idhash(data_adaptor) - params["annotations-data-collection-is-read-only"] = not self.user_annotations_enabled() - params["annotations-data-collection-name"] = collection - - parameters.update(params) diff --git a/backend/czi_hosted/common/config/__init__.py b/backend/czi_hosted/common/config/__init__.py deleted file mode 100644 index 8b12f32a..00000000 --- a/backend/czi_hosted/common/config/__init__.py +++ /dev/null @@ -1,4 +0,0 @@ -from backend.common.utils.aws_secret_utils import get_secret_key # noqa F504 - -DEFAULT_SERVER_PORT = 5005 -BIG_FILE_SIZE_THRESHOLD = 100 * 2 ** 20 # 100MB diff --git a/backend/czi_hosted/common/config/app_config.py b/backend/czi_hosted/common/config/app_config.py deleted file mode 100644 index 517491b2..00000000 --- a/backend/czi_hosted/common/config/app_config.py +++ /dev/null @@ -1,247 +0,0 @@ -import yaml -from flatten_dict import unflatten - -from backend.czi_hosted.common.config.external_config import ExternalConfig -from backend.czi_hosted.common.config.dataset_config import DatasetConfig -from backend.czi_hosted.common.config.server_config import ServerConfig -from backend.common.errors import ConfigurationError -from backend.czi_hosted.default_config import get_default_config - - -class AppConfig(object): - """ - AppConfig stores all the configuration for cellxgene. - AppConfig contains one or more DatasetConfig(s) and one ServerConfig. - The server_config contains attributes that refer to the server process as a whole. - The default_dataset_config refers to attributes that are associated with the features and - presentations of a dataset. - The dataset config attributes can be overridden depending on the url by which the - dataset was accessed. These are stored in dataroot_config. - AppConfig has methods to initialize, modify, and access the configuration. - """ - - def __init__(self): - - # the default configuration (see default_config.py) - # TODO @madison -- if we always read from the default config (hard coded path) can we set those values as - # defaults within the config class? - self.default_config = get_default_config() - # the server configuration - self.server_config = ServerConfig(self, self.default_config["server"]) - # the dataset config, unless overridden by an entry in dataroot_config - self.default_dataset_config = DatasetConfig(None, self, self.default_config["dataset"]) - # a dictionary of keys to DatasetConfig objects. Each key must exist in the multi_dataset__dataroot - # attribute of the server_config. The default dataset config will apply to all datasets unless a different set - # of config vars was passed for a specific dataset under the multidataset config. For example: - """ - per_dataset_config: - d1: - user_annotations: - enable: false - d2: - user_annotations: - enable: true - """ - # dataroot config - self.dataroot_config = {} - - # external config - self.external_config = ExternalConfig(self, self.default_config["external"]) - - # Set to true when config_completed is called - self.is_completed = False - - def get_dataset_config(self, dataroot_key): - if self.server_config.single_dataset__datapath: - return self.default_dataset_config - else: - return self.dataroot_config.get(dataroot_key, self.default_dataset_config) - - def check_config(self): - """Verify all the attributes in the config have been type checked""" - if not self.is_completed: - raise ConfigurationError("The configuration has not been completed") - self.server_config.check_config() - self.default_dataset_config.check_config() - for dataset_config in self.dataroot_config.values(): - dataset_config.check_config() - self.external_config.check_config() - - def update_server_config(self, **kw): - self.server_config.update(**kw) - self.is_completed = False - - def update_default_dataset_config(self, **kw): - self.default_dataset_config.update(**kw) - # update all the other dataset configs, if any - for value in self.dataroot_config.values(): - value.update(**kw) - self.is_completed = False - - def update_single_config_from_path_and_value(self, path, value): - """Update a single config parameter with the value. - Path is a list of string, that gives a path to the config parameter to be updated. - For example, path may be ["server","app","port"]. - """ - self.is_completed = False - if not isinstance(path, list): - raise ConfigurationError(f"path must be a list of strings, got '{str(path)}'") - for part in path: - if not isinstance(part, str): - raise ConfigurationError(f"path must be a list of strings, got '{str(path)}'") - - if len(path) < 1 or path[0] not in ("server", "dataset", "per_dataset_config"): - raise ConfigurationError("path must start with 'server', 'dataset', or 'per_dataset_config'") - - if path[0] == "server": - attr = "__".join(path[1:]) - try: - self.update_server_config(**{attr: value}) - except ConfigurationError: - raise ConfigurationError(f"unknown config parameter at path: '{str(path)}'") - elif path[0] == "dataset": - attr = "__".join(path[1:]) - try: - self.update_default_dataset_config(**{attr: value}) - except ConfigurationError: - raise ConfigurationError(f"unknown config parameter at path: '{str(path)}'") - - elif path[0] == "per_dataset_config": - if len(path) < 2: - raise ConfigurationError(f"missing dataroot when using per_dataset_config: got '{path}'") - dataroot = path[1] - if dataroot not in self.dataroot_config: - dataroots = str(list(self.dataroot_config.keys())) - raise ConfigurationError( - f"unknown dataroot when using per_dataset_config: got '{path}'," - f" dataroots specified in config are {dataroots}" - ) - - attr = "__".join(path[2:]) - try: - self.dataroot_config[dataroot].update(**{attr: value}) - except ConfigurationError: - raise ConfigurationError(f"unknown config parameter at path: '{str(path)}'") - - def update_from_config_file(self, config_file): - try: - with open(config_file) as yml_file: - config = yaml.safe_load(yml_file) - except yaml.YAMLError as e: - raise ConfigurationError(f"The specified config file contained an error: {e}") - except OSError as e: - raise ConfigurationError(f"Issue retrieving the specified config file: {e}") - - if config.get("server"): - self.server_config.update_from_config(config["server"], "server") - if config.get("dataset"): - self.default_dataset_config.update_from_config(config["dataset"], "dataset") - - per_dataset_config = config.get("per_dataset_config", {}) - for key, dataroot_config in per_dataset_config.items(): - # first create and initialize the dataroot with the default config - self.add_dataroot_config(key, **config["dataset"]) - # then apply the per dataset configuration - self.dataroot_config[key].update_from_config(dataroot_config, f"per_dataset_config__{key}") - - if config.get("external"): - self.external_config.update_from_config(config["external"], "external") - - self.is_completed = False - - def config_to_dict(self): - """return the configuration as an unflattened dict""" - server = self.server_config.create_mapping(self.server_config.default_config) - dataset = self.default_dataset_config.create_mapping(self.default_dataset_config.default_config) - external = self.external_config.create_mapping(self.external_config.default_config) - config = dict(server={}, dataset={}) - for attrname in server.keys(): - config["server__" + attrname] = getattr(self.server_config, attrname) - for attrname in dataset.keys(): - config["dataset__" + attrname] = getattr(self.default_dataset_config, attrname) - if self.dataroot_config: - config["per_dataset_config"] = {} - for dataroot_tag, dataroot_config in self.dataroot_config.items(): - dataset = dataroot_config.create_mapping(dataroot_config.default_config) - for attrname in dataset.keys(): - config[f"per_dataset_config__{dataroot_tag}__" + attrname] = getattr(dataroot_config, attrname) - for attrname in external.keys(): - config["external__" + attrname] = getattr(self.external_config, attrname) - - config = unflatten(config, splitter=lambda key: key.split("__")) - return config - - def write_config(self, config_file): - """output the config to a yaml file""" - config = self.config_to_dict() - yaml.dump(config, open(config_file, "w")) - - def changes_from_default(self): - """Return all the attribute that are different from the default""" - diff_server = self.server_config.changes_from_default() - diff_dataset = self.default_dataset_config.changes_from_default() - diff_external = self.external.changes_from_default() - diff = dict(server=diff_server, dataset=diff_dataset, external=diff_external) - return diff - - def add_dataroot_config(self, dataroot_tag, **kw): - """Create a new dataset config object based on the default dataset config, and kw parameters""" - if dataroot_tag in self.dataroot_config: - raise ConfigurationError(f"dataroot config already exists: {dataroot_tag}") - if type(self.server_config.multi_dataset__dataroot) != dict: - raise ConfigurationError("The server__multi_dataset__dataroot must be a dictionary") - if dataroot_tag not in self.server_config.multi_dataset__dataroot: - raise ConfigurationError(f"The dataroot_tag ({dataroot_tag}) not found in server__multi_dataset__dataroot") - - self.is_completed = False - self.dataroot_config[dataroot_tag] = DatasetConfig(dataroot_tag, self, self.default_config["dataset"]) - flat_config = self.default_dataset_config.create_mapping(self.default_dataset_config.default_config) - config = {key: value[1] for key, value in flat_config.items()} - self.dataroot_config[dataroot_tag].update(**config) - self.dataroot_config[dataroot_tag].update_from_config(kw, dataroot_tag) - - def complete_config(self, messagefn=None): - """The configure options are checked, and any additional setup based on the config - parameters is done""" - - if messagefn is None: - - def noop(message): - pass - - messagefn = noop - - # TODO: to give better error messages we can add a mapping between where each config - # attribute originated (e.g. command line argument or config file), then in the error - # messages we can give correct context for attributes with bad value. - context = dict(messagefn=messagefn) - - # complete config for external_config first, since this may update values in the other sections - self.external_config.complete_config(context) - self.server_config.complete_config(context) - self.default_dataset_config.complete_config(context) - for dataroot_config in self.dataroot_config.values(): - dataroot_config.complete_config(context) - - self.is_completed = True - self.check_config() - - def get_matrix_data_cache_manager(self): - return self.server_config.matrix_data_cache_manager - - def is_multi_dataset(self): - return self.server_config.multi_dataset__dataroot is not None - - def get_title(self, data_adaptor): - return ( - self.server_config.single_dataset__title - if self.server_config.single_dataset__title - else data_adaptor.get_title() - ) - - def get_about(self, data_adaptor): - return ( - self.server_config.single_dataset__about - if self.server_config.single_dataset__about - else data_adaptor.get_about() - ) diff --git a/backend/czi_hosted/common/config/base_config.py b/backend/czi_hosted/common/config/base_config.py deleted file mode 100644 index 7c4f98bf..00000000 --- a/backend/czi_hosted/common/config/base_config.py +++ /dev/null @@ -1,132 +0,0 @@ -import copy - -from flatten_dict import flatten -from backend.common.errors import ConfigurationError - - -class BaseConfig(object): - """ - This class handles the mechanics of updating and checking attributes. - Derived classes are expected to store the actual attributes - Currently DatasetConfig and ServerConfig both inherit from BaseConfig. - """ - - def __init__(self, app_config, default_config, dictval_cases={}): - # reference back to the app_config - self.app_config = app_config - # the complete set of attributes and their default values (unflattened) - self.default_config = default_config - # attributes where the value may be a dict (and therefore are not flattened) - self.dictval_cases = dictval_cases - # used to make sure every attribute value is checked - self.attr_checked = {key_name: False for key_name in self.create_mapping(default_config).keys()} - - def create_mapping(self, config): - """ - Create a dictionary where the keys are the name of attributes (using double underscore convention) - For example: authentication__type - - The values are a tuple, - - the first item of the tuple is a tuple of path elements (location in config 'tree') - - the second item is the value of the config parameter - - For example: (('authentication', 'type'), 'session')) - """ - config_copy = copy.deepcopy(config) - mapping = {} - - # special cases where the value could be a dict. - # If its value is not None, the entry is added to the mapping, and not included - # in the flattening below. - for dictval_case in self.dictval_cases: - cur = config_copy - for part in dictval_case[:-1]: - cur = cur.get(part, {}) - val = cur.get(dictval_case[-1]) - if val is not None: - key = "__".join(dictval_case) - mapping[key] = (dictval_case, val) - del cur[dictval_case[-1]] - - flat_config = flatten(config_copy) - for key, value in flat_config.items(): - # name of the attribute - attr = "__".join(key) - mapping[attr] = (key, value) - - return mapping - - def validate_correct_type_of_configuration_attribute(self, attrname, vtype): - val = getattr(self, attrname) - if type(vtype) in (list, tuple): - if type(val) not in vtype: - tnames = ",".join([x.__name__ for x in vtype]) - raise ConfigurationError( - f"Invalid type for attribute: {attrname}, expected types ({tnames}), got {type(val).__name__}" - ) - else: - if type(val) != vtype: - raise ConfigurationError( - f"Invalid type for attribute: {attrname}, " - f"expected type {vtype.__name__}, got {type(val).__name__}" - ) - - self.attr_checked[attrname] = True - - def check_config(self): - mapping = self.create_mapping(self.default_config) - for key in mapping.keys(): - if not self.attr_checked[key]: - raise ConfigurationError(f"The attr '{key}' has not been checked") - - def update(self, **kw): - """Update the attributes defined in kw with their new values.""" - for key, value in kw.items(): - if not hasattr(self, key): - - # check if the key is setting into a dictval entry. - found_dictval = False - for dictval in self.dictval_cases: - dictvalname = "__".join(dictval) - if dictvalname + "__" in key: - dictkey = key[len(dictvalname) + 2 :] - curdictval = getattr(self, dictvalname) - if curdictval is None: - setattr(self, dictvalname, dict(dictkey=value)) - else: - curdictval[dictkey] = value - - found_dictval = True - break - - if found_dictval: - continue - raise ConfigurationError(f"unknown config parameter {key}.") - try: - if type(value) == tuple: - # convert tuple values to list values - value = list(value) - setattr(self, key, value) - except KeyError: - raise ConfigurationError(f"Unable to set config parameter {key}.") - - self.attr_checked[key] = False - - def update_from_config(self, config, prefix): - mapping = self.create_mapping(config) - for attr, (key, value) in mapping.items(): - if not hasattr(self, attr): - raise ConfigurationError(f"Unknown key from config file: {prefix}__{attr}") - setattr(self, attr, value) - - self.attr_checked[attr] = False - - def changes_from_default(self): - """Return all the attribute that are different from the default""" - mapping = self.create_mapping(self.default_config) - diff = [] - for attrname, (key, defval) in mapping.items(): - curval = getattr(self, attrname) - if curval != defval: - diff.append((attrname, curval, defval)) - return diff diff --git a/backend/czi_hosted/common/config/client_config.py b/backend/czi_hosted/common/config/client_config.py deleted file mode 100644 index c4aa5fb8..00000000 --- a/backend/czi_hosted/common/config/client_config.py +++ /dev/null @@ -1,121 +0,0 @@ -from backend.czi_hosted import display_version as cellxgene_display_version - - -def get_client_config(app_config, data_adaptor): - """ - Return the configuration as required by the /config REST route - """ - - server_config = app_config.server_config - dataset_config = data_adaptor.dataset_config - annotation = dataset_config.user_annotations - auth = server_config.auth - - # FIXME The current set of config is not consistently presented: - # we have camalCase, hyphen-text, and underscore_text - - # make sure the configuration has been checked. - app_config.check_config() - - # display_names - title = app_config.get_title(data_adaptor) - about = app_config.get_about(data_adaptor) - - display_names = dict(engine=data_adaptor.get_name(), dataset=title) - - # library_versions - library_versions = {} - library_versions.update(data_adaptor.get_library_versions()) - library_versions["cellxgene"] = cellxgene_display_version - - # links - links = {"about-dataset": about} - - # parameters - parameters = { - "layout": dataset_config.embeddings__names, - "max-category-items": dataset_config.presentation__max_categories, - "obs_names": server_config.single_dataset__obs_names, - "var_names": server_config.single_dataset__var_names, - "diffexp_lfc_cutoff": dataset_config.diffexp__lfc_cutoff, - "backed": server_config.adaptor__anndata_adaptor__backed, - "disable-diffexp": not dataset_config.diffexp__enable, - "annotations": False, - "annotations_file": None, - "annotations_dir": None, - "annotations_genesets": True, # feature flag - "annotations_genesets_readonly": True, - "annotations_genesets_summary_methods": ["mean"], - "custom_colors": dataset_config.presentation__custom_colors, - "diffexp-may-be-slow": False, - "about_legal_tos": dataset_config.app__about_legal_tos, - "about_legal_privacy": dataset_config.app__about_legal_privacy, - } - - # corpora dataset_props - # TODO/Note: putting info from the dataset into the /config is not ideal. - # However, it is definitely not part of /schema, and we do not have a top-level - # route for data properties. Consider creating one at some point. - corpora_props = data_adaptor.get_corpora_props() - if corpora_props and "default_embedding" in corpora_props: - default_embedding = corpora_props["default_embedding"] - if isinstance(default_embedding, str) and default_embedding.startswith("X_"): - default_embedding = default_embedding[2:] # drop X_ prefix - if default_embedding in data_adaptor.get_embedding_names(): - parameters["default_embedding"] = default_embedding - - data_adaptor.update_parameters(parameters) - if annotation: - annotation.update_parameters(parameters, data_adaptor) - - # gather it all together - client_config = {} - config = client_config["config"] = {} - config["displayNames"] = display_names - config["library_versions"] = library_versions - config["links"] = links - config["parameters"] = parameters - config["corpora_props"] = corpora_props - config["limits"] = { - "column_request_max": server_config.limits__column_request_max, - "diffexp_cellcount_max": server_config.limits__diffexp_cellcount_max, - } - - if dataset_config.app__authentication_enable and auth.is_valid_authentication_type(): - config["authentication"] = { - "requires_client_login": auth.requires_client_login(), - } - if auth.requires_client_login(): - config["authentication"].update( - { - # Todo why are these stored on the data_adaptor? - "login": auth.get_login_url(data_adaptor), - "logout": auth.get_logout_url(data_adaptor), - } - ) - - return client_config - - -def get_client_userinfo(app_config, data_adaptor): - """ - Return the userinfo as required by the /userinfo REST route - """ - - server_config = app_config.server_config - dataset_config = data_adaptor.dataset_config - auth = server_config.auth - - # make sure the configuration has been checked. - app_config.check_config() - - if dataset_config.app__authentication_enable and auth.is_valid_authentication_type(): - userinfo = {} - userinfo["userinfo"] = { - "is_authenticated": auth.is_user_authenticated(), - "username": auth.get_user_name(), - "user_id": auth.get_user_id(), - "email": auth.get_user_email(), - "picture": auth.get_user_picture(), - } - return userinfo diff --git a/backend/czi_hosted/common/config/dataset_config.py b/backend/czi_hosted/common/config/dataset_config.py deleted file mode 100644 index 50d96787..00000000 --- a/backend/czi_hosted/common/config/dataset_config.py +++ /dev/null @@ -1,211 +0,0 @@ -import os -from os.path import splitext, isdir - -from backend.czi_hosted.common.annotations.annotations import Annotations -from backend.czi_hosted.common.annotations.hosted_tiledb import AnnotationsHostedTileDB -from backend.czi_hosted.common.annotations.local_file_csv import AnnotationsLocalFile -from backend.czi_hosted.common.config.base_config import BaseConfig -from backend.common.errors import ConfigurationError -from backend.czi_hosted.db.db_utils import DbUtils - - -class DatasetConfig(BaseConfig): - """Manages the config attribute associated with a dataset.""" - - def __init__(self, tag, app_config, default_config): - super().__init__(app_config, default_config) - self.tag = tag - try: - self.app__scripts = default_config["app"]["scripts"] - self.app__inline_scripts = default_config["app"]["inline_scripts"] - self.app__about_legal_tos = default_config["app"]["about_legal_tos"] - self.app__about_legal_privacy = default_config["app"]["about_legal_privacy"] - self.app__authentication_enable = default_config["app"]["authentication_enable"] - - self.presentation__max_categories = default_config["presentation"]["max_categories"] - self.presentation__custom_colors = default_config["presentation"]["custom_colors"] - - self.user_annotations__enable = default_config["user_annotations"]["enable"] - self.user_annotations__type = default_config["user_annotations"]["type"] - self.user_annotations__local_file_csv__directory = default_config["user_annotations"]["local_file_csv"][ - "directory" - ] - self.user_annotations__local_file_csv__file = default_config["user_annotations"]["local_file_csv"]["file"] - self.user_annotations__hosted_tiledb_array__db_uri = default_config["user_annotations"][ - "hosted_tiledb_array" - ]["db_uri"] - self.user_annotations__hosted_tiledb_array__hosted_file_directory = default_config["user_annotations"][ - "hosted_tiledb_array" - ]["hosted_file_directory"] - - self.embeddings__names = default_config["embeddings"]["names"] - - self.diffexp__enable = default_config["diffexp"]["enable"] - self.diffexp__lfc_cutoff = default_config["diffexp"]["lfc_cutoff"] - self.diffexp__top_n = default_config["diffexp"]["top_n"] - - self.X_approximate_distribution = default_config["X_approximate_distribution"] - - except KeyError as e: - raise ConfigurationError(f"Unexpected config: {str(e)}") - - # Create the default annotation, which supports gene set reading without - # further configuration. Depending on configuration options, `complete_config` - # may create a more specialized annotation object and replace this default. - self.user_annotations = Annotations() - - def complete_config(self, context): - self.handle_app() - self.handle_presentation() - self.handle_user_annotations(context) - self.handle_embeddings() - self.handle_diffexp(context) - self.handle_X_approximate_distribution() - - def handle_app(self): - self.validate_correct_type_of_configuration_attribute("app__scripts", list) - self.validate_correct_type_of_configuration_attribute("app__inline_scripts", list) - self.validate_correct_type_of_configuration_attribute("app__about_legal_tos", (type(None), str)) - self.validate_correct_type_of_configuration_attribute("app__about_legal_privacy", (type(None), str)) - self.validate_correct_type_of_configuration_attribute("app__authentication_enable", bool) - - # scripts can be string (filename) or dict (attributes). Convert string to dict. - scripts = [] - for script in self.app__scripts: - try: - if isinstance(script, str): - scripts.append({"src": script}) - elif isinstance(script, dict) and isinstance(script["src"], str): - scripts.append(script) - else: - raise Exception - except Exception as e: - raise ConfigurationError(f"Scripts must be string or a dict containing an src key: {e}") - - self.app__scripts = scripts - - def handle_presentation(self): - self.validate_correct_type_of_configuration_attribute("presentation__max_categories", int) - self.validate_correct_type_of_configuration_attribute("presentation__custom_colors", bool) - - def handle_user_annotations(self, context): - self.validate_correct_type_of_configuration_attribute("user_annotations__enable", bool) - self.validate_correct_type_of_configuration_attribute("user_annotations__type", str) - self.validate_correct_type_of_configuration_attribute( - "user_annotations__local_file_csv__directory", (type(None), str) - ) - self.validate_correct_type_of_configuration_attribute( - "user_annotations__local_file_csv__file", (type(None), str) - ) - self.validate_correct_type_of_configuration_attribute( - "user_annotations__hosted_tiledb_array__db_uri", (type(None), str) - ) - self.validate_correct_type_of_configuration_attribute( - "user_annotations__hosted_tiledb_array__hosted_file_directory", (type(None), str) - ) - if self.user_annotations__enable: - server_config = self.app_config.server_config - if not self.app__authentication_enable: - raise ConfigurationError("user annotations requires authentication to be enabled") - if not server_config.auth.is_valid_authentication_type(): - auth_type = server_config.authentication__type - raise ConfigurationError(f"authentication method {auth_type} is not compatible with user annotations") - - if self.user_annotations__type == "local_file_csv": - self.handle_local_file_csv_annotations() - elif self.user_annotations__type == "hosted_tiledb_array": - self.handle_hosted_tiledb_annotations() - else: - raise ConfigurationError('The only annotation type support is "local_file_csv" or "hosted_tiledb_array') - else: - self.check_annotation_config_vars_not_set(context) - - def handle_local_file_csv_annotations(self): - dirname = self.user_annotations__local_file_csv__directory - filename = self.user_annotations__local_file_csv__file - if filename is not None and dirname is not None: - raise ConfigurationError("'annotations-file' and 'annotations-dir' may not be used together.") - - if filename is not None: - lf_name, lf_ext = splitext(filename) - if lf_ext and lf_ext != ".csv": - raise ConfigurationError(f"annotation file type must be .csv: {filename}") - - if dirname is not None and not isdir(dirname): - try: - os.mkdir(dirname) - except OSError: - raise ConfigurationError("Unable to create directory specified by --annotations-dir") - - anno_config = { - "user-annotations": self.user_annotations__enable, - "genesets-save": False, - } - self.user_annotations = AnnotationsLocalFile(anno_config, dirname, filename) - - # if the user has specified a fixed label file, go ahead and validate it - # so that we can remove errors early in the process. - server_config = self.app_config.server_config - if server_config.single_dataset__datapath and self.user_annotations__local_file_csv__file: - with server_config.matrix_data_cache_manager.data_adaptor( - self.tag, server_config.single_dataset__datapath, self.app_config - ) as data_adaptor: - data_adaptor.check_new_labels(self.user_annotations.read_labels(data_adaptor)) - - def handle_hosted_tiledb_annotations(self): - self.validate_correct_type_of_configuration_attribute("user_annotations__hosted_tiledb_array__db_uri", str) - self.validate_correct_type_of_configuration_attribute( - "user_annotations__hosted_tiledb_array__hosted_file_directory", str - ) - anno_config = { - "user-annotations": self.user_annotations__enable, - "genesets-save": False, - } - self.user_annotations = AnnotationsHostedTileDB( - anno_config, - directory_path=self.user_annotations__hosted_tiledb_array__hosted_file_directory, - db=DbUtils(self.user_annotations__hosted_tiledb_array__db_uri), - ) - - def check_annotation_config_vars_not_set(self, context): - if self.user_annotations__type is not None: - dirname = self.user_annotations__local_file_csv__directory - filename = self.user_annotations__local_file_csv__file - db_uri = self.user_annotations__hosted_tiledb_array__db_uri - hosted_file_dirname = self.user_annotations__hosted_tiledb_array__hosted_file_directory - if filename is not None: - context["messagefn"]("Warning: --annotations-file ignored as annotations are disabled.") - if dirname is not None: - context["messagefn"]("Warning: --annotations-dir ignored as annotations are disabled.") - if db_uri is not None: - context["messagefn"]("Warning: db_uri ignored as annotations are disabled.") - if hosted_file_dirname is not None: - context["messagefn"]( - "Warning: hosted_file_directory for hosted_tiledb_array ignored as annotations are disabled." - ) - - def handle_embeddings(self): - self.validate_correct_type_of_configuration_attribute("embeddings__names", list) - - def handle_diffexp(self, context): - self.validate_correct_type_of_configuration_attribute("diffexp__enable", bool) - self.validate_correct_type_of_configuration_attribute("diffexp__lfc_cutoff", float) - self.validate_correct_type_of_configuration_attribute("diffexp__top_n", int) - - server_config = self.app_config.server_config - if server_config.single_dataset__datapath: - with server_config.matrix_data_cache_manager.data_adaptor( - self.tag, server_config.single_dataset__datapath, self.app_config - ) as data_adaptor: - if self.diffexp__enable and data_adaptor.parameters.get("diffexp_may_be_slow", False): - context["messagefn"]( - "CAUTION: due to the size of your dataset, " - "running differential expression may take longer or fail." - ) - - def handle_X_approximate_distribution(self): - self.validate_correct_type_of_configuration_attribute("X_approximate_distribution", str) - if self.X_approximate_distribution not in ["normal", "count"]: - raise ConfigurationError( - "X_approximate_distribution has unknown value -- must be 'normal' or 'count'." - ) diff --git a/backend/czi_hosted/common/config/external_config.py b/backend/czi_hosted/common/config/external_config.py deleted file mode 100644 index 915486e1..00000000 --- a/backend/czi_hosted/common/config/external_config.py +++ /dev/null @@ -1,95 +0,0 @@ -import os - -from backend.czi_hosted.common.config.base_config import BaseConfig -from backend.common.errors import ConfigurationError, SecretKeyRetrievalError -from backend.common.utils.aws_secret_utils import get_secret_key -from backend.common.utils.type_conversion_utils import convert_string_to_value - - -class ExternalConfig(BaseConfig): - """Manages the config attribute associated with external configuration sources, such as - environment variables or the AWS Secrets Manager.""" - - def __init__(self, app_config, default_config): - super().__init__(app_config, default_config) - try: - self.environment = default_config["environment"] - self.aws_secrets_manager__region = default_config["aws_secrets_manager"]["region"] - self.aws_secrets_manager__secrets = default_config["aws_secrets_manager"]["secrets"] - - except KeyError as e: - raise ConfigurationError(f"Unexpected config: {str(e)}") - - def complete_config(self, context): - self.handle_environment(context) - self.handle_aws_secrets_manager(context) - - def handle_environment(self, context): - """For each environment variable defined, get the value (if it is set), - and set the specified config parameter""" - self.validate_correct_type_of_configuration_attribute("environment", list) - for envdict in self.environment: - name = envdict.get("name") - if name is None: - raise ConfigurationError("environment: 'name' is missing") - required = envdict.get("required", False) - if type(required) != bool: - raise ConfigurationError("environment: 'required' must be a bool") - path = envdict.get("path") - if path is None: - raise ConfigurationError("environment: 'path' is missing") - - value = os.environ.get(name) - if value is None: - if required: - raise ConfigurationError(f"required environment variable '{name}' not set") - else: - value = convert_string_to_value(value) - self.app_config.update_single_config_from_path_and_value(path, value) - - def handle_aws_secrets_manager(self, context): - """For each aws secret defined, get the key/values, and set the specified config parameter""" - self.validate_correct_type_of_configuration_attribute("aws_secrets_manager__region", (type(None), str)) - self.validate_correct_type_of_configuration_attribute("aws_secrets_manager__secrets", list) - - if not self.aws_secrets_manager__secrets: - return - - self.validate_correct_type_of_configuration_attribute("aws_secrets_manager__region", str) - - for secret in self.aws_secrets_manager__secrets: - secret_name = secret.get("name") - if secret_name is None: - raise ConfigurationError("aws_secrets_manager: 'name' is missing") - if not isinstance(secret_name, str): - raise ConfigurationError("aws_secrets_manager: 'name' must be a string") - - try: - secret_dict = get_secret_key(self.aws_secrets_manager__region, secret_name) - except SecretKeyRetrievalError as e: - raise ConfigurationError(f"Unable to retrieve secret {secret_name}: {str(e)}") - - values = secret.get("values") - if values is None: - raise ConfigurationError("aws_secrets_manager: 'values' is missing") - if not isinstance(values, list): - raise ConfigurationError("aws_secrets_manager: 'values' must be a list") - - for value in values: - key = value.get("key") - if key is None: - raise ConfigurationError(f"missing 'key' in secret values: {secret_name}") - path = value.get("path") - if path is None: - raise ConfigurationError(f"missing 'path' in secret values: {secret_name}") - required = value.get("required", False) - if type(required) != bool: - raise ConfigurationError(f"wrong type for 'required' in secret values: {secret_name}") - - secret_value = secret_dict.get(key) - if secret_value is None: - if required: - raise ConfigurationError(f"required secret '{secret_name}:{key}' not set") - else: - secret_value = convert_string_to_value(secret_value) - self.app_config.update_single_config_from_path_and_value(path, secret_value) diff --git a/backend/czi_hosted/common/config/server_config.py b/backend/czi_hosted/common/config/server_config.py deleted file mode 100644 index afc76b44..00000000 --- a/backend/czi_hosted/common/config/server_config.py +++ /dev/null @@ -1,387 +0,0 @@ -import os -import sys -import warnings -from os.path import basename -from urllib.parse import urlparse, quote_plus - -from backend.czi_hosted.auth.auth import AuthTypeFactory -from backend.czi_hosted.common.config import DEFAULT_SERVER_PORT, BIG_FILE_SIZE_THRESHOLD -from backend.czi_hosted.common.config.base_config import BaseConfig -from backend.common.utils.data_locator import discover_s3_region_name -from backend.common.errors import ConfigurationError, DatasetAccessError -from backend.common.utils.utils import is_port_available, find_available_port, custom_format_warning -from backend.czi_hosted.compute import diffexp_cxg as diffexp_tiledb -from backend.czi_hosted.data_common.matrix_loader import MatrixDataCacheManager, MatrixDataLoader, MatrixDataType - - -class ServerConfig(BaseConfig): - """Manages the config attribute associated with the server.""" - - def __init__(self, app_config, default_config): - dictval_cases = [ - ("app", "csp_directives"), - ("authentication", "params_oauth", "cookie"), - ("authentication", "params_oauth", "jwt_decode_options"), - ("adaptor", "cxg_adaptor", "tiledb_ctx"), - ("multi_dataset", "dataroot"), - ] - super().__init__(app_config, default_config, dictval_cases) - - try: - self.app__verbose = default_config["app"]["verbose"] - self.app__debug = default_config["app"]["debug"] - self.app__host = default_config["app"]["host"] - self.app__port = default_config["app"]["port"] - self.app__open_browser = default_config["app"]["open_browser"] - self.app__force_https = default_config["app"]["force_https"] - self.app__flask_secret_key = default_config["app"]["flask_secret_key"] - self.app__generate_cache_control_headers = default_config["app"]["generate_cache_control_headers"] - self.app__server_timing_headers = default_config["app"]["server_timing_headers"] - self.app__csp_directives = default_config["app"]["csp_directives"] - self.app__api_base_url = default_config["app"]["api_base_url"] - self.app__web_base_url = default_config["app"]["web_base_url"] - - self.authentication__type = default_config["authentication"]["type"] - self.authentication__insecure_test_environment = default_config["authentication"][ - "insecure_test_environment" - ] - self.authentication__params_oauth__oauth_api_base_url = default_config["authentication"]["params_oauth"][ - "oauth_api_base_url" - ] - self.authentication__params_oauth__client_id = default_config["authentication"]["params_oauth"]["client_id"] - self.authentication__params_oauth__client_secret = default_config["authentication"]["params_oauth"][ - "client_secret" - ] - self.authentication__params_oauth__jwt_decode_options = default_config["authentication"]["params_oauth"][ - "jwt_decode_options" - ] - self.authentication__params_oauth__session_cookie = default_config["authentication"]["params_oauth"][ - "session_cookie" - ] - self.authentication__params_oauth__cookie = default_config["authentication"]["params_oauth"]["cookie"] - - self.multi_dataset__dataroot = default_config["multi_dataset"]["dataroot"] - self.multi_dataset__index = default_config["multi_dataset"]["index"] - self.multi_dataset__allowed_matrix_types = default_config["multi_dataset"]["allowed_matrix_types"] - self.multi_dataset__matrix_cache__max_datasets = default_config["multi_dataset"]["matrix_cache"][ - "max_datasets" - ] - self.multi_dataset__matrix_cache__timelimit_s = default_config["multi_dataset"]["matrix_cache"][ - "timelimit_s" - ] - - self.single_dataset__datapath = default_config["single_dataset"]["datapath"] - self.single_dataset__obs_names = default_config["single_dataset"]["obs_names"] - self.single_dataset__var_names = default_config["single_dataset"]["var_names"] - self.single_dataset__about = default_config["single_dataset"]["about"] - self.single_dataset__title = default_config["single_dataset"]["title"] - - self.diffexp__alg_cxg__max_workers = default_config["diffexp"]["alg_cxg"]["max_workers"] - self.diffexp__alg_cxg__cpu_multiplier = default_config["diffexp"]["alg_cxg"]["cpu_multiplier"] - self.diffexp__alg_cxg__target_workunit = default_config["diffexp"]["alg_cxg"]["target_workunit"] - - self.data_locator__s3__region_name = default_config["data_locator"]["s3"]["region_name"] - - self.adaptor__cxg_adaptor__tiledb_ctx = default_config["adaptor"]["cxg_adaptor"]["tiledb_ctx"] - self.adaptor__anndata_adaptor__backed = default_config["adaptor"]["anndata_adaptor"]["backed"] - - self.limits__diffexp_cellcount_max = default_config["limits"]["diffexp_cellcount_max"] - self.limits__column_request_max = default_config["limits"]["column_request_max"] - - except KeyError as e: - raise ConfigurationError(f"Unexpected config: {str(e)}") - - # The matrix data cache manager is created during the complete_config and stored here. - self.matrix_data_cache_manager = None - - # The authentication object - self.auth = None - - def complete_config(self, context): - self.handle_app(context) - self.handle_data_source() - self.handle_authentication() - self.handle_data_locator() - self.handle_adaptor() # may depend on data_locator - self.handle_single_dataset(context) # may depend on adaptor - self.handle_multi_dataset() # may depend on adaptor - self.handle_diffexp() - self.handle_limits() - - self.check_config() - - def handle_app(self, context): - self.validate_correct_type_of_configuration_attribute("app__verbose", bool) - self.validate_correct_type_of_configuration_attribute("app__debug", bool) - self.validate_correct_type_of_configuration_attribute("app__host", str) - self.validate_correct_type_of_configuration_attribute("app__port", (type(None), int)) - self.validate_correct_type_of_configuration_attribute("app__open_browser", bool) - self.validate_correct_type_of_configuration_attribute("app__force_https", bool) - self.validate_correct_type_of_configuration_attribute("app__flask_secret_key", str) - self.validate_correct_type_of_configuration_attribute("app__generate_cache_control_headers", bool) - self.validate_correct_type_of_configuration_attribute("app__server_timing_headers", bool) - self.validate_correct_type_of_configuration_attribute("app__csp_directives", (type(None), dict)) - self.validate_correct_type_of_configuration_attribute("app__api_base_url", (type(None), str)) - self.validate_correct_type_of_configuration_attribute("app__web_base_url", (type(None), str)) - - if self.app__port: - try: - if not is_port_available(self.app__host, self.app__port): - raise ConfigurationError( - f"The port selected {self.app__port} is in use, please configure an open port." - ) - except OverflowError: - raise ConfigurationError(f"Invalid port: {self.app__port}") - else: - try: - default_server_port = int(os.environ.get("CXG_SERVER_PORT", DEFAULT_SERVER_PORT)) - except ValueError: - raise ConfigurationError( - "Invalid port from environment variable CXG_SERVER_PORT: " + os.environ.get("CXG_SERVER_PORT") - ) - try: - self.app__port = find_available_port(self.app__host, default_server_port) - except OverflowError: - raise ConfigurationError(f"Invalid port: {default_server_port}") - - if self.app__debug: - context["messagefn"]("in debug mode, setting verbose=True and open_browser=False") - self.app__verbose = True - self.app__open_browser = False - else: - warnings.formatwarning = custom_format_warning - - if not self.app__verbose: - sys.tracebacklimit = 0 - - # CSP Directives are a dict of string: list(string) or string: string - if self.app__csp_directives is not None: - for k, v in self.app__csp_directives.items(): - if not isinstance(k, str): - raise ConfigurationError("CSP directive names must be a string.") - if isinstance(v, list): - for policy in v: - if not isinstance(policy, str): - raise ConfigurationError("CSP directive value must be a string or list of strings.") - elif not isinstance(v, str): - raise ConfigurationError("CSP directive value must be a string or list of strings.") - - if self.app__web_base_url is None: - self.app__web_base_url = self.app__api_base_url - - def handle_authentication(self): - self.validate_correct_type_of_configuration_attribute("authentication__type", (type(None), str)) - self.validate_correct_type_of_configuration_attribute("authentication__insecure_test_environment", bool) - - if self.authentication__type == "test" and not self.authentication__insecure_test_environment: - raise ConfigurationError("Test auth can only be used in an insecure test environment") - - # oauth - ptypes = str if self.authentication__type == "oauth" else (type(None), str) - self.validate_correct_type_of_configuration_attribute( - "authentication__params_oauth__oauth_api_base_url", ptypes - ) - self.validate_correct_type_of_configuration_attribute("authentication__params_oauth__client_id", ptypes) - self.validate_correct_type_of_configuration_attribute("authentication__params_oauth__client_secret", ptypes) - self.validate_correct_type_of_configuration_attribute( - "authentication__params_oauth__jwt_decode_options", (type(None), dict) - ) - self.validate_correct_type_of_configuration_attribute("authentication__params_oauth__session_cookie", bool) - - if self.authentication__params_oauth__session_cookie: - self.validate_correct_type_of_configuration_attribute( - "authentication__params_oauth__cookie", (type(None), dict) - ) - else: - self.validate_correct_type_of_configuration_attribute("authentication__params_oauth__cookie", dict) - - self.auth = AuthTypeFactory.create(self.authentication__type, self) - if self.auth is None: - raise ConfigurationError(f"Unknown authentication type: {self.authentication__type}") - - def handle_data_locator(self): - self.validate_correct_type_of_configuration_attribute("data_locator__s3__region_name", (type(None), bool, str)) - if self.data_locator__s3__region_name is True: - path = self.single_dataset__datapath or self.multi_dataset__dataroot - - if type(path) == dict: - # if multi_dataset__dataroot is a dict, then use the first key - # that is in s3. NOTE: it is not supported to have dataroots - # in different regions. - paths = [val.get("dataroot") for val in path.values()] - for path in paths: - if path.startswith("s3://"): - break - if path.startswith("s3://"): - region_name = discover_s3_region_name(path) - if region_name is None: - raise ConfigurationError(f"Unable to discover s3 region name from {path}") - else: - region_name = None - self.data_locator__s3__region_name = region_name - - def handle_data_source(self): - self.validate_correct_type_of_configuration_attribute("single_dataset__datapath", (str, type(None))) - self.validate_correct_type_of_configuration_attribute("multi_dataset__dataroot", (type(None), dict, str)) - - if self.single_dataset__datapath and self.multi_dataset__dataroot: - raise ConfigurationError( - "You must supply either a datapath (for single datasets) or a dataroot (for multidatasets). Not both" - ) - if self.single_dataset__datapath is None and self.multi_dataset__dataroot is None: - raise ConfigurationError("You must specify a datapath for a single dataset or a dataroot for multidatasets") - - def handle_single_dataset(self, context): - self.validate_correct_type_of_configuration_attribute("single_dataset__datapath", (str, type(None))) - self.validate_correct_type_of_configuration_attribute("single_dataset__title", (str, type(None))) - self.validate_correct_type_of_configuration_attribute("single_dataset__about", (str, type(None))) - self.validate_correct_type_of_configuration_attribute("single_dataset__obs_names", (str, type(None))) - self.validate_correct_type_of_configuration_attribute("single_dataset__var_names", (str, type(None))) - - if self.single_dataset__datapath is None: - return - - # create the matrix data cache manager: - if self.matrix_data_cache_manager is None: - self.matrix_data_cache_manager = MatrixDataCacheManager(max_cached=1, timelimit_s=None) - - # preload this data set - matrix_data_loader = MatrixDataLoader(self.single_dataset__datapath, app_config=self.app_config) - try: - matrix_data_loader.pre_load_validation() - except DatasetAccessError as e: - raise ConfigurationError(str(e)) - - file_size = matrix_data_loader.file_size() - file_basename = basename(self.single_dataset__datapath) - if file_size > BIG_FILE_SIZE_THRESHOLD: - context["messagefn"](f"Loading data from {file_basename}, this may take a while...") - else: - context["messagefn"](f"Loading data from {file_basename}.") - - if self.single_dataset__about: - - def url_check(url): - try: - result = urlparse(url) - if all([result.scheme, result.netloc]): - return True - else: - return False - except ValueError: - return False - - if not url_check(self.single_dataset__about): - raise ConfigurationError( - "Must provide an absolute URL for --about. (Example format: http://example.com)" - ) - - def handle_multi_dataset(self): - self.validate_correct_type_of_configuration_attribute("multi_dataset__dataroot", (type(None), dict, str)) - self.validate_correct_type_of_configuration_attribute("multi_dataset__index", (type(None), bool, str)) - self.validate_correct_type_of_configuration_attribute("multi_dataset__allowed_matrix_types", list) - self.validate_correct_type_of_configuration_attribute("multi_dataset__matrix_cache__max_datasets", int) - self.validate_correct_type_of_configuration_attribute( - "multi_dataset__matrix_cache__timelimit_s", (type(None), int, float) - ) - - if self.multi_dataset__dataroot is None: - return - - if type(self.multi_dataset__dataroot) == str: - default_dict = dict(base_url="d", dataroot=self.multi_dataset__dataroot) - self.multi_dataset__dataroot = dict(d=default_dict) - - for tag, dataroot_dict in self.multi_dataset__dataroot.items(): - if "base_url" not in dataroot_dict: - raise ConfigurationError(f"error in multi_dataset__dataroot: missing base_url for tag {tag}") - if "dataroot" not in dataroot_dict: - raise ConfigurationError(f"error in multi_dataset__dataroot: missing dataroot, for tag {tag}") - - base_url = dataroot_dict["base_url"] - - # sanity check for well formed base urls - bad = False - if type(base_url) != str: - bad = True - elif os.path.normpath(base_url) != base_url: - bad = True - else: - base_url_parts = base_url.split("/") - if [quote_plus(part) for part in base_url_parts] != base_url_parts: - bad = True - if ".." in base_url_parts: - bad = True - if bad: - raise ConfigurationError(f"error in multi_dataset__dataroot base_url {base_url} for tag {tag}") - - # verify all the base_urls are unique - base_urls = [d["base_url"] for d in self.multi_dataset__dataroot.values()] - if len(base_urls) > len(set(base_urls)): - raise ConfigurationError("error in multi_dataset__dataroot: base_urls must be unique") - - # error checking - for mtype in self.multi_dataset__allowed_matrix_types: - try: - MatrixDataType(mtype) - except ValueError: - raise ConfigurationError(f'Invalid matrix type in "allowed_matrix_types": {mtype}') - - # create the matrix data cache manager: - if self.matrix_data_cache_manager is None: - self.matrix_data_cache_manager = MatrixDataCacheManager( - max_cached=self.multi_dataset__matrix_cache__max_datasets, - timelimit_s=self.multi_dataset__matrix_cache__timelimit_s, - ) - - def handle_diffexp(self): - self.validate_correct_type_of_configuration_attribute("diffexp__alg_cxg__max_workers", (str, int)) - self.validate_correct_type_of_configuration_attribute("diffexp__alg_cxg__cpu_multiplier", int) - self.validate_correct_type_of_configuration_attribute("diffexp__alg_cxg__target_workunit", int) - - max_workers = self.diffexp__alg_cxg__max_workers - cpu_multiplier = self.diffexp__alg_cxg__cpu_multiplier - cpu_count = os.cpu_count() - max_workers = min(max_workers, cpu_multiplier * cpu_count) - diffexp_tiledb.set_config(max_workers, self.diffexp__alg_cxg__target_workunit) - - def handle_adaptor(self): - # cxg - self.validate_correct_type_of_configuration_attribute("adaptor__cxg_adaptor__tiledb_ctx", dict) - regionkey = "vfs.s3.region" - if regionkey not in self.adaptor__cxg_adaptor__tiledb_ctx: - if type(self.data_locator__s3__region_name) == str: - self.adaptor__cxg_adaptor__tiledb_ctx[regionkey] = self.data_locator__s3__region_name - - from backend.czi_hosted.data_cxg.cxg_adaptor import CxgAdaptor - - CxgAdaptor.set_tiledb_context(self.adaptor__cxg_adaptor__tiledb_ctx) - - # anndata - self.validate_correct_type_of_configuration_attribute("adaptor__anndata_adaptor__backed", bool) - - def handle_limits(self): - self.validate_correct_type_of_configuration_attribute("limits__diffexp_cellcount_max", (type(None), int)) - self.validate_correct_type_of_configuration_attribute("limits__column_request_max", (type(None), int)) - - def exceeds_limit(self, limit_name, value): - limit_value = getattr(self, "limits__" + limit_name, None) - if limit_value is None: # disabled - return False - return value > limit_value - - def get_api_base_url(self): - if self.app__api_base_url == "local": - return f"http://{self.app__host}:{self.app__port}" - if self.app__api_base_url and self.app__api_base_url.endswith("/"): - return self.app__api_base_url[:-1] - return self.app__api_base_url - - def get_web_base_url(self): - if self.app__web_base_url == "local": - return f"http://{self.app__host}:{self.app__port}" - if self.app__web_base_url is None: - return self.get_api_base_url() - if self.app__web_base_url.endswith("/"): - return self.app__web_base_url[:-1] - return self.app__web_base_url diff --git a/backend/czi_hosted/common/corpora.py b/backend/czi_hosted/common/corpora.py deleted file mode 100644 index 29f5a62f..00000000 --- a/backend/czi_hosted/common/corpora.py +++ /dev/null @@ -1,78 +0,0 @@ -""" -Corpora schema conventions support. Helper functions for reading. - -https://github.com/chanzuckerberg/corpora-data-portal/blob/main/backend/schema/corpora_schema.md - -https://github.com/chanzuckerberg/corpora-data-portal/blob/main/backend/schema/corpora_schema_h5ad_implementation.md -""" -import collections -import json - -from backend.czi_hosted.cli.upgrade import validate_version_str -from backend.czi_hosted.common.utils.corpora_constants import CorporaConstants - - -def corpora_get_versions_from_anndata(adata): - """ - Given an AnnData object, return: - * None - if not a Corpora object - * [ corpora_schema_version, corpora_encoding_version ] - if a Corpora object - - Implements the identification protocol defined in the specification. - """ - - # per Corpora AnnData spec, this is a corpora file if the following is true - if "version" not in adata.uns_keys(): - return None - version = adata.uns["version"] - if not isinstance(version, collections.abc.Mapping) or "corpora_schema_version" not in version: - return None - - corpora_schema_version = version.get("corpora_schema_version") - corpora_encoding_version = version.get("corpora_encoding_version") - - # TODO: spec says these must be SEMVER values, so check. - if validate_version_str(corpora_schema_version) and validate_version_str(corpora_encoding_version): - return [corpora_schema_version, corpora_encoding_version] - - -def corpora_is_version_supported(corpora_schema_version, corpora_encoding_version): - return ( - corpora_schema_version - and corpora_encoding_version - and corpora_schema_version.startswith("1.") - and corpora_encoding_version.startswith("0.1.") - ) - - -def corpora_get_props_from_anndata(adata): - """ - Get Corpora dataset properties from an AnnData - """ - versions = corpora_get_versions_from_anndata(adata) - if versions is None: - return None - [corpora_schema_version, corpora_encoding_version] = versions - version_is_supported = corpora_is_version_supported(corpora_schema_version, corpora_encoding_version) - if not version_is_supported: - raise ValueError("Unsupported Corpora schema version") - - corpora_props = {} - for key in CorporaConstants.REQUIRED_SIMPLE_METADATA_FIELDS: - if key not in adata.uns: - raise KeyError(f"missing Corpora schema field {key}") - corpora_props[key] = adata.uns[key] - - for key in CorporaConstants.OPTIONAL_JSON_ENCODED_METADATA_FIELD: - if key not in adata.uns: - continue - try: - corpora_props[key] = json.loads(adata.uns[key]) - except json.JSONDecodeError: - raise json.JSONDecodeError(f"Corpora schema field {key} is expected to be a valid JSON string") - - for key in CorporaConstants.OPTIONAL_SIMPLE_METADATA_FIELDS: - if key in adata.uns: - corpora_props[key] = adata.uns[key] - - return corpora_props diff --git a/backend/czi_hosted/common/health.py b/backend/czi_hosted/common/health.py deleted file mode 100644 index db13630d..00000000 --- a/backend/czi_hosted/common/health.py +++ /dev/null @@ -1,38 +0,0 @@ -from http import HTTPStatus -from flask import make_response, jsonify - -from backend.czi_hosted import __version__ as cellxgene_version -from backend.common.utils.data_locator import DataLocator - - -def _is_accessible(path, config): - if path is None: - return True - - try: - dl = DataLocator(path, region_name=config.data_locator__s3__region_name) - return dl.exists() - except RuntimeError: - return False - - -def health_check(config): - """ - simple health check - return HTTP response. - See https://tools.ietf.org/id/draft-inadarei-api-health-check-01.html - """ - health = {"status": None, "version": "1", "releaseID": cellxgene_version} - - checks = False - server_config = config.server_config - if config.is_multi_dataset(): - dataroots = [datapath_dict["dataroot"] for datapath_dict in server_config.multi_dataset__dataroot.values()] - checks = all([_is_accessible(dataroot, server_config) for dataroot in dataroots]) - else: - checks = _is_accessible(server_config.single_dataset__datapath, server_config) - - health["status"] = "pass" if checks else "fail" - code = HTTPStatus.OK if health["status"] == "pass" else HTTPStatus.BAD_REQUEST - response = make_response(jsonify(health), code) - response.headers["Content-Type"] = "application/health+json" - return response diff --git a/backend/czi_hosted/common/immutable_kvcache.py b/backend/czi_hosted/common/immutable_kvcache.py deleted file mode 100644 index dddfe879..00000000 --- a/backend/czi_hosted/common/immutable_kvcache.py +++ /dev/null @@ -1,71 +0,0 @@ -import threading -from collections.abc import MutableMapping - - -class ImmutableKVCache(MutableMapping): - """ - Guarantees that the factory will be called for each key once, and - only once. - """ - - def __init__(self, factory): - self.factory = factory # user-provided factory function - self.lock = threading.Lock() # guards factory_calls - self.factory_calls = {} # per-key factory condition variables - self.cache = {} # result cache, indexed by key - super().__init__() - - def __getitem__(self, key): - if key in self.cache: - return self.cache[key] - - # we need to call factory. First grab the main lock and the per-key CV. - factory_calls = None - creation_thr = False - with self.lock: - if key in self.cache: - return self.cache[key] - if key not in self.factory_calls: - creation_thr = True - self.factory_calls[key] = {"cv": threading.Condition(), "is_done": False, "error": None} - factory_calls = self.factory_calls[key] - - # with the CV, create the value (or wait for it to be created) - cv = factory_calls["cv"] - with cv: - if creation_thr: - try: - self.cache[key] = self.factory(key) - except Exception as e: - factory_calls["error"] = e - - factory_calls["is_done"] = True - cv.notify_all() - else: - """ wait for the value to be available """ - while not factory_calls["is_done"]: - cv.wait() - - with self.lock: - if key in self.factory_calls: - del self.factory_calls[key] - - return self.cache[key] - - def __iter__(self): - """ weak iter, don't call factory """ - return self.cache.__iter__() - - def __len__(self): - return self.cache.__len__() - - def __contains__(self, key): - """ weak contain - don't call factory """ - return self.cache.__contains__(key) - - def __delitem__(self, key): - del self.cache[key] - - def __setitem__(self, key, value): - """ unsupported """ - raise NotImplementedError diff --git a/backend/czi_hosted/common/rest.py b/backend/czi_hosted/common/rest.py deleted file mode 100644 index 5ca17d1c..00000000 --- a/backend/czi_hosted/common/rest.py +++ /dev/null @@ -1,381 +0,0 @@ -import copy -import logging -import sys -from http import HTTPStatus -import zlib -import json - -from flask import make_response, jsonify, current_app, abort -from werkzeug.urls import url_unquote - -from backend.czi_hosted.common.config.client_config import get_client_config, get_client_userinfo -from backend.common.constants import Axis, DiffExpMode, JSON_NaN_to_num_warning_msg -from backend.common.errors import ( - FilterError, - JSONEncodingValueError, - PrepareError, - DisabledFeatureError, - ExceedsLimitError, - DatasetAccessError, - ColorFormatException, - AnnotationsError, - UnsupportedSummaryMethod, -) -from backend.common.genesets import summarizeQueryHash -from backend.common.fbs.matrix import decode_matrix_fbs - - -def abort_and_log(code, logmsg, loglevel=logging.DEBUG, include_exc_info=False): - """ - Log the message, then abort with HTTP code. If include_exc_info is true, - also include current exception via sys.exc_info(). - """ - if include_exc_info: - exc_info = sys.exc_info() - else: - exc_info = False - current_app.logger.log(loglevel, logmsg, exc_info=exc_info) - # Do NOT send log message to HTTP response. - return abort(code) - - -def _query_parameter_to_filter(args): - """ - Convert an annotation value filter, if present in the query args, - into the standard dict filter format used by internal code. - - Query param filters look like: :name=value, where value - may be one of: - - a range, min,max, where either may be an open range by using an asterisc, eg, 10,* - - a value - Eg, - ...?tissue=lung&obs:tissue=heart&obs:num_reads=1000,* - """ - filters = { - "obs": {}, - "var": {}, - } - - # args has already been url-unquoted once. We assume double escaping - # on name and value. - try: - for key, value in args.items(multi=True): - axis, name = key.split(":") - if axis not in ("obs", "var"): - raise FilterError("unknown filter axis") - name = url_unquote(name) - current = filters[axis].setdefault(name, {"name": name}) - - val_split = value.split(",") - if len(val_split) == 1: - if "min" in current or "max" in current: - raise FilterError("do not mix range and value filters") - value = url_unquote(value) - values = current.setdefault("values", []) - values.append(value) - - elif len(val_split) == 2: - if len(current) > 1: - raise FilterError("duplicate range specification") - min = url_unquote(val_split[0]) - max = url_unquote(val_split[1]) - if min != "*": - current["min"] = float(min) - if max != "*": - current["max"] = float(max) - if len(current) < 2: - raise FilterError("must specify at least min or max in range filter") - - else: - raise FilterError("badly formated filter value") - - except ValueError as e: - raise FilterError(str(e)) - - result = {} - for axis in ("obs", "var"): - axis_filter = filters[axis] - if len(axis_filter) > 0: - result[axis] = {"annotation_value": [val for val in axis_filter.values()]} - - return result - - -def schema_get_helper(data_adaptor): - """helper function to gather the schema from the data source and annotations""" - schema = data_adaptor.get_schema() - schema = copy.deepcopy(schema) - - # add label obs annotations as needed - annotations = data_adaptor.dataset_config.user_annotations - if annotations.user_annotations_enabled(): - label_schema = annotations.get_schema(data_adaptor) - schema["annotations"]["obs"]["columns"].extend(label_schema) - - return schema - - -def schema_get(data_adaptor): - schema = schema_get_helper(data_adaptor) - return make_response(jsonify({"schema": schema}), HTTPStatus.OK) - - -def config_get(app_config, data_adaptor): - config = get_client_config(app_config, data_adaptor) - return make_response(jsonify(config), HTTPStatus.OK) - - -def userinfo_get(app_config, data_adaptor): - config = get_client_userinfo(app_config, data_adaptor) - return make_response(jsonify(config), HTTPStatus.OK) - - -def annotations_obs_get(request, data_adaptor): - fields = request.args.getlist("annotation-name", None) - num_columns_requested = len(data_adaptor.get_obs_keys()) if len(fields) == 0 else len(fields) - if data_adaptor.server_config.exceeds_limit("column_request_max", num_columns_requested): - return abort(HTTPStatus.BAD_REQUEST) - preferred_mimetype = request.accept_mimetypes.best_match(["application/octet-stream"]) - if preferred_mimetype != "application/octet-stream": - return abort(HTTPStatus.NOT_ACCEPTABLE) - - try: - labels = None - annotations = data_adaptor.dataset_config.user_annotations - if annotations.user_annotations_enabled(): - labels = annotations.read_labels(data_adaptor) - fbs = data_adaptor.annotation_to_fbs_matrix(Axis.OBS, fields, labels) - return make_response(fbs, HTTPStatus.OK, {"Content-Type": "application/octet-stream"}) - except KeyError as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - - -def annotations_put_fbs_helper(data_adaptor, fbs): - """helper function to write annotations from fbs""" - annotations = data_adaptor.dataset_config.user_annotations - if not annotations.user_annotations_enabled(): - raise DisabledFeatureError("Writable annotations are not enabled") - - new_label_df = decode_matrix_fbs(fbs) - if not new_label_df.empty: - new_label_df = data_adaptor.check_new_labels(new_label_df) - annotations.write_labels(new_label_df, data_adaptor) - - -def inflate(data): - return zlib.decompress(data) - - -def annotations_obs_put(request, data_adaptor): - annotations = data_adaptor.dataset_config.user_annotations - if not annotations.user_annotations_enabled(): - return abort(HTTPStatus.NOT_IMPLEMENTED) - - anno_collection = request.args.get("annotation-collection-name", default=None) - fbs = inflate(request.get_data()) - - if anno_collection is not None: - if not annotations.is_safe_collection_name(anno_collection): - return abort(HTTPStatus.BAD_REQUEST, "Bad annotation collection name") - annotations.set_collection(anno_collection) - - try: - annotations_put_fbs_helper(data_adaptor, fbs) - res = json.dumps({"status": "OK"}) - return make_response(res, HTTPStatus.OK, {"Content-Type": "application/json"}) - except (ValueError, DisabledFeatureError, KeyError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - - -def annotations_var_get(request, data_adaptor): - fields = request.args.getlist("annotation-name", None) - num_columns_requested = len(data_adaptor.get_var_keys()) if len(fields) == 0 else len(fields) - if data_adaptor.server_config.exceeds_limit("column_request_max", num_columns_requested): - return abort(HTTPStatus.BAD_REQUEST) - preferred_mimetype = request.accept_mimetypes.best_match(["application/octet-stream"]) - if preferred_mimetype != "application/octet-stream": - return abort(HTTPStatus.NOT_ACCEPTABLE) - - try: - labels = None - annotations = data_adaptor.dataset_config.user_annotations - if annotations.user_annotations_enabled(): - labels = annotations.read_labels(data_adaptor) - return make_response( - data_adaptor.annotation_to_fbs_matrix(Axis.VAR, fields, labels), - HTTPStatus.OK, - {"Content-Type": "application/octet-stream"}, - ) - except KeyError as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - - -def data_var_put(request, data_adaptor): - preferred_mimetype = request.accept_mimetypes.best_match(["application/octet-stream"]) - if preferred_mimetype != "application/octet-stream": - return abort(HTTPStatus.NOT_ACCEPTABLE) - - filter_json = request.get_json() - filter = filter_json["filter"] if filter_json else None - try: - return make_response( - data_adaptor.data_frame_to_fbs_matrix(filter, axis=Axis.VAR), - HTTPStatus.OK, - {"Content-Type": "application/octet-stream"}, - ) - except (FilterError, ValueError, ExceedsLimitError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - - -def data_var_get(request, data_adaptor): - preferred_mimetype = request.accept_mimetypes.best_match(["application/octet-stream"]) - if preferred_mimetype != "application/octet-stream": - return abort(HTTPStatus.NOT_ACCEPTABLE) - - try: - filter = _query_parameter_to_filter(request.args) - return make_response( - data_adaptor.data_frame_to_fbs_matrix(filter, axis=Axis.VAR), - HTTPStatus.OK, - {"Content-Type": "application/octet-stream"}, - ) - except (FilterError, ValueError, ExceedsLimitError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - - -def colors_get(data_adaptor): - if not data_adaptor.dataset_config.presentation__custom_colors: - return make_response(jsonify({}), HTTPStatus.OK) - try: - return make_response(jsonify(data_adaptor.get_colors()), HTTPStatus.OK) - except ColorFormatException as e: - return abort_and_log(HTTPStatus.NOT_FOUND, str(e), include_exc_info=True) - - -def diffexp_obs_post(request, data_adaptor): - if not data_adaptor.dataset_config.diffexp__enable: - return abort(HTTPStatus.NOT_IMPLEMENTED) - - args = request.get_json() - try: - # TODO: implement varfilter mode - mode = DiffExpMode(args["mode"]) - if mode == DiffExpMode.VAR_FILTER or "varFilter" in args: - return abort_and_log(HTTPStatus.NOT_IMPLEMENTED, "varFilter not enabled") - - set1_filter = args.get("set1", {"filter": {}})["filter"] - set2_filter = args.get("set2", {"filter": {}})["filter"] - # TODO(#1281): When we simplify the config, we should actually use the config to determine this number, - # this will also require an update in the client - count = 15 - - if set1_filter is None or set2_filter is None or count is None: - return abort_and_log(HTTPStatus.BAD_REQUEST, "missing required parameter") - if Axis.VAR in set1_filter or Axis.VAR in set2_filter: - return abort_and_log(HTTPStatus.BAD_REQUEST, "var axis filter not enabled") - - except (KeyError, TypeError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - - try: - diffexp = data_adaptor.diffexp_topN(set1_filter, set2_filter, count) - return make_response(diffexp, HTTPStatus.OK, {"Content-Type": "application/json"}) - except (ValueError, DisabledFeatureError, FilterError, ExceedsLimitError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - except JSONEncodingValueError: - # JSON encoding failure, usually due to bad data. Just let it ripple up - # to default exception handler. - current_app.logger.warning(JSON_NaN_to_num_warning_msg) - raise - - -def layout_obs_get(request, data_adaptor): - fields = request.args.getlist("layout-name", None) - num_columns_requested = len(data_adaptor.get_embedding_names()) if len(fields) == 0 else len(fields) - if data_adaptor.server_config.exceeds_limit("column_request_max", num_columns_requested): - return abort(HTTPStatus.BAD_REQUEST) - - preferred_mimetype = request.accept_mimetypes.best_match(["application/octet-stream"]) - if preferred_mimetype != "application/octet-stream": - return abort(HTTPStatus.NOT_ACCEPTABLE) - - try: - return make_response( - data_adaptor.layout_to_fbs_matrix(fields), HTTPStatus.OK, {"Content-Type": "application/octet-stream"} - ) - except (KeyError, DatasetAccessError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e), include_exc_info=True) - except PrepareError: - return abort_and_log( - HTTPStatus.NOT_IMPLEMENTED, - f"No embedding available {request.path}", - loglevel=logging.ERROR, - include_exc_info=True, - ) - - -def genesets_get(request, data_adaptor): - preferred_mimetype = request.accept_mimetypes.best_match(["application/json", "text/csv"]) - if preferred_mimetype not in ("application/json", "text/csv"): - return abort(HTTPStatus.NOT_ACCEPTABLE) - - try: - annotations = data_adaptor.dataset_config.user_annotations - (genesets, tid) = annotations.read_gene_sets(data_adaptor) - - if preferred_mimetype == "text/csv": - return make_response( - annotations.gene_sets_to_csv(genesets), - HTTPStatus.OK, - { - "Content-Type": "text/csv", - "Content-Disposition": "attachment; filename=genesets.csv", - }, - ) - else: - return make_response( - jsonify({"genesets": annotations.gene_sets_to_response(genesets), "tid": tid}), HTTPStatus.OK - ) - except (ValueError, KeyError, AnnotationsError) as e: - return abort_and_log(HTTPStatus.BAD_REQUEST, str(e)) - - -def summarize_var_helper(request, data_adaptor, key, raw_query): - preferred_mimetype = request.accept_mimetypes.best_match(["application/octet-stream"]) - if preferred_mimetype != "application/octet-stream": - return abort(HTTPStatus.NOT_ACCEPTABLE) - - summary_method = request.values.get("method", default="mean") - query_hash = summarizeQueryHash(raw_query) - if key and query_hash != key: - return abort(HTTPStatus.BAD_REQUEST, description="query key did not match") - - args_filter_only = request.values.copy() - args_filter_only.poplist("method") - args_filter_only.poplist("key") - - try: - filter = _query_parameter_to_filter(args_filter_only) - return make_response( - data_adaptor.summarize_var(summary_method, filter, query_hash), - HTTPStatus.OK, - {"Content-Type": "application/octet-stream"}, - ) - except (ValueError) as e: - return abort(HTTPStatus.NOT_FOUND, description=str(e)) - except (UnsupportedSummaryMethod, FilterError) as e: - return abort(HTTPStatus.BAD_REQUEST, description=str(e)) - - -def summarize_var_get(request, data_adaptor): - return summarize_var_helper(request, data_adaptor, None, request.query_string) - - -def summarize_var_post(request, data_adaptor): - if not request.content_type or "application/x-www-form-urlencoded" not in request.content_type: - return abort(HTTPStatus.UNSUPPORTED_MEDIA_TYPE) - if request.content_length > 1_000_000: # just a sanity check to avoid memory exhaustion - return abort(HTTPStatus.BAD_REQUEST) - - key = request.args.get("key", default=None) - return summarize_var_helper(request, data_adaptor, key, request.get_data()) diff --git a/backend/czi_hosted/common/utils/__init__.py b/backend/czi_hosted/common/utils/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/common/utils/corpora_constants.py b/backend/czi_hosted/common/utils/corpora_constants.py deleted file mode 100644 index fa1641d5..00000000 --- a/backend/czi_hosted/common/utils/corpora_constants.py +++ /dev/null @@ -1,22 +0,0 @@ -class CorporaConstants(object): - REQUIRED_SIMPLE_METADATA_FIELDS = [ - "version", - "title", - "layer_descriptions", - "organism", - "organism_ontology_term_id", - ] - - # The Corpora specification requires some values encoded as JSON due to the inability of AnnData to store complex - # types. - OPTIONAL_JSON_ENCODED_METADATA_FIELD = ["contributors", "project_links"] - - OPTIONAL_SIMPLE_METADATA_FIELDS = [ - "preprint_doi", - "publication_doi", - "default_embedding", - "default_field", - "tags", - "project_name", - "project_description", - ] diff --git a/backend/czi_hosted/common/utils/cxg_constants.py b/backend/czi_hosted/common/utils/cxg_constants.py deleted file mode 100644 index 5982ec15..00000000 --- a/backend/czi_hosted/common/utils/cxg_constants.py +++ /dev/null @@ -1,4 +0,0 @@ -class CxgConstants(object): - # The CXG container version number. Must be a semver string (major.minor.patch) - # DO NOT UPDATE THIS WITHOUT ALSO UPDATING CXG SPECIFICATION. - CXG_VERSION = "0.2.0" diff --git a/backend/czi_hosted/common/utils/cxg_generation_utils.py b/backend/czi_hosted/common/utils/cxg_generation_utils.py deleted file mode 100644 index c3c1c867..00000000 --- a/backend/czi_hosted/common/utils/cxg_generation_utils.py +++ /dev/null @@ -1,178 +0,0 @@ -import json - -import numpy as np -import tiledb - -from backend.common.utils.type_conversion_utils import get_encoding_dtype_of_array, get_dtype_and_schema_of_array - - -def convert_dictionary_to_cxg_group(cxg_container, metadata_dict, group_metadata_name="cxg_group_metadata"): - """ - Saves the contents of the dictionary to the CXG output directory specified. - - This function is primarily used to save metadata about a dataset to the CXG directory. At some point, tiledb will - have support for metadata on groups at which point the utility of this function should be revisited. Until such - feature exists, this function create an empty array and annotate that array. - - For more information, visit https://github.com/TileDB-Inc/TileDB-Py/issues/254. - """ - - array_name = f"{cxg_container}/{group_metadata_name}" - - # Because TileDB does not allow one to attach metadata directly to a CXG group, we need to have a workaround - # where we create an empty array and attached the metadata onto to this empty array. Below we construct this empty - # array. - tiledb.from_numpy(array_name, np.zeros((1,))) - - with tiledb.DenseArray(array_name, mode="w") as metadata_array: - for key, value in metadata_dict.items(): - metadata_array.meta[key] = value - - -def convert_dataframe_to_cxg_array(cxg_container, dataframe_name, dataframe, index_column_name, ctx): - """ - Saves the contents of the dataframe to the CXG output directory specified. - - Current access patterns are oriented toward reading very large slices of the dataframe, one attribute at a time. - Attribute data also tends to be (often) repetitive (bools, categories, strings). Given this, we use a large tile - size (1000) and very aggressive compression levels. - """ - - def create_dataframe_array(array_name, dataframe): - tiledb_filter = tiledb.FilterList( - [ - # Attempt aggressive compression as many of these dataframes are very repetitive strings, bools and - # other non-float data. - tiledb.ZstdFilter(level=22), - ] - ) - attrs = [ - tiledb.Attr(name=column, dtype=get_encoding_dtype_of_array(dataframe[column]), filters=tiledb_filter) - for column in dataframe - ] - domain = tiledb.Domain( - tiledb.Dim(domain=(0, dataframe.shape[0] - 1), tile=min(dataframe.shape[0], 1000), dtype=np.uint32) - ) - schema = tiledb.ArraySchema( - domain=domain, sparse=False, attrs=attrs, cell_order="row-major", tile_order="row-major" - ) - tiledb.DenseArray.create(array_name, schema) - - array_name = f"{cxg_container}/{dataframe_name}" - - create_dataframe_array(array_name, dataframe) - - with tiledb.DenseArray(array_name, mode="w", ctx=ctx) as array: - value = {} - schema_hints = {} - for column_name, column_values in dataframe.items(): - dtype, hints = get_dtype_and_schema_of_array(column_values) - value[column_name] = column_values.to_numpy(dtype=dtype) - if hints: - schema_hints.update({column_name: hints}) - - schema_hints.update({"index": index_column_name}) - array[:] = value - array.meta["cxg_schema"] = json.dumps(schema_hints) - - tiledb.consolidate(array_name, ctx=ctx) - - -def convert_ndarray_to_cxg_dense_array(ndarray_name, ndarray, ctx): - """ - Saves contents of ndarray to the CXG output directory specified. - - Generally this function is used to convert dataset embeddings. Because embeddings are typically accessed with - very large slices (or all of the embedding), they do not benefit from overly aggressive compression due to their - format. Given this, we use a large tile size (1000) but only default compression level. - """ - - def create_ndarray_array(ndarray_name, ndarray): - filters = tiledb.FilterList([tiledb.ZstdFilter()]) - attrs = [tiledb.Attr(dtype=ndarray.dtype, filters=filters)] - dimensions = [ - tiledb.Dim( - domain=(0, ndarray.shape[dimension] - 1), tile=min(ndarray.shape[dimension], 1000), dtype=np.uint32 - ) - for dimension in range(ndarray.ndim) - ] - domain = tiledb.Domain(*dimensions) - schema = tiledb.ArraySchema( - domain=domain, sparse=False, attrs=attrs, capacity=1_000_000, cell_order="row-major", tile_order="row-major" - ) - tiledb.DenseArray.create(ndarray_name, schema) - - create_ndarray_array(ndarray_name, ndarray) - - with tiledb.DenseArray(ndarray_name, mode="w", ctx=ctx) as array: - array[:] = ndarray - - tiledb.consolidate(ndarray_name, ctx=ctx) - - -def convert_matrix_to_cxg_array( - matrix_name, matrix, encode_as_sparse_array, ctx, column_shift_for_sparse_encoding=None -): - """ - Converts a numpy array matrix into a TileDB SparseArray of DenseArray based on whether `encode_as_sparse_array` - is true or not. Note that when the matrix is encoded as a SparseArray, it only writes the values that are - nonzero. This means that if you count the number of elements in the SparseArray, it will not equal the total - number of elements in the matrix, only the number of nonzero elements. - - Furthermore, if the `column_shift_for_sparse_encoding` matrix is not None, this function will subtract the sparse - encoding from the original given matrix and as previously stated, only write the nonzero values to the TileDB - SparseArray. - """ - - def create_matrix_array(matrix_name, number_of_rows, number_of_columns, encode_as_sparse_array): - filters = tiledb.FilterList([tiledb.ZstdFilter()]) - attrs = [tiledb.Attr(dtype=np.float32, filters=filters)] - if encode_as_sparse_array: - domain = tiledb.Domain( - tiledb.Dim(name="obs", domain=(0, number_of_rows - 1), tile=min(number_of_rows, 512), dtype=np.uint32), - tiledb.Dim( - name="var", domain=(0, number_of_columns - 1), tile=min(number_of_columns, 2048), dtype=np.uint32 - ), - ) - else: - domain = tiledb.Domain( - tiledb.Dim(name="obs", domain=(0, number_of_rows - 1), tile=min(number_of_rows, 50), dtype=np.uint32), - tiledb.Dim( - name="var", domain=(0, number_of_columns - 1), tile=min(number_of_columns, 100), dtype=np.uint32 - ), - ) - schema = tiledb.ArraySchema( - domain=domain, sparse=encode_as_sparse_array, attrs=attrs, cell_order="row-major", tile_order="col-major" - ) - if encode_as_sparse_array: - tiledb.SparseArray.create(matrix_name, schema) - else: - tiledb.DenseArray.create(matrix_name, schema) - - number_of_rows = matrix.shape[0] - number_of_columns = matrix.shape[1] - stride = min(int(np.power(10, np.around(np.log10(1e9 / number_of_columns)))), 10_000) - - create_matrix_array(matrix_name, number_of_rows, number_of_columns, encode_as_sparse_array) - - if encode_as_sparse_array: - with tiledb.SparseArray(matrix_name, mode="w", ctx=ctx) as array: - for start_row_index in range(0, number_of_rows, stride): - end_row_index = min(start_row_index + stride, number_of_rows) - matrix_subset = matrix[start_row_index:end_row_index, :] - if not isinstance(matrix_subset, np.ndarray): - matrix_subset = matrix_subset.toarray() - if column_shift_for_sparse_encoding is not None: - matrix_subset = matrix_subset - column_shift_for_sparse_encoding - indices = np.nonzero(matrix_subset) - trow = indices[0] + start_row_index - array[trow, indices[1]] = matrix_subset[indices[0], indices[1]] - - else: - with tiledb.DenseArray(matrix_name, mode="w", ctx=ctx) as array: - for start_row_index in range(0, number_of_rows, stride): - end_row_index = min(start_row_index + stride, number_of_rows) - matrix_subset = matrix[start_row_index:end_row_index, :] - if not isinstance(matrix_subset, np.ndarray): - matrix_subset = matrix_subset.toarray() - array[start_row_index:end_row_index, :] = matrix_subset diff --git a/backend/czi_hosted/common/utils/matrix_utils.py b/backend/czi_hosted/common/utils/matrix_utils.py deleted file mode 100644 index 60dfb19b..00000000 --- a/backend/czi_hosted/common/utils/matrix_utils.py +++ /dev/null @@ -1,115 +0,0 @@ -import logging - -import numpy as np -from scipy.stats import mode - - -def is_matrix_sparse(matrix: np.ndarray, sparse_threshold): - """ - Returns whether `matrix` is sparse or not (i.e. dense). This is determined by figuring out whether the matrix has - a sparsity percentage below the sparse_threshold, returning the number of non-zeros encountered and number of - elements evaluated. This function may return before evaluating the whole matrix if it can be determined that matrix - is not sparse enough. - """ - - if sparse_threshold == 100.0: - return True - if sparse_threshold == 0.0: - return False - - total_number_of_rows = matrix.shape[0] - total_number_of_columns = matrix.shape[1] - total_number_of_matrix_elements = total_number_of_rows * total_number_of_columns - - # For efficiency, we count the number of non-zero elements in chunks of the matrix at a time until we hit the - # maximum number of non zero values allowed before the matrix is deemed "dense." This allows the function the - # quit early for large dense matrices. - row_stride = min(int(np.power(10, np.around(np.log10(1e9 / total_number_of_columns)))), 10_000) - - maximum_number_of_non_zero_elements_in_matrix = int( - total_number_of_rows * total_number_of_columns * sparse_threshold / 100 - ) - number_of_non_zero_elements = 0 - - for start_row_index in range(0, total_number_of_rows, row_stride): - end_row_index = min(start_row_index + row_stride, total_number_of_rows) - - matrix_subset = matrix[start_row_index:end_row_index, :] - if not isinstance(matrix_subset, np.ndarray): - matrix_subset = matrix_subset.toarray() - - number_of_non_zero_elements += np.count_nonzero(matrix_subset) - if number_of_non_zero_elements > maximum_number_of_non_zero_elements_in_matrix: - if end_row_index != total_number_of_rows: - percentage_of_non_zero_elements = ( - 100 * number_of_non_zero_elements / (end_row_index * total_number_of_columns) - ) - logging.info( - f"Matrix is not sparse. Percentage of non-zero elements (estimate): " - f"{percentage_of_non_zero_elements:6.2f}" - ) - else: - percentage_of_non_zero_elements = 100 * number_of_non_zero_elements / total_number_of_matrix_elements - logging.info( - f"Matrix is not sparse. Percentage of non-zero elements (exact): " - f"{percentage_of_non_zero_elements:6.2f}" - ) - return False - - is_sparse = (100.0 * number_of_non_zero_elements / total_number_of_matrix_elements) < sparse_threshold - return is_sparse - - -def get_column_shift_encode_for_matrix(matrix, sparse_threshold): - """ - Returns a column shift if there is a column shift that allows the given matrix to be considered as sparse. Column - shift encoding works by taking the most common value in each column, then subtracting that value from each element - of the column. If each column mostly contains its most common value, then the resulting matrix can be very sparse. - - This function determines if column shift encoding can be used to transform the matrix into a sparse matrix with a - sparsity below the sparse_threshold. If so, returns the array that stores this encoding. This function also returns - the number of non-zeros encountered and number of elements evaluated. This function may return before evaluating - the whole matrix if it can be determined that the matrix cannot benefit from column shift encoding. - """ - - total_number_of_rows = matrix.shape[0] - total_number_of_columns = matrix.shape[1] - total_number_of_matrix_elements = total_number_of_rows * total_number_of_columns - - stride = max(1, 128_000_000 // total_number_of_rows) - column_shift = np.zeros(total_number_of_columns) - - maximum_number_of_non_zero_elements_in_matrix = int( - total_number_of_rows * total_number_of_columns * sparse_threshold / 100 - ) - number_of_non_zero_elements = 0 - - for start_column_index in range(0, total_number_of_columns, stride): - end_column_index = min(start_column_index + stride, total_number_of_columns) - - matrix_subset = matrix[:, start_column_index:end_column_index] - if not isinstance(matrix_subset, np.ndarray): - matrix_subset = matrix_subset.toarray() - - matrix_subset_mode = mode(matrix_subset) - - column_shift[start_column_index:end_column_index] = matrix_subset_mode.mode - number_of_non_zero_elements += total_number_of_rows * (end_column_index - start_column_index) - np.sum( - matrix_subset_mode.count - ) - - if number_of_non_zero_elements > maximum_number_of_non_zero_elements_in_matrix: - if end_column_index != total_number_of_columns: - logging.info( - "Matrix is not sparse even with column shift. Percentage of non-zero elements (estimate): %6.2f" - % (100 * number_of_non_zero_elements / end_column_index * total_number_of_rows) - ) - else: - logging.info( - "Matrix is not sparse even with column shift. Percentage of non-zero elements (exact): %6.2f" - % (100 * number_of_non_zero_elements / total_number_of_matrix_elements) - ) - return None - - is_sparse = (100.0 * number_of_non_zero_elements / total_number_of_matrix_elements) < sparse_threshold - return column_shift if is_sparse else None diff --git a/backend/czi_hosted/common/utils/sanitization_utils.py b/backend/czi_hosted/common/utils/sanitization_utils.py deleted file mode 100644 index af6f299f..00000000 --- a/backend/czi_hosted/common/utils/sanitization_utils.py +++ /dev/null @@ -1,40 +0,0 @@ -import re - - -def sanitize_values_in_list(list_of_keys: list): - """ - Returns a dictionary mapping of the old keys in the list of `list_of_keys` to its new, clean name that is both - safe and unique. - """ - - if not all([isinstance(key, str) for key in list_of_keys]): - raise Exception("List of keys to sanitize must contain all strings.") - - # Mask out [~/.] and anything outside the ASCII range. - mask = re.compile(r"[^ -\-0-\[\]-\}]") - clean_keys_list = [mask.sub("_", key) for key in list_of_keys] - - # Dedupe the clean keys list - deduped_clean_keys_list = [] - for index, clean_key in enumerate(clean_keys_list): - total_occurrences_of_clean_key = clean_keys_list.count(clean_key) - total_occurrences_up_until_current_index = clean_keys_list[:index].count(clean_key) - deduped_clean_keys_list.append( - clean_key + "_" + str(total_occurrences_up_until_current_index + 1) - if total_occurrences_of_clean_key > 1 - else clean_key - ) - - return dict(zip(list_of_keys, deduped_clean_keys_list)) - - -def sanitize_keys_in_dictionary(dict_to_sanitize: dict): - """ - Clean and dedupe the keys in the given dictionary. - """ - - clean_keys = sanitize_values_in_list(dict_to_sanitize.keys()) - for original_key, sanitized_key in clean_keys.items(): - if original_key != sanitized_key: - dict_to_sanitize[sanitized_key] = dict_to_sanitize[original_key] - del dict_to_sanitize[original_key] diff --git a/backend/czi_hosted/common/web/__init__.py b/backend/czi_hosted/common/web/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/compute/__init__.py b/backend/czi_hosted/compute/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/compute/diffexp_cxg.py b/backend/czi_hosted/compute/diffexp_cxg.py deleted file mode 100644 index d37d866c..00000000 --- a/backend/czi_hosted/compute/diffexp_cxg.py +++ /dev/null @@ -1,199 +0,0 @@ -import concurrent.futures -import numpy as np - -from numba import jit - -from backend.czi_hosted.data_cxg.cxg_util import pack_selector_from_indices -from backend.common.compute.diffexp_generic import diffexp_ttest_from_mean_var, mean_var_n -from backend.common.errors import ComputeError - -""" -See the comments in diffexp_generic for a description of this algorithm - -This implementation runs directly in-process. It is multi- threaded, but not particularly scalable. -Longer term, will likely move to a distributed framework for this. - -There are currently no global throttles on simultaneous workers. -""" - -diffexp_thread_executor = None -max_workers = None -target_workunit = None - - -def set_config(config_max_workers, config_target_workunit): - global max_workers - global target_workunit - max_workers = config_max_workers - target_workunit = config_target_workunit - - -def get_thread_executor(): - global diffexp_thread_executor - if diffexp_thread_executor is None: - diffexp_thread_executor = concurrent.futures.ThreadPoolExecutor(max_workers=max_workers) - return diffexp_thread_executor - - -def diffexp_ttest(adaptor, maskA, maskB, top_n=8, diffexp_lfc_cutoff=0.01): - - matrix = adaptor.open_array("X") - row_selector_A = np.where(maskA)[0] - row_selector_B = np.where(maskB)[0] - nA = len(row_selector_A) - nB = len(row_selector_B) - - dtype = matrix.dtype - cols = matrix.shape[1] - tile_extent = [dim.tile for dim in matrix.schema.domain] - - is_sparse = matrix.schema.sparse - - if is_sparse: - row_selector_A = pack_selector_from_indices(row_selector_A) - row_selector_B = pack_selector_from_indices(row_selector_B) - else: - # The rows from both row_selector_A and row_selector_B are gathered at the - # same time, then the mean and variance are computed by subsetting on that - # combined submatrix. Combining the gather reduces number of requests/bandwidth - # to the data source. - row_selector_AB = np.union1d(row_selector_A, row_selector_B) - row_selector_A_in_AB = np.in1d(row_selector_AB, row_selector_A, assume_unique=True) - row_selector_B_in_AB = np.in1d(row_selector_AB, row_selector_B, assume_unique=True) - row_selector_AB = pack_selector_from_indices(row_selector_AB) - - # because all IO is done per-tile, and we are always col-major, - # use the tile column size as the unit of partition. Possibly access - # more than one column tile at a time based on the target_workunit. - # Revisit partitioning if we change the X layout, or start using a non-local execution environment - # which may have other constraints. - - # TODO: If the number of row selections is large enough, then the cells_per_coltile will exceed - # the target_workunit. A potential improvement would be to partition by both columns and rows. - # However partitioning the rows is slightly more complex due to the arbitrary distribution - # of row selections that are passed into this algorithm. - - cells_per_coltile = (nA + nB) * tile_extent[1] - cols_per_partition = max(1, int(target_workunit / cells_per_coltile)) * tile_extent[1] - col_partitions = [(c, min(c + cols_per_partition, cols)) for c in range(0, cols, cols_per_partition)] - - meanA = np.zeros((cols,), dtype=np.float64) - varA = np.zeros((cols,), dtype=np.float64) - meanB = np.zeros((cols,), dtype=np.float64) - varB = np.zeros((cols,), dtype=np.float64) - - executor = get_thread_executor() - futures = [] - - if is_sparse: - for cols in col_partitions: - futures.append(executor.submit(_mean_var_sparse_ab, matrix, row_selector_A, nA, row_selector_B, nB, cols)) - else: - for cols in col_partitions: - futures.append( - executor.submit(_mean_var_ab, matrix, row_selector_AB, row_selector_A_in_AB, row_selector_B_in_AB, cols) - ) - - for future in futures: - # returns tuple: (meanA, varA, meanB, varB, cols) - try: - result = future.result() - part_meanA, part_varA, part_meanB, part_varB, cols = result - meanA[cols[0] : cols[1]] += part_meanA - varA[cols[0] : cols[1]] += part_varA - meanB[cols[0] : cols[1]] += part_meanB - varB[cols[0] : cols[1]] += part_varB - except Exception as e: - for future in futures: - future.cancel() - raise ComputeError(str(e)) - - if is_sparse: - if adaptor.has_array("X_col_shift"): - X_col_shift = adaptor.open_array("X_col_shift")[:] - meanA += X_col_shift - meanB += X_col_shift - - r = diffexp_ttest_from_mean_var( - meanA=meanA.astype(dtype), - varA=varA.astype(dtype), - nA=nA, - meanB=meanB.astype(dtype), - varB=varB.astype(dtype), - nB=nB, - top_n=top_n, - diffexp_lfc_cutoff=diffexp_lfc_cutoff - ) - - return r - - -def _mean_var_ab(matrix, row_selector_AB, row_selector_A_in_AB, row_selector_B_in_AB, col_range): - X = matrix.multi_index[row_selector_AB, col_range[0] : col_range[1] - 1][""] - meanA, varA, n = mean_var_n(X[row_selector_A_in_AB]) - meanB, varB, n = mean_var_n(X[row_selector_B_in_AB]) - return (meanA, varA, meanB, varB, col_range) - - -def _mean_var_sparse_ab(matrix, row_selector_A, nrows_A, row_selector_B, nrows_B, col_range): - meanA, varA = _mean_var_sparse(matrix, row_selector_A, nrows_A, col_range) - meanB, varB = _mean_var_sparse(matrix, row_selector_B, nrows_B, col_range) - return (meanA, varA, meanB, varB, col_range) - - -@jit(nopython=True) -def _mean_var_sparse_numba(x, var, nrows, ncols): - """Kernel to compute the mean and variance. It was not clear if this function - could be written using numpy, thus avoiding the loops. Therefore numba is - used here to speed things up. With numba, this function takes a negligible amount - of time compared to reading in the sparse matrix""" - mean = np.zeros((ncols,), dtype=np.float64) - for col, val in zip(var, x): - mean[col] += val - mean /= nrows - - # optimize the sumsq computation. - # since most entries in a sparse matrix are 0, then start by assuming - # all values are 0, so fill the sumsq array with nrows * (0 - mean)**2. - # as non-zero values are encountered, subtract off the (mean*mean) value - # and replace with (val-mean)**2. Simplifying the expression - # gives the following code. - sumsq = nrows * np.multiply(mean, mean) - for col, val in zip(var, x): - sumsq[col] += val * (val - 2 * mean[col]) - v = sumsq / (nrows - 1) - return mean, v - - -def _mean_var_sparse(matrix, selector, nrows, col_range): - data = matrix.multi_index[selector, col_range[0] : col_range[1] - 1] - x = data[""] - - # tiledb < 0.6.0 and >= 0.6.0 have slightly different interfaces. - # the following takes care of both cases: - # older: data["coords]["var"] - # newer: data["var"] - var = data.get("coords", data)["var"] - - # shift the column indices to start at 0, this - # will become the index into the mean and var arrays. - var -= col_range[0] - - fp_err_occurred = False - - def fp_err_set(err, flag): - nonlocal fp_err_occurred - fp_err_occurred = True - - ncols = col_range[1] - col_range[0] - with np.errstate(divide="call", invalid="call", call=fp_err_set): - mean, v = _mean_var_sparse_numba(x, var, nrows, ncols) - - if fp_err_occurred: - mean[np.isfinite(mean) == False] = 0 # noqa: E712 - v[np.isfinite(v) == False] = 0 # noqa: E712 - else: - mean[np.isnan(mean)] = 0 - v[np.isnan(v)] = 0 - - return mean, v diff --git a/backend/czi_hosted/converters/__init__.py b/backend/czi_hosted/converters/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/converters/h5ad_data_file.py b/backend/czi_hosted/converters/h5ad_data_file.py deleted file mode 100644 index 7b09030b..00000000 --- a/backend/czi_hosted/converters/h5ad_data_file.py +++ /dev/null @@ -1,250 +0,0 @@ -import json -import logging -from os import path - -import anndata -import numpy as np -import tiledb - -from backend.common.colors import convert_anndata_category_colors_to_cxg_category_colors -from backend.czi_hosted.common.corpora import corpora_get_props_from_anndata -from backend.common.errors import ColorFormatException -from backend.czi_hosted.common.utils.cxg_constants import CxgConstants -from backend.czi_hosted.common.utils.cxg_generation_utils import ( - convert_dictionary_to_cxg_group, - convert_dataframe_to_cxg_array, - convert_ndarray_to_cxg_dense_array, - convert_matrix_to_cxg_array, -) -from backend.czi_hosted.common.utils.matrix_utils import is_matrix_sparse, get_column_shift_encode_for_matrix - - -class H5ADDataFile: - """ Class encapsulating required information about an H5AD datafile that ultimately will be transformed into - another format (currently just CXG is supported). """ - - def __init__( - self, - input_filename, - backed=False, - dataset_title=None, - dataset_about=None, - obs_index_column_name=None, - vars_index_column_name=None, - use_corpora_schema=True, - ): - self.input_filename = input_filename - self.backed = backed - self.dataset_title = dataset_title - self.dataset_about = dataset_about - self.obs_index_column_name = obs_index_column_name - self.vars_index_column_name = vars_index_column_name - - self.use_corpora_schema = use_corpora_schema - - self.validate_input_file_type() - - self.extract_anndata_elements_from_file() - self.extract_metadata_about_dataset() - - self.validate_anndata() - - def to_cxg(self, output_cxg_directory, sparse_threshold, convert_anndata_colors_to_cxg_colors=True): - """ - Writes the following attributes of the anndata to CXG: 1) the metadata as metadata attached to an empty - DenseArray, 2) the obs DataFrame as a DenseArray, 3) the var DataFrame as a DenseArray, 4) all valid - embeddings stored in obsm, each one as a DenseArray, 5) the main X matrix of the anndata as either a - SparseArray or DenseArray based on the `sparse_threshold`, and optionally 6) the column shift of the main X - matrix that might turn an otherwise Dense matrix into a Sparse matrix. - """ - - logging.info("Beginning writing to CXG.") - ctx = tiledb.Ctx( - { - "sm.num_reader_threads": 32, - "sm.num_writer_threads": 32, - "sm.consolidation.buffer_size": 1 * 1024 * 1024 * 1024, - } - ) - - tiledb.group_create(output_cxg_directory, ctx=ctx) - logging.info(f"\t...group created, with name {output_cxg_directory}") - - convert_dictionary_to_cxg_group( - output_cxg_directory, self.generate_cxg_metadata(convert_anndata_colors_to_cxg_colors) - ) - logging.info("\t...dataset metadata saved") - - convert_dataframe_to_cxg_array(output_cxg_directory, "obs", self.obs, self.obs_index_column_name, ctx) - logging.info("\t...dataset obs dataframe saved") - - convert_dataframe_to_cxg_array(output_cxg_directory, "var", self.var, self.var_index_column_name, ctx) - logging.info("\t...dataset var dataframe saved") - - self.write_anndata_embeddings_to_cxg(output_cxg_directory, ctx) - logging.info("\t...dataset embeddings saved") - - self.write_anndata_x_matrix_to_cxg(output_cxg_directory, ctx, sparse_threshold) - logging.info("\t...dataset X matrix saved") - - logging.info("Completed writing to CXG.") - - def write_anndata_x_matrix_to_cxg(self, output_cxg_directory, ctx, sparse_threshold): - matrix_container = f"{output_cxg_directory}/X" - - x_matrix_data = self.anndata.X - is_sparse = is_matrix_sparse(x_matrix_data, sparse_threshold) - if not is_sparse: - col_shift = get_column_shift_encode_for_matrix(x_matrix_data, sparse_threshold) - is_sparse = col_shift is not None - else: - col_shift = None - - if col_shift is not None: - logging.info("Converting matrix X as sparse matrix with column shift encoding") - x_col_shift_name = f"{output_cxg_directory}/X_col_shift" - convert_ndarray_to_cxg_dense_array(x_col_shift_name, col_shift, ctx) - - convert_matrix_to_cxg_array(matrix_container, x_matrix_data, is_sparse, ctx, col_shift) - - tiledb.consolidate(matrix_container, ctx=ctx) - if hasattr(tiledb, "vacuum"): - tiledb.vacuum(matrix_container) - - def write_anndata_embeddings_to_cxg(self, output_cxg_directory, ctx): - def is_valid_embedding(adata, embedding_name, embedding_array): - """ - Returns true if this layout data is a valid array for front-end presentation with the following criteria: - * ndarray, with shape (n_obs, >= 2), dtype float/int/uint - * follows ScanPy embedding naming conventions - * with all values finite or NaN (no +Inf or -Inf) - """ - - is_valid = isinstance(embedding_name, str) and embedding_name.startswith("X_") and len(embedding_name) > 2 - is_valid = is_valid and isinstance(embedding_array, np.ndarray) and embedding_array.dtype.kind in "fiu" - is_valid = is_valid and embedding_array.shape[0] == adata.n_obs and embedding_array.shape[1] >= 2 - is_valid = is_valid and not np.any(np.isinf(embedding_array)) and not np.all(np.isnan(embedding_array)) - return is_valid - - embedding_container = f"{output_cxg_directory}/emb" - tiledb.group_create(embedding_container, ctx=ctx) - - for embedding_name, embedding_values in self.anndata.obsm.items(): - if is_valid_embedding(self.anndata, embedding_name, embedding_values): - embedding_name = f"{embedding_container}/{embedding_name[2:]}" - convert_ndarray_to_cxg_dense_array(embedding_name, embedding_values, ctx) - logging.info(f"\t\t...{embedding_name} embedding created") - - def generate_cxg_metadata(self, convert_anndata_colors_to_cxg_colors): - """ - Return a dictionary containing metadata about CXG dataset. This include data about the version as well as - Corpora schema properties if they exist, among other pieces of metadata. - """ - - cxg_group_metadata = { - "cxg_version": CxgConstants.CXG_VERSION, - "cxg_properties": json.dumps({"title": self.dataset_title, "about": self.dataset_about}), - } - if self.corpora_properties is not None: - cxg_group_metadata["corpora"] = json.dumps(self.corpora_properties) - - if convert_anndata_colors_to_cxg_colors: - try: - cxg_group_metadata["cxg_category_colors"] = json.dumps( - convert_anndata_category_colors_to_cxg_category_colors(self.anndata) - ) - except ColorFormatException: - logging.warning( - "Failed to extract colors from H5AD file! Fix the H5AD file or rerun with " - "--disable-custom-colors. See help for more details." - ) - - return cxg_group_metadata - - def validate_input_file_type(self): - """ - Validate that the input file is of a type that we can handle. Currently the only valid file type is `.h5ad`. - """ - - if not self.input_filename.endswith(".h5ad"): - raise Exception(f"Cannot process input file {self.input_filename}. File must be an H5AD.") - - if self.dataset_title or self.dataset_about: - logging.warning( - "If you convert this dataset into CXG and you explicit specify values for the dataset title metadata " - "or the dataset about metadata, it will override any metadata that is extracted as part of the " - "Corpora schema fields." - ) - - def validate_anndata(self): - if not self.var.index.is_unique: - raise ValueError("Variable index in AnnData object is not unique.") - if not self.obs.index.is_unique: - raise ValueError("Observation index in AnnData object is not unique.") - - def extract_anndata_elements_from_file(self): - logging.info(f"Reading in AnnData dataset: {path.basename(self.input_filename)}") - self.anndata = anndata.read_h5ad(self.input_filename, backed="r" if self.backed else None) - logging.info("Completed reading in AnnData dataset!") - - self.obs = self.transform_dataframe_index_into_column(self.anndata.obs, "obs", self.obs_index_column_name) - self.var = self.transform_dataframe_index_into_column(self.anndata.var, "var", self.vars_index_column_name) - - def extract_metadata_about_dataset(self): - """ - Extract metadata information about the dataset that upon conversion will be saved as group metadata with the - CXG that is generated. This metadata information includes Corpora schema properties, the dataset title and - a link that details more information about the dataset. - """ - - self.corpora_properties = corpora_get_props_from_anndata(self.anndata) if self.use_corpora_schema else None - if self.corpora_properties is None and self.use_corpora_schema: - # If the return value is None, this means that we were not able to figure out what version of the Corpora - # schema the object is using and therefore cannot extract any properties. - raise ValueError("Unknown source file schema version is unsupported.") - - # The title and about properties of the dataset are set by the following order: if they are explicitly defined - # then use the explicit value. If the dataset is a Corpora-schema based schema, then extract the title and about - # from the corpora_properties. Otherwise, use the input filename (only for title, about will be blank). - if self.corpora_properties: - corpora_project_links = self.corpora_properties.get("project_links", []) - corpora_about_link = next( - (link for link in corpora_project_links if (link.get("link_type", None) == "SUMMARY")), {} - ) - else: - corpora_about_link = {} - - filename = path.splitext(path.basename(self.input_filename))[0] - - self.dataset_title = self.dataset_title if self.dataset_title else corpora_about_link.get("link_name", filename) - self.dataset_about = self.dataset_about if self.dataset_about else corpora_about_link.get("link_url") - - def transform_dataframe_index_into_column(self, dataframe, dataframe_name, index_column_name): - """ - Convert the dataframe's index into another column in the dataframe. If an index_column_name is specified, - use that column as the index instead. - """ - - if index_column_name is None: - # Create a unique column name for the index. - suffix = 0 - while f"name_{suffix}" in dataframe.columns: - suffix += 1 - index_column_name = f"name_{suffix}" - - # Turn the index into a normal column - dataframe.rename_axis(index_column_name, inplace=True) - dataframe.reset_index(inplace=True) - - elif index_column_name in dataframe.columns: - # User has specified alternative column for unique names, and it exists - if not dataframe[index_column_name].is_unique: - raise KeyError( - f"Values in {dataframe_name}.{index_column_name} must be unique. Please prepare data to contain " - f"unique values." - ) - else: - raise KeyError(f"Column {index_column_name} does not exist.") - - setattr(self, f"{dataframe_name}_index_column_name", index_column_name) - return dataframe diff --git a/backend/czi_hosted/converters/schema/__init__.py b/backend/czi_hosted/converters/schema/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/converters/schema/gene_symbol.py b/backend/czi_hosted/converters/schema/gene_symbol.py deleted file mode 100644 index 2d0de5a7..00000000 --- a/backend/czi_hosted/converters/schema/gene_symbol.py +++ /dev/null @@ -1,211 +0,0 @@ -"""Helpers for converting and checking HGNC gene symbols.""" - -import argparse -import enum -import logging -import os -import re -import numpy as np -import pandas as pd - - -def get_upgraded_var_index(var, hgnc_path=None): - """Given an anndata var dataframe, return a new index for the dataframe - where human gene symbols have been upgraded to the current HGNC set. - """ - - if not hgnc_path: - hgnc_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), "hgnc_complete_set.txt.gz") - - hgnc_symbol_checker = HGNCSymbolChecker.from_hgnc_records(hgnc_path) - - return pd.Index([hgnc_symbol_checker.upgrade_symbol(s) for s in var.index]) - - -class SymbolStatus(enum.Enum): - """The status of a symbol in the HGNC database. - - APPROVED: Currently a valid symbol - WITHDRAWN: A previously approved HGNC symbol for a gene that has since been shown - not to exist _unless_ that symbol is also approved - AMBIGUOUS: A symbol that is not approved but is an alias or previous symbol for - multiple approved symbols - UPGRADABLE: A symbol that is not approved but unambiguously maps to an approved - symbol - UNKNOWN: A symbol that does not appear in HGNC - """ - - APPROVED = 1 - WITHDRAWN = 2 - AMBIGUOUS = 3 - UPGRADABLE = 4 - UNKNOWN = 5 - - -class HGNCSymbolChecker: - """Handle checking and correcting HGNC symbols.""" - - def __init__(self, approved_symbols, withdrawn_symbols, ambiguous_symbols, symbol_map): - self.approved_symbols = approved_symbols - self.withdrawn_symbols = withdrawn_symbols - self.ambiguous_symbols = ambiguous_symbols - self.symbol_map = symbol_map - - def print_symbol_map(self): - """Print out a map from old symbol to new symbol.""" - - for symbol_pair in self.symbol_map.items(): - print("\t".join(symbol_pair)) - - def check_symbol(self, symbol): - """See if a symbol if approved or something else.""" - if symbol in self.approved_symbols: - return SymbolStatus.APPROVED - - if symbol in self.withdrawn_symbols: - return SymbolStatus.WITHDRAWN - - if symbol in self.ambiguous_symbols: - return SymbolStatus.AMBIGUOUS - - if symbol in self.symbol_map: - return SymbolStatus.UPGRADABLE - - return SymbolStatus.UNKNOWN - - def upgrade_symbol(self, symbol): - """Return the approved symbol for the given symbol. - - If the symbol cannot be upgraded, just return the original symbol. - """ - - fixed_symbol, stripped_symbol = format_symbol(symbol) - - if fixed_symbol in self.approved_symbols: - return fixed_symbol - elif fixed_symbol in self.symbol_map: - return self.symbol_map[fixed_symbol] - elif stripped_symbol in self.approved_symbols: - return stripped_symbol - elif stripped_symbol in self.symbol_map: - return self.symbol_map[stripped_symbol] - - return symbol - - @classmethod - def from_hgnc_records(cls, hgnc_dataset_path): - """Parse a hgnc database download into a HGNCSymbolChecker object.""" - - def all_symbols(record): - """Get all the symbols associated with an HGNC record including previous, alias, - and approved.""" - yield format_symbol(record["symbol"])[0] - for symbol in alias_and_previous_symbols(record): - yield symbol - - def alias_and_previous_symbols(record): - """Get alias and previous symbols from an HGNC record.""" - for field in ("alias_symbol", "prev_symbol"): - if record[field] is not np.nan: - for symbol in record[field].split("|"): - yield format_symbol(symbol)[0] - # Sometimes something like HGNC:1234 appears in datasets, which we - # want to fix as well. - yield record["hgnc_id"] - - hgnc_records = pd.read_csv(hgnc_dataset_path, sep="\t", header=0, low_memory=False).to_dict("records") - - # Get all symbols that are currently approved. - approved_symbols = set() - for record in hgnc_records: - if record["status"] == "Approved": - approved_symbols.add(format_symbol(record["symbol"])[0]) - - # Get all symbols that have been withdrawn - withdrawn_symbols = set() - for record in hgnc_records: - if record["status"] == "Entry Withdrawn": - for symbol in all_symbols(record): - withdrawn_symbols.add(symbol) - - # If a symbol is both approved and withdrawn, be optimistic and call it approved - logging.warning( - f"Some symbols are simulaneously withdrawn and approved\n" - f"We will treat them at approved:\n" - f"{withdrawn_symbols.intersection(approved_symbols)}" - ) - withdrawn_symbols = withdrawn_symbols.difference(approved_symbols) - - # Now try to map from symbols that are not approved but are an alias or previous symbol for an approved symbol - alias_previous_to_approved = {} - ambiguous_symbols = set() - - for record in hgnc_records: - if record["status"] == "Approved": - - # The approved symbol is what we'll map to - approved_symbol = format_symbol(record["symbol"])[0] - - for symbol in alias_and_previous_symbols(record): - - # If the alias or previous symbol is also an approved symbol, - # we'll just leave it alone - if symbol in approved_symbols: - continue - - # If the alias or previous symbol maps to a different approved symbol, mark it as ambiguous - if symbol in alias_previous_to_approved and alias_previous_to_approved[symbol] != approved_symbol: - ambiguous_symbols.add(symbol) - else: - alias_previous_to_approved[symbol] = approved_symbol - - # Remove all the ambiguous symbols from the map - for ambiguous_symbol in ambiguous_symbols: - alias_previous_to_approved.pop(ambiguous_symbol) - - return HGNCSymbolChecker(approved_symbols, withdrawn_symbols, ambiguous_symbols, alias_previous_to_approved) - - -def format_symbol(symbol): - """HGNC rules say symbols should all be upper case except for C#orf#. However, case is - variable in both alias and previous symbols as well as in the symbols we get in - submissions. So, upper case everything except for the one situation where mixed-case - is allowed, which are the genes like C2orf157. - - Also, seurat and scanpy append ".1" or "-1" to duplicated gene names, and these altered - names persist throughout the life of the object. They won't match against the HGNC database - and we want to merge them, so we need to strip off the suffix and try matching again. - - This function takes a symbol and returns the symbol with the fixed case and also with the - seurat/scanpy suffix stripped off. - """ - - match = re.match(r"^(C)(\d+)(orf)(\d+)$", symbol, re.IGNORECASE) - - if match: - fixed_case = f"C{match.group(2)}orf{match.group(4)}" - else: - fixed_case = symbol.upper() - - suffix_stripped = re.sub(r"[\.\-]\d+$", "", fixed_case) - - return fixed_case, suffix_stripped - - -def main(): - """When called as main, parse a given hgnc download and print out a map from old to new - symbol. - """ - parser = argparse.ArgumentParser() - parser.add_argument( - "hgnc_dataset", help="HGNC dataset tsv, available from www.genenames.org/download/statistics-and-files/" - ) - args = parser.parse_args() - - hgnc_symbol_checker = HGNCSymbolChecker.from_hgnc_records(args.hgnc_dataset) - - hgnc_symbol_checker.print_symbol_map() - - -if 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This is required by the OLS API.""" - return quote_plus(quote_plus(url)) - - -def _iri(curie): - """Get the iri from a curie. This is a bit hopeful that they all map to purl.obolibrary.org""" - if _ontology_name(curie) == "EFO": - return f"http://www.ebi.ac.uk/efo/EFO_{_ontology_value(curie)}" - return f"http://purl.obolibrary.org/obo/{_ontology_name(curie)}_{_ontology_value(curie)}" - - -class OntologyLookupError(Exception): - """Exception for some problem with looking up ontology information.""" - - -def _ontology_info_url(curie): - """Get the to make a GET to to get information about an ontology term.""" - - # If the curie is empty, just return an empty string. This happens when there is no - # valid ontology value. - if not curie: - return "" - else: - return f"{OLS_API_ROOT}/ontologies/{_ontology_name(curie)}/terms/{_double_encode(_iri(curie))}" - - -def get_ontology_label(curie): - """For a given curie like 'CL:1000413', get the label like 'endothelial cell of artery'""" - - url = _ontology_info_url(curie) - - if not url: - return "" - - response = requests.get(url) - - if not response.ok: - raise OntologyLookupError( - f"Curie {curie} lookup failed, got status code {response.status_code}: {response.text}" - ) - return response.json()["label"] - - -def lookup_candidate_term(label, ontology="cl", method="select"): - """Lookup candidate terms for a label. This is useful when there is an existing label in a - submitted dataset, and you want to find an appropriate ontology term. - - Args: - label: the label to find ontology terms for - ontology: the ontology to search in, cl or uberon or efo for example - method: select or search. search provides much broader results - - Returns: - list of (curie, label) tuples returned by OLS - """ - # using OLS REST API [https://www.ebi.ac.uk/ols/docs/api] - url = f"{OLS_API_ROOT}/{method}?q={quote_plus(label)}&ontology={ontology.lower()}" - response = requests.get(url) - - if not response.ok: - raise OntologyLookupError( - f"Label {label} lookup failed, got status code {response.status_code}: {response.text}" - ) - - return [(r["obo_id"], r["label"]) for r in response.json()["response"]["docs"]] diff --git a/backend/czi_hosted/converters/schema/remix.py b/backend/czi_hosted/converters/schema/remix.py deleted file mode 100644 index 5cc60746..00000000 --- a/backend/czi_hosted/converters/schema/remix.py +++ /dev/null @@ -1,264 +0,0 @@ -import argparse -import collections -import json -import logging -import math -import string - -import anndata -import numpy as np -import pandas as pd -import yaml - -from . import gene_symbol -from . import ontology -from . import validate - -REPLACE_SUFFIX = "_original" -ONTOLOGY_SUFFIX = "_ontology_term_id" - - -def is_curie(value): - """Return True iff the value is an OBO-id CURIE like EFO:000001""" - return (value.count(":") - and all(len(part) > 0 for part in value.split(":")) - and all(c in string.digits for c in value.split(":")[1])) - - -def is_ontology_field(field_name): - """Return True iff the field_name is an ontology field like tissue_ontology_term_id""" - return field_name.endswith(ONTOLOGY_SUFFIX) - - -def get_label_field_name(field_name): - """Get the associated label field from an ontology field, assay_ontology_term_id --> assay""" - return field_name[: -len(ONTOLOGY_SUFFIX)] - - -def split_suffix(maybe_curie): - """Split off the (cell culture) or (organoid) suffix.""" - - suffixes = [" (cell culture)", " (organoid)"] - for suffix in suffixes: - if maybe_curie.endswith(suffix): - return maybe_curie[:-len(suffix)], suffix - return maybe_curie, "" - - -def get_curie_and_label(maybe_curie): - """Given a string that might be a curie, return a (curie, label) pair""" - - maybe_curie, suffix = split_suffix(maybe_curie) - if not is_curie(maybe_curie): - return ("", maybe_curie + suffix) - return (maybe_curie + suffix, ontology.get_ontology_label(maybe_curie) + suffix) - - -def safe_add_field(adata_attr, field_name, field_value): - """Add a field and value to an AnnData, but don't clobber an exising value.""" - - if ( - isinstance(field_value, list) - and field_value - and isinstance(field_value[0], dict) - ): - field_value = json.dumps(field_value) - if field_name in adata_attr: - adata_attr[field_name + REPLACE_SUFFIX] = adata_attr[field_name] - adata_attr[field_name] = field_value - - -def remix_uns(adata, uns_config): - """Add fields from the config to adata.uns""" - for field_name, field_value in uns_config.items(): - - if is_ontology_field(field_name): - # If it's an ontology field, look it up - label_field_name = get_label_field_name(field_name) - ontology_term, ontology_label = get_curie_and_label(field_value) - safe_add_field(adata.uns, field_name, ontology_term) - safe_add_field(adata.uns, label_field_name, ontology_label) - else: - safe_add_field(adata.uns, field_name, field_value) - - -def remix_obs(adata, obs_config): - """Add fields from the config to adata.obs""" - - for field_name, field_value in obs_config.items(): - - if isinstance(field_value, dict): - # If the value is a dict, that means we are supposed to map from an - # existing column to the new one - source_column, column_map = next(iter(field_value.items())) - nan_value = None - for key in column_map: - if isinstance(key, float) and math.isnan(key): - nan_value = column_map[key] - if nan_value is not None: - column_map["nan"] = nan_value - - for key in column_map: - if key not in adata.obs[source_column].unique(): - logging.warning(f'Key {key} not in adata.obs["{source_column}"]') - - for value in adata.obs[source_column].unique(): - if value not in column_map: - logging.warning(f'Value {value} in adata.obs["{source_column}"] not in translation dict') - - if is_ontology_field(field_name): - ontology_term_map, ontology_label_map = {}, {} - logging.info(f"Looking up labels for {field_name}") - for original_value, maybe_curie in column_map.items(): - curie, label = get_curie_and_label(maybe_curie) - ontology_term_map[original_value] = curie - ontology_label_map[original_value] = label - logging.info(f"Mapping {original_value} -> {curie} -> {label}") - - ontology_column = adata.obs[source_column].replace( - ontology_term_map, inplace=False - ) - label_column = adata.obs[source_column].replace( - ontology_label_map, inplace=False - ) - - safe_add_field(adata.obs, field_name, ontology_column) - safe_add_field( - adata.obs, get_label_field_name(field_name), label_column - ) - else: - label_column = adata.obs[source_column].replace( - column_map, inplace=False - ) - safe_add_field(adata.obs, field_name, label_column) - - else: - if is_ontology_field(field_name): - # If it's an ontology field, look it up - label_field_name = get_label_field_name(field_name) - ontology_term, ontology_label = get_curie_and_label(field_value) - safe_add_field(adata.obs, field_name, ontology_term) - safe_add_field(adata.obs, label_field_name, ontology_label) - else: - safe_add_field(adata.obs, field_name, field_value) - - -def merge_df(df, domain, index, columns): - """ - Given a dataframe with duplicate column labels, merge and return a dataframe where - the duplicates have been merged together, resulting in a dataframe with unique column - labels. - - "merge" depends on the value of domain. If the domain is "raw", then duplicate columns - can just be summed. If it's "log1p" or "sqrt", it needs to be exp1m'd or squared, then - summed, and then logged or sqrt'd again. - """ - - if not isinstance(df, np.ndarray): - to_merge = df.toarray() - else: - to_merge = df - if domain == "raw": - merged_df = pd.DataFrame(to_merge, index=index, columns=columns).sum( - axis=1, level=0, skipna=False - ) - elif domain == "log1p": - merged_df = ( - pd.DataFrame(np.expm1(to_merge, dtype=np.float128), index=index, columns=columns) - .sum(axis=1, level=0, skipna=False) - ) - merged_df = pd.DataFrame(np.log1p(merged_df.to_numpy()), index=merged_df.index, columns=merged_df.columns) - elif domain == "sqrt": - merged_df = ( - pd.DataFrame(np.square(to_merge), index=index, columns=columns) - .sum(axis=1, level=0, skipna=False) - ) - merged_df = pd.DataFrame(np.sqrt(merged_df.to_numpy()), index=merged_df.index, columns=merged_df.columns) - - return merged_df - - -def fixup_gene_symbols(adata, fixup_config): - """Update the var index to hold a consistent set of HGNC gene symbols.""" - - upgraded_var_index = gene_symbol.get_upgraded_var_index(adata.var) - - merged_X = merge_df(adata.X, fixup_config["X"], adata.obs.index, upgraded_var_index) - fixup_adata = anndata.AnnData( - X=merged_X, - obs=adata.obs, - var=merged_X.columns.to_frame(name="hgnc_gene_symbol"), - uns=adata.uns, - obsm=adata.obsm, - ) - - for layer, domain in fixup_config.items(): - if layer == "X": - continue - if layer == "raw.X": - df = adata.raw.X - else: - df = adata.layers[layer] - - merged_df = merge_df(df, domain, adata.obs.index, upgraded_var_index) - assert merged_df.index.equals(merged_X.index) - assert merged_df.columns.equals(merged_X.columns) - - if domain == "raw": - fixup_raw = anndata.AnnData( - X=merged_df, - obs=adata.obs, - var=merged_X.columns.to_frame(name="hgnc_gene_symbol"), - ) - fixup_adata.raw = fixup_raw - else: - fixup_adata.layers[layer] = merged_df - - return fixup_adata - -def _strip_version(adata): - """Remove version information from the AnnData object.""" - - if "version" in adata.uns_keys(): - del adata.uns["version"] - -def apply_schema(source_h5ad, remix_config, output_filename): - - try: - import scanpy - except ImportError: - raise ImportError("scanpy must be installed for cellxgene schema") - adata = scanpy.read_h5ad(source_h5ad) - config = yaml.load(open(remix_config), Loader=yaml.FullLoader) - remix_uns(adata, config["uns"]) - remix_obs(adata, config["obs"]) - - if config.get("fixup_gene_symbols"): - adata = fixup_gene_symbols(adata, config["fixup_gene_symbols"]) - - if ("version" in adata.uns_keys() - and isinstance(adata.uns["version"], collections.Mapping) - and "corpora_schema_version" in adata.uns["version"]): - schema_version = adata.uns["version"]["corpora_schema_version"] - try: - validate.get_schema_definition(schema_version) - except ValueError: - logging.warning(f"Stripping version information out of AnnData because schema " - f"version {schema_version} is unknown.") - _strip_version(adata) - - if not validate.validate_adata(adata, shallow=False): - logging.warning(f"Stripping version information out of AnnData because it does not " - f"follow schema version {schema_version} .") - _strip_version(adata) - - adata.write_h5ad(output_filename, compression="gzip") - - -if __name__ == "__main__": - parser = argparse.ArgumentParser() - parser.add_argument("--source-h5ad", required=True) - parser.add_argument("--remix-config", required=True) - parser.add_argument("--output-filename", required=True) - args = parser.parse_args() - apply_schema(args.source_h5ad, args.remix_config, args.output_filename) diff --git a/backend/czi_hosted/converters/schema/schema_definitions/1_0_0.yaml b/backend/czi_hosted/converters/schema/schema_definitions/1_0_0.yaml deleted file mode 100644 index acff2238..00000000 --- a/backend/czi_hosted/converters/schema/schema_definitions/1_0_0.yaml +++ /dev/null @@ -1,95 +0,0 @@ -title: Corpora schema version 1.0.0 -type: anndata -components: - uns: - type: dict - keys: - version: - type: dict - keys: - corpora_schema_version: null - corpora_encoding_version: null - title: - type: string - contributors: - type: stringified list of dicts - layer_descriptions: - type: dict - keys: - X: null - organism: - type: string - nullable: false - organism_ontology_term_id: - type: curie - prefixes: - - NCBITaxon - var: - type: dataframe - index: - type: human-readable string - unique: true - obs: - type: dataframe - index: - unique: true - columns: - tissue: - type: human-readable string - nullable: false - tissue_ontology_term_id: - type: suffixed curie - nullable: true - prefixes: - - UBERON - assay: - type: human-readable string - nullable: false - assay_ontology_term_id: - type: curie - nullable: true - prefixes: - - EFO - disease: - type: human-readable string - nullable: false - disease_ontology_term_id: - type: curie - nullable: true - prefixes: - - MONDO - - PATO - cell_type: - type: human-readable string - nullable: false - cell_type_ontology_term_id: - type: curie - nullable: true - prefixes: - - CL - - UBERON - sex: - type: string - enum: - - male - - female - - mixed - - unknown - - other - ethnicity: - type: human-readable string - nullable: false - ethnicity_ontology_term_id: - type: curie - nullable: true - prefixes: - - HANCESTRO - development_stage: - type: human-readable string - nullable: false - development_stage_ontology_term_id: - type: curie - nullable: true - prefixes: - - HsapDv - - EFO diff --git a/backend/czi_hosted/converters/schema/schema_definitions/1_1_0.yaml b/backend/czi_hosted/converters/schema/schema_definitions/1_1_0.yaml deleted file mode 100644 index 7531c72e..00000000 --- a/backend/czi_hosted/converters/schema/schema_definitions/1_1_0.yaml +++ /dev/null @@ -1,93 +0,0 @@ -title: Corpora schema version 1.1.0 -type: anndata -components: - uns: - type: dict - keys: - version: - type: dict - keys: - corpora_schema_version: null - corpora_encoding_version: null - title: - type: string - layer_descriptions: - type: dict - keys: - X: null - organism: - type: string - nullable: false - organism_ontology_term_id: - type: curie - prefixes: - - NCBITaxon - var: - type: dataframe - index: - type: human-readable string - unique: true - obs: - type: dataframe - index: - unique: true - columns: - tissue: - type: human-readable string - nullable: false - tissue_ontology_term_id: - type: suffixed curie - nullable: true - prefixes: - - UBERON - assay: - type: human-readable string - nullable: false - assay_ontology_term_id: - type: curie - nullable: true - prefixes: - - EFO - disease: - type: human-readable string - nullable: false - disease_ontology_term_id: - type: curie - nullable: true - prefixes: - - MONDO - - PATO - cell_type: - type: human-readable string - nullable: false - cell_type_ontology_term_id: - type: curie - nullable: true - prefixes: - - CL - - UBERON - sex: - type: string - enum: - - male - - female - - mixed - - unknown - - other - ethnicity: - type: human-readable string - nullable: false - ethnicity_ontology_term_id: - type: curie - nullable: true - prefixes: - - HANCESTRO - development_stage: - type: human-readable string - nullable: false - development_stage_ontology_term_id: - type: curie - nullable: true - prefixes: - - HsapDv - - EFO diff --git a/backend/czi_hosted/converters/schema/validate.py b/backend/czi_hosted/converters/schema/validate.py deleted file mode 100644 index ec463dd5..00000000 --- a/backend/czi_hosted/converters/schema/validate.py +++ /dev/null @@ -1,236 +0,0 @@ -import json -import re -import os -import sys - -import pandas as pd -import yaml - - -def _is_null(v): - """Return True if v is null, for one of the multiple ways a "null" value shows up in an h5ad.""" - return pd.isnull(v) or (hasattr(v, "__len__") and len(v) == 0) - - -def _validate_stringified_list_of_dicts(s): - """Verify that a string can be parsed into a list. - - We have some types that are lists of dicts. Those cannot be stored directly in an h5ad, so we have to - json.dumps them. This verifies that we can load them back. - """ - - try: - list_ = json.loads(s) - if not isinstance(list_, list): - return False - for el in list_: - if not isinstance(el, dict): - return False - return True - except (json.JSONDecodeError, TypeError): - pass - return False - - -def _validate_human_readable_string(s): - """Verify that a string is human-readable. - - There are parts of the schema where a "human-readable" string is required. "Human-readable" is kind - of vague and subjective. I feel like I can read many strings. So here we just check for the main ways - that fails: someone puts in an ontology term id or and ensembl gene/transcript id. - - Returns False if s is not a string or is one of those bad string types. - """ - - return isinstance(s, str) and (not re.match(r"[A-Z]\w+:\d+", s)) and (not re.match(r"ENS[GT]\d+$", s)) - - -def _validate_curie(c, prefixes): - """Verify that a string is a valid compact URI, like EFO:000001. If prefixes is not empty, make sure the - prefix of the curies is in prefixes. - """ - - if not c: - return True - - match = re.match(r"([A-Z]\w+):\d+$", c) - - if prefixes: - return match and match.group(1) in prefixes - else: - return match - - -def _validate_suffixed_curie(c, prefixes): - """Verify that a string is a compact URI with an optional suffix like 'EFO:00001 (cell culture)'""" - - # Pull off the suffix - suffix = re.findall(r"\ \(.*\)$", c) - if suffix: - c = c[: -len(suffix[0])] - return _validate_curie(c, prefixes) - - -def _validate_column(column, column_name, df_name, schema_def): - """Given a schema definition and the column of a dataframe, verify that the column satifies - the schema. - """ - - errors = [] - - if schema_def.get("unique"): - if column.nunique() != len(column): - errors.append(f"Column {column_name} in dataframe {df_name} is not unique.") - - if "nullable" in schema_def and not schema_def["nullable"]: - if any(_is_null(v) for v in column): - errors.append(f"Column {column_name} in dataframe {df_name} contains empty values.") - - if schema_def.get("type") == "human-readable string": - non_readables = [v for v in column if not _validate_human_readable_string(v)] - if non_readables: - errors.append( - f"Column {column_name} in dataframe {df_name} contains non-human-readable " - f"values like {non_readables[0]}" - ) - - if schema_def.get("type") in ("curie", "suffixed curie"): - validation_func = _validate_curie if schema_def.get("type") == "curie" else _validate_suffixed_curie - non_valid_curies = [v for v in column if not validation_func(v, schema_def.get("prefixes"))] - if non_valid_curies: - errors.append( - f"Column {column_name} in dataframe {df_name} contains invalid ontology values like " - f"{non_valid_curies[0]}." - ) - if "prefixes" in schema_def: - errors[-1] += f" Values must be curies from one of these ontologies {schema_def['prefixes']}." - - if "enum" in schema_def: - bad_enums = [v for v in column if v not in schema_def["enum"]] - if bad_enums: - errors.append( - f"Column {column_name} in dataframe {df_name} contains unpermitted values like " - f"{bad_enums[0]}. Values must be one of {schema_def['enum']}." - ) - - return errors - - -def _validate_dict(dict_, dict_name, schema_def): - """Given a schema definition and dict, verify that the dict satifies the schema.""" - - errors = [] - - for key in schema_def.get("keys", []): - if key not in dict_: - errors.append(f"{dict_name} is missing key {key}.") - elif schema_def["keys"][key]: - if schema_def["keys"][key]["type"] == "stringified list of dicts": - if not _validate_stringified_list_of_dicts(dict_[key]): - errors.append( - f"Key {key} in {dict_name} should be a JSON-encoded list of dicts, but it is {dict_[key]}" - ) - elif schema_def["keys"][key]["type"] == "dict": - errors.extend(_validate_dict(dict_[key], key, schema_def["keys"][key])) - elif schema_def["keys"][key]["type"] == "curie": - if not _validate_curie(dict_[key], schema_def["keys"][key]["prefixes"]): - errors.append(f"Key {key} in {dict_name} contains invalid ontology value.") - if "nullable" in schema_def["keys"][key] and not schema_def["keys"][key]["nullable"]: - if _is_null(dict_[key]): - errors.append(f"Key {key} in dict {dict_name} is an empty value.") - - return errors - - -def _validate_dataframe(df, df_name, schema_def): - """Given a dataframe and schema definition, verify that the dataframe follows the schema.""" - - errors = [] - - if "index" in schema_def: - errors.extend(_validate_column(df.index, "index", df_name, schema_def["index"])) - - for column in schema_def.get("columns", []): - if column not in df.columns: - errors.append(f"Dataframe {df_name} is missing column {column}.") - else: - errors.extend(_validate_column(df[column], column, df_name, schema_def["columns"][column])) - - return errors - - -def get_schema_definition(version): - """Look up and read a schema definition based on a version number like "1.0.0".""" - - path = os.path.join( - os.path.dirname(os.path.realpath(__file__)), "schema_definitions", version.replace(".", "_") + ".yaml" - ) - - if not os.path.isfile(path): - raise ValueError(f"No definition for version {version} found.") - - return yaml.load(open(path), Loader=yaml.FullLoader) - - -def deep_check(adata, schema_def): - """Perform a "deep" check of the AnnData object using the schema definition. - - This checks all the columns and unstructured metadata rather than just the version. - - Returns a list of error messages. If that list is empty, the object passed validation. - """ - - errors = [] - - for component, component_def in schema_def["components"].items(): - if component_def["type"] == "dataframe": - errors.extend(_validate_dataframe(getattr(adata, component), component, component_def)) - elif component_def["type"] == "dict": - errors.extend(_validate_dict(getattr(adata, component), component, component_def)) - else: - raise ValueError(f"Unexpected component type {component['type']}") - - return errors - - -def validate_adata(adata, shallow): - """Validate an AnnData object. If shallow, just check that the required version information is - present. - """ - - # Does it have the version information written into uns? - if "version" not in adata.uns_keys() or "corpora_schema_version" not in adata.uns["version"]: - print("AnnData file is missing corpora version information") - return False - - # We can stop here if it's a "shallow" check, that is, if we're just - # checking that version is present. - if shallow: - return True - - schema_def = get_schema_definition(adata.uns["version"]["corpora_schema_version"]) - - errors = deep_check(adata, schema_def) - - for error in errors: - print(error) - - return not errors - - -def validate(h5ad_path, shallow=False): - """Entry point for validation.""" - - try: - import scanpy - except ImportError: - raise ImportError("scanpy must be installed for cellxgene schema") - - try: - adata = scanpy.read_h5ad(h5ad_path, backed="r") - except (OSError, TypeError): - print(f"Unable to open {h5ad_path} with scanpy.") - sys.exit(1) - - if not validate_adata(adata, shallow): - sys.exit(1) diff --git a/backend/czi_hosted/converters/to_sparse.py b/backend/czi_hosted/converters/to_sparse.py deleted file mode 100644 index daaa4c43..00000000 --- a/backend/czi_hosted/converters/to_sparse.py +++ /dev/null @@ -1,81 +0,0 @@ -""" -Script to create a sparse dataset in CXG format based on an input dataset in CXG format. -The input dataset is not modified. -""" -import argparse -import os -import shutil -import sys - -import tiledb - -from backend.czi_hosted.common.utils.cxg_generation_utils import convert_ndarray_to_cxg_dense_array, \ - convert_matrix_to_cxg_array -from backend.czi_hosted.common.utils.matrix_utils import is_matrix_sparse, get_column_shift_encode_for_matrix - - -def main(): - parser = argparse.ArgumentParser() - parser.add_argument("input", help="input cxg directory") - parser.add_argument("output", help="output cxg directory") - parser.add_argument("--overwrite", action="store_true", help="replace output cxg directory") - parser.add_argument("--verbose", "-v", action="count", default=0, help="verbose output") - parser.add_argument( - "--sparse-threshold", - "-s", - type=float, - default=5.0, # default is 5% non-zero values - help="The X array will be sparse if the percent of non-zeros falls below this value", - ) - args = parser.parse_args() - - if os.path.exists(args.output): - print("output dir exists:", args.output) - if args.overwrite: - print("output dir removed:", args.output) - shutil.rmtree(args.output) - else: - print("use the overwrite option to remove the output directory") - sys.exit(1) - - if not os.path.isdir(args.input): - print("input is not a directory", args.input) - sys.exit(1) - - shutil.copytree(args.input, args.output, ignore=shutil.ignore_patterns("X", "X_col_shift")) - - ctx = tiledb.Ctx( - { - "sm.num_reader_threads": 32, - "sm.num_writer_threads": 32, - "sm.consolidation.buffer_size": 1 * 1024 * 1024 * 1024, - } - ) - - with tiledb.DenseArray(os.path.join(args.input, "X"), mode="r", ctx=ctx) as X_in: - x_matrix_data = X_in[:, :] - matrix_container = args.output - - is_sparse = is_matrix_sparse(x_matrix_data, args.sparse_threshold) - if not is_sparse: - col_shift = get_column_shift_encode_for_matrix(x_matrix_data, args.sparse_threshold) - is_sparse = col_shift is not None - else: - col_shift = None - - if col_shift is not None: - x_col_shift_name = f"{args.output}/X_col_shift" - convert_ndarray_to_cxg_dense_array(x_col_shift_name, col_shift, ctx) - tiledb.consolidate(matrix_container, ctx=ctx) - if is_sparse: - convert_matrix_to_cxg_array(matrix_container, x_matrix_data, is_sparse, ctx, col_shift) - tiledb.consolidate(matrix_container, ctx=ctx) - - if not is_sparse: - print("The array is not sparse, cleaning up, abort.") - shutil.rmtree(args.output) - sys.exit(1) - - -if __name__ == "__main__": - main() diff --git a/backend/czi_hosted/data_anndata/__init__.py b/backend/czi_hosted/data_anndata/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/data_anndata/anndata_adaptor.py b/backend/czi_hosted/data_anndata/anndata_adaptor.py deleted file mode 100644 index 8badd8de..00000000 --- a/backend/czi_hosted/data_anndata/anndata_adaptor.py +++ /dev/null @@ -1,362 +0,0 @@ -import warnings - -import anndata -import numpy as np -from packaging import version -from pandas.core.dtypes.dtypes import CategoricalDtype -from scipy import sparse - -import backend.common.compute.diffexp_generic as diffexp_generic -from backend.common.colors import convert_anndata_category_colors_to_cxg_category_colors -from backend.common.constants import Axis, MAX_LAYOUTS, XApproximateDistribution -from backend.czi_hosted.common.corpora import corpora_get_props_from_anndata -from backend.common.errors import PrepareError, DatasetAccessError, ConfigurationError -from backend.common.utils.type_conversion_utils import get_schema_type_hint_of_array -from backend.czi_hosted.data_common.data_adaptor import DataAdaptor -from backend.common.fbs.matrix import encode_matrix_fbs - -anndata_version = version.parse(str(anndata.__version__)).release - - -def anndata_version_is_pre_070(): - major = anndata_version[0] - minor = anndata_version[1] if len(anndata_version) > 1 else 0 - return major == 0 and minor < 7 - - -class AnndataAdaptor(DataAdaptor): - def __init__(self, data_locator, app_config=None, dataset_config=None): - super().__init__(data_locator, app_config, dataset_config) - self.data = None - self.X_approximate_distribution = None - self._load_data(data_locator) - self._validate_and_initialize() - - def cleanup(self): - pass - - @staticmethod - def pre_load_validation(data_locator): - if data_locator.islocal(): - # if data locator is local, apply file system conventions and other "cheap" - # validation checks. If a URI, defer until we actually fetch the data and - # try to read it. Many of these tests don't make sense for URIs (eg, extension- - # based typing). - if not data_locator.exists(): - raise DatasetAccessError("does not exist") - if not data_locator.isfile(): - raise DatasetAccessError("is not a file") - - @staticmethod - def file_size(data_locator): - return data_locator.size() if data_locator.islocal() else 0 - - @staticmethod - def open(data_locator, app_config, dataset_config=None): - return AnndataAdaptor(data_locator, app_config, dataset_config) - - def get_corpora_props(self): - return corpora_get_props_from_anndata(self.data) - - def get_name(self): - return "cellxgene anndata adaptor version" - - def get_library_versions(self): - return dict(anndata=str(anndata.__version__)) - - @staticmethod - def _create_unique_column_name(df, col_name_prefix): - """given the columns of a dataframe, and a name prefix, return a column name which - does not exist in the dataframe, AND which is prefixed by `prefix` - - The approach is to append a numeric suffix, starting at zero and increasing by - one, until an unused name is found (eg, prefix_0, prefix_1, ...). - """ - suffix = 0 - while f"{col_name_prefix}{suffix}" in df: - suffix += 1 - return f"{col_name_prefix}{suffix}" - - def _alias_annotation_names(self): - """ - The front-end relies on the existance of a unique, human-readable - index for obs & var (eg, var is typically gene name, obs the cell name). - The user can specify these via the --obs-names and --var-names config. - If they are not specified, use the existing index to create them, giving - the resulting column a unique name (eg, "name"). - - In both cases, enforce that the result is unique, and communicate the - index column name to the front-end via the obs_names and var_names config - (which is incorporated into the schema). - """ - self.original_obs_index = self.data.obs.index - - for (ax_name, var_name) in ((Axis.OBS, "obs"), (Axis.VAR, "var")): - config_name = f"single_dataset__{var_name}_names" - parameter_name = f"{var_name}_names" - name = getattr(self.server_config, config_name) - df_axis = getattr(self.data, str(ax_name)) - if name is None: - # Default: create unique names from index - if not df_axis.index.is_unique: - raise KeyError( - f"Values in {ax_name}.index must be unique. " - "Please prepare data to contain unique index values, or specify an " - "alternative with --{ax_name}-name." - ) - name = self._create_unique_column_name(df_axis.columns, "name_") - self.parameters[parameter_name] = name - # reset index to simple range; alias name to point at the - # previously specified index. - df_axis.rename_axis(name, inplace=True) - df_axis.reset_index(inplace=True) - elif name in df_axis.columns: - # User has specified alternative column for unique names, and it exists - if not df_axis[name].is_unique: - raise KeyError( - f"Values in {ax_name}.{name} must be unique. " "Please prepare data to contain unique values." - ) - df_axis.reset_index(drop=True, inplace=True) - self.parameters[parameter_name] = name - else: - # user specified a non-existent column name - raise KeyError(f"Annotation name {name}, specified in --{ax_name}-name does not exist.") - - def _create_schema(self): - self.schema = { - "dataframe": { - "nObs": self.cell_count, - "nVar": self.gene_count, - **get_schema_type_hint_of_array(self.data.X), - }, - "annotations": { - "obs": {"index": self.parameters.get("obs_names"), "columns": []}, - "var": {"index": self.parameters.get("var_names"), "columns": []}, - }, - "layout": {"obs": []}, - } - for ax in Axis: - curr_axis = getattr(self.data, str(ax)) - for ann in curr_axis: - ann_schema = {"name": ann, "writable": False} - ann_schema.update(get_schema_type_hint_of_array(curr_axis[ann])) - self.schema["annotations"][ax]["columns"].append(ann_schema) - - for layout in self.get_embedding_names(): - layout_schema = {"name": layout, "type": "float32", "dims": [f"{layout}_0", f"{layout}_1"]} - self.schema["layout"]["obs"].append(layout_schema) - - def get_schema(self): - return self.schema - - def _load_data(self, data_locator): - # as of AnnData 0.6.19, backed mode performs initial load fast, but at the - # cost of significantly slower access to X data. - try: - # there is no guarantee data_locator indicates a local file. The AnnData - # API will only consume local file objects. If we get a non-local object, - # make a copy in tmp, and delete it after we load into memory. - with data_locator.local_handle() as lh: - # as of AnnData 0.6.19, backed mode performs initial load fast, but at the - # cost of significantly slower access to X data. - backed = "r" if self.server_config.adaptor__anndata_adaptor__backed else None - self.data = anndata.read_h5ad(lh, backed=backed) - - except ValueError: - raise DatasetAccessError( - "File must be in the .h5ad format. Please read " - "https://github.com/theislab/scanpy_usage/blob/master/170505_seurat/info_h5ad.md to " - "learn more about this format. You may be able to convert your file into this format " - "using `cellxgene prepare`, please run `cellxgene prepare --help` for more " - "information." - ) - except MemoryError: - raise DatasetAccessError("Out of memory - file is too large for available memory.") - except Exception: - raise DatasetAccessError( - "File not found or is inaccessible. File must be an .h5ad object. " - "Please check your input and try again." - ) - - def _validate_and_initialize(self): - if anndata_version_is_pre_070(): - warnings.warn( - "Use of anndata versions older than 0.7 will have serious issues. Please update to at " - "least anndata 0.7 or later." - ) - - # var and obs column names must be unique - if not self.data.obs.columns.is_unique or not self.data.var.columns.is_unique: - raise KeyError("All annotation column names must be unique.") - - self._alias_annotation_names() - self._validate_data_types() - self.cell_count = self.data.shape[0] - self.gene_count = self.data.shape[1] - self._create_schema() - - if self.dataset_config.X_approximate_distribution == "auto": - raise ConfigurationError("X-approximate-distribution 'auto' mode unsupported.") - self.X_approximate_distribution = self.dataset_config.X_approximate_distribution - - # heuristic - n_values = self.data.shape[0] * self.data.shape[1] - if (n_values > 1e8 and self.server_config.adaptor__anndata_adaptor__backed is True) or (n_values > 5e8): - self.parameters.update({"diffexp_may_be_slow": True}) - - def _is_valid_layout(self, arr): - """return True if this layout data is a valid array for front-end presentation: - * ndarray, dtype float/int/uint - * with shape (n_obs, >= 2) - * with all values finite or NaN (no +Inf or -Inf) - """ - is_valid = type(arr) == np.ndarray and arr.dtype.kind in "fiu" - is_valid = is_valid and arr.shape[0] == self.data.n_obs and arr.shape[1] >= 2 - is_valid = is_valid and not np.any(np.isinf(arr)) and not np.all(np.isnan(arr)) - return is_valid - - def _validate_data_types(self): - # The backed API does not support interrogation of the underlying sparsity or sparse matrix type - # Fake it by asking for a small subarray and testing it. NOTE: if the user has ignored our - # anndata <= 0.7 warning, opted for the --backed option, and specified a large, sparse dataset, - # this "small" indexing request will load the entire X array. This is due to a bug in anndata<=0.7 - # which will load the entire X matrix to fullfill any slicing request if X is sparse. See - # user warning in _load_data(). - X0 = self.data.X[0, 0:1] - if sparse.isspmatrix(X0) and not sparse.isspmatrix_csc(X0): - warnings.warn( - "Anndata data matrix is sparse, but not a CSC (columnar) matrix. " - "Performance may be improved by using CSC." - ) - if self.data.X.dtype != "float32": - warnings.warn( - f"Anndata data matrix is in {self.data.X.dtype} format not float32. " f"Precision may be truncated." - ) - for ax in Axis: - curr_axis = getattr(self.data, str(ax)) - for ann in curr_axis: - datatype = curr_axis[ann].dtype - downcast_map = { - "int64": "int32", - "uint32": "int32", - "uint64": "int32", - "float64": "float32", - } - if datatype in downcast_map: - warnings.warn( - f"Anndata annotation {ax}:{ann} is in unsupported format: {datatype}. " - f"Data will be downcast to {downcast_map[datatype]}." - ) - if isinstance(datatype, CategoricalDtype): - category_num = len(curr_axis[ann].dtype.categories) - if category_num > 500 and category_num > self.dataset_config.presentation__max_categories: - warnings.warn( - f"{str(ax).title()} annotation '{ann}' has {category_num} categories, this may be " - f"cumbersome or slow to display. We recommend setting the " - f"--max-category-items option to 500, this will hide categorical " - f"annotations with more than 500 categories in the UI" - ) - - def annotation_to_fbs_matrix(self, axis, fields=None, labels=None): - if axis == Axis.OBS: - if labels is not None and not labels.empty: - df = self.data.obs.join(labels, self.parameters.get("obs_names")) - else: - df = self.data.obs - else: - df = self.data.var - - if fields is not None and len(fields) > 0: - df = df[fields] - return encode_matrix_fbs(df, col_idx=df.columns) - - def get_embedding_names(self): - """ - Return pre-computed embeddings. - - function: - a) generate list of default layouts - b) validate layouts are legal. remove/warn on any that are not - c) cap total list of layouts at global const MAX_LAYOUTS - """ - # load default layouts from the data. - layouts = self.dataset_config.embeddings__names - - if layouts is None or len(layouts) == 0: - layouts = [key[2:] for key in self.data.obsm_keys() if type(key) == str and key.startswith("X_")] - - # remove invalid layouts - valid_layouts = [] - obsm_keys = self.data.obsm_keys() - for layout in layouts: - layout_name = f"X_{layout}" - if layout_name not in obsm_keys: - warnings.warn(f"Ignoring unknown layout name: {layout}.") - elif not self._is_valid_layout(self.data.obsm[layout_name]): - warnings.warn(f"Ignoring layout due to malformed shape or data type: {layout}") - else: - valid_layouts.append(layout) - - if len(valid_layouts) == 0: - raise PrepareError("No valid layout data.") - - # cap layouts to MAX_LAYOUTS - return valid_layouts[0:MAX_LAYOUTS] - - def get_embedding_array(self, ename, dims=2): - full_embedding = self.data.obsm[f"X_{ename}"] - return full_embedding[:, 0:dims] - - def compute_diffexp_ttest(self, maskA, maskB, top_n=None, lfc_cutoff=None): - if top_n is None: - top_n = self.dataset_config.diffexp__top_n - if lfc_cutoff is None: - lfc_cutoff = self.dataset_config.diffexp__lfc_cutoff - return diffexp_generic.diffexp_ttest(self, maskA, maskB, top_n, lfc_cutoff) - - def get_colors(self): - return convert_anndata_category_colors_to_cxg_category_colors(self.data) - - def get_X_array(self, obs_mask=None, var_mask=None): - # H5Py does not support boolean indexing (masks), so convert to integer indexing - # when backed (ie, when AnnData is using H5Py indexing) - if obs_mask is None: - obs_mask = slice(None) - elif self.data.isbacked and obs_mask.dtype == bool: - obs_mask = obs_mask.nonzero()[0] - if var_mask is None: - var_mask = slice(None) - elif self.data.isbacked and var_mask.dtype == bool: - var_mask = var_mask.nonzero()[0] - X = self.data.X[obs_mask, var_mask] - return X - - def get_X_approximate_distribution(self) -> XApproximateDistribution: - return self.X_approximate_distribution - - def get_shape(self): - return self.data.shape - - def query_var_array(self, term_name): - return getattr(self.data.var, term_name) - - def query_obs_array(self, term_name): - return getattr(self.data.obs, term_name) - - def get_obs_index(self): - name = self.server_config.single_dataset__obs_names - if name is None: - return self.original_obs_index - else: - return self.data.obs[name] - - def get_obs_columns(self): - return self.data.obs.columns - - def get_obs_keys(self): - # return list of keys - return self.data.obs.keys().to_list() - - def get_var_keys(self): - # return list of keys - return self.data.var.keys().to_list() diff --git a/backend/czi_hosted/data_common/__init__.py b/backend/czi_hosted/data_common/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/data_common/data_adaptor.py b/backend/czi_hosted/data_common/data_adaptor.py deleted file mode 100644 index 3bbdc6b1..00000000 --- a/backend/czi_hosted/data_common/data_adaptor.py +++ /dev/null @@ -1,428 +0,0 @@ -from abc import ABCMeta, abstractmethod -from os.path import basename, splitext - -import numpy as np -import pandas as pd -from scipy import sparse -from server_timing import Timing as ServerTiming - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.constants import Axis, XApproximateDistribution -from backend.common.errors import ( - FilterError, - JSONEncodingValueError, - ExceedsLimitError, - UnsupportedSummaryMethod, - DatasetAccessError, -) -from backend.common.utils.utils import jsonify_strict -from backend.common.fbs.matrix import encode_matrix_fbs - - -class DataAdaptor(metaclass=ABCMeta): - """Base class for loading and accessing matrix data""" - - def __init__(self, data_locator, app_config, dataset_config=None): - if type(app_config) != AppConfig: - raise TypeError("config expected to be of type AppConfig") - - # location to the dataset - self.data_locator = data_locator - - # config is the application configuration - self.app_config = app_config - self.server_config = self.app_config.server_config - self.dataset_config = dataset_config or app_config.default_dataset_config - - # parameters set by this data adaptor based on the data. - self.parameters = {} - self.uri_path = None - - def set_uri_path(self, path): - # uri path to the dataset, e.g. /d/ - self.uri_path = path - - @staticmethod - @abstractmethod - def pre_load_validation(data_locator): - pass - - @staticmethod - @abstractmethod - def open(data_locator, app_config, dataset_config): - pass - - @staticmethod - @abstractmethod - def file_size(data_locator): - pass - - @abstractmethod - def get_name(self): - """return a string name for this data adaptor""" - pass - - @abstractmethod - def get_library_versions(self): - """return a dictionary of library name to library versions""" - pass - - @abstractmethod - def get_embedding_names(self): - """return a list of pre-computed embedding names""" - pass - - @abstractmethod - def get_embedding_array(self, ename, dims=2): - """return an numpy array for the given pre-computed embedding name.""" - pass - - @abstractmethod - def get_X_array(self, obs_mask=None, var_mask=None): - """return the X array, possibly filtered by obs_mask or var_mask. - the return type is either ndarray or scipy.sparse.spmatrix.""" - pass - - @abstractmethod - def get_X_approximate_distribution(self) -> XApproximateDistribution: - """return the approximate distribution of the X matrix.""" - pass - - @abstractmethod - def get_shape(self): - pass - - @abstractmethod - def query_var_array(self, term_var): - pass - - @abstractmethod - def query_obs_array(self, term_var): - pass - - @abstractmethod - def get_colors(self): - pass - - @abstractmethod - def get_obs_index(self): - pass - - @abstractmethod - def get_obs_columns(self): - pass - - @abstractmethod - def get_obs_keys(self): - # return list of keys - pass - - @abstractmethod - def get_var_keys(self): - # return list of keys - pass - - @abstractmethod - def cleanup(self): - pass - - def get_data_locator(self): - return self.data_locator - - def get_location(self): - return self.data_locator.uri_or_path - - def get_about(self): - return None - - def get_title(self): - # default to file name - location = self.get_location() - if location.endswith("/"): - location = location[:-1] - return splitext(basename(location))[0] - - def get_corpora_props(self): - return None - - @abstractmethod - def get_schema(self): - """ - Return current schema - """ - pass - - @abstractmethod - def annotation_to_fbs_matrix(self, axis, field=None, uid=None): - """ - Gets annotation value for each observation - :param axis: string obs or var - :param fields: list of keys for annotation to return, returns all annotation values if not set. - :return: flatbuffer: in fbs/matrix.fbs encoding - """ - pass - - def update_parameters(self, parameters): - parameters.update(self.parameters) - - def _index_filter_to_mask(self, filter, count): - mask = np.zeros((count,), dtype=np.bool) - for i in filter: - if type(i) == list: - mask[i[0] : i[1]] = True - else: - mask[i] = True - return mask - - def _axis_filter_to_mask(self, axis, filter, count): - mask = np.ones((count,), dtype=np.bool) - if "index" in filter: - mask = np.logical_and(mask, self._index_filter_to_mask(filter["index"], count)) - if "annotation_value" in filter: - mask = np.logical_and(mask, self._annotation_filter_to_mask(axis, filter["annotation_value"], count)) - - return mask - - def _annotation_filter_to_mask(self, axis, filter, count): - mask = np.ones((count,), dtype=np.bool) - for v in filter: - name = v["name"] - if axis == Axis.VAR: - anno_data = self.query_var_array(name) - elif axis == Axis.OBS: - anno_data = self.query_obs_array(name) - - if anno_data.dtype.name in ["boolean", "category", "object"]: - values = v.get("values", []) - key_idx = np.in1d(anno_data, values) - mask = np.logical_and(mask, key_idx) - - else: - min_ = v.get("min", None) - max_ = v.get("max", None) - if min_ is not None: - key_idx = (anno_data >= min_).ravel() - mask = np.logical_and(mask, key_idx) - if max_ is not None: - key_idx = (anno_data <= max_).ravel() - mask = np.logical_and(mask, key_idx) - - return mask - - def _filter_to_mask(self, filter): - """ - Return the filter as a row and column selection list. - No filter on a dimension means 'all' - """ - shape = self.get_shape() - var_selector = None - obs_selector = None - if filter is not None: - if Axis.OBS in filter: - obs_selector = self._axis_filter_to_mask(Axis.OBS, filter["obs"], shape[0]) - - if Axis.VAR in filter: - var_selector = self._axis_filter_to_mask(Axis.VAR, filter["var"], shape[1]) - - return (obs_selector, var_selector) - - def check_new_labels(self, labels_df): - """Check the new annotations labels, then set the labels_df index""" - if labels_df is None or labels_df.empty: - return - - labels_df.index = self.get_obs_index() - if labels_df.index.name is None: - labels_df.index.name = "index" - - # all labels must have a name, which must be unique and not used in obs column names - if not labels_df.columns.is_unique: - raise KeyError("All column names specified in user annotations must be unique.") - - # the label index must be unique, and must have same values the anndata obs index - if not labels_df.index.is_unique: - raise KeyError("All row index values specified in user annotations must be unique.") - - obs_columns = self.get_obs_columns() - - duplicate_columns = list(set(labels_df.columns) & set(obs_columns)) - if len(duplicate_columns) > 0: - raise KeyError( - "Labels file may not contain column names which overlap " f"with h5ad obs columns {duplicate_columns}" - ) - - # labels must have same count as obs annotations - shape = self.get_shape() - if labels_df.shape[0] != shape[0]: - raise ValueError("Labels file must have same number of rows as data file.") - - # This will convert a float column that contains integer data into an integer type. - # This case can occur when a user makes a copy of a category that originally contained integer data. - # The client always copies array data to floats, therefore the copy will contain floats instead of integers. - # float data is not allowed as a categorical type. - if any([np.issubdtype(coltype.type, np.floating) for coltype in labels_df.dtypes]): - labels_df = labels_df.convert_dtypes() - for col, dtype in zip(labels_df, labels_df.dtypes): - if isinstance(dtype, pd.Int32Dtype): - labels_df[col] = labels_df[col].astype("int32") - if isinstance(dtype, pd.Int64Dtype): - labels_df[col] = labels_df[col].astype("int64") - - if any([np.issubdtype(coltype.type, np.floating) for coltype in labels_df.dtypes]): - raise ValueError("Columns may not have floating point types") - - return labels_df - - def data_frame_to_fbs_matrix(self, filter, axis): - """ - Retrieves data 'X' and returns in a flatbuffer Matrix. - :param filter: filter: dictionary with filter params - :param axis: string obs or var - :return: flatbuffer Matrix - - Caveats: - * currently only supports access on VAR axis - * currently only supports filtering on VAR axis - """ - if axis != Axis.VAR: - raise ValueError("Only VAR dimension access is supported") - - try: - obs_selector, var_selector = self._filter_to_mask(filter) - except (KeyError, IndexError, TypeError, AttributeError, DatasetAccessError): - raise FilterError("Error parsing filter") - - if obs_selector is not None: - raise FilterError("filtering on obs unsupported") - - num_columns = self.get_shape()[1] if var_selector is None else np.count_nonzero(var_selector) - if self.server_config.exceeds_limit("column_request_max", num_columns): - raise ExceedsLimitError("Requested dataframe columns exceed column request limit") - - X = self.get_X_array(obs_selector, var_selector) - col_idx = np.nonzero([] if var_selector is None else var_selector)[0] - return encode_matrix_fbs(X, col_idx=col_idx, row_idx=None) - - def diffexp_topN(self, obsFilterA, obsFilterB, top_n=None): - """ - Computes the top N differentially expressed variables between two observation sets. If mode - is "TOP_N", then stats for the top N - dataframes - contain a subset of variables, then statistics for all variables will be returned, otherwise - only the top N vars will be returned. - :param obsFilterA: filter: dictionary with filter params for first set of observations - :param obsFilterB: filter: dictionary with filter params for second set of observations - :param top_n: Limit results to top N (Top var mode only) - :return: top N genes and corresponding stats - """ - if Axis.VAR in obsFilterA or Axis.VAR in obsFilterB: - raise FilterError("Observation filters may not contain variable conditions") - try: - shape = self.get_shape() - obs_mask_A = self._axis_filter_to_mask(Axis.OBS, obsFilterA["obs"], shape[0]) - obs_mask_B = self._axis_filter_to_mask(Axis.OBS, obsFilterB["obs"], shape[0]) - except (KeyError, IndexError): - raise FilterError("Error parsing filter") - if top_n is None: - top_n = self.dataset_config.diffexp__top_n - - if self.server_config.exceeds_limit( - "diffexp_cellcount_max", np.count_nonzero(obs_mask_A) + np.count_nonzero(obs_mask_B) - ): - raise ExceedsLimitError("Diffexp request exceeds max cell count limit") - - result = self.compute_diffexp_ttest( - maskA=obs_mask_A, maskB=obs_mask_B, top_n=top_n, lfc_cutoff=self.dataset_config.diffexp__lfc_cutoff - ) - - try: - return jsonify_strict(result) - except ValueError: - raise JSONEncodingValueError("Error encoding differential expression to JSON") - - @abstractmethod - def compute_diffexp_ttest(self, maskA, maskB, top_n, lfc_cutoff): - pass - - @staticmethod - def normalize_embedding(embedding): - """Normalize embedding layout to meet client assumptions. - Embedding is an ndarray, shape (n_obs, n)., where n is normally 2 - """ - - # scale isotropically - try: - min = np.nanmin(embedding, axis=0) - max = np.nanmax(embedding, axis=0) - except RuntimeError: - # indicates entire array was NaN, which should propagate - min = np.NaN - max = np.NaN - - scale = np.amax(max - min) - normalized_layout = (embedding - min) / scale - - # translate to center on both axis - translate = 0.5 - ((max - min) / scale / 2) - normalized_layout = normalized_layout + translate - - normalized_layout = normalized_layout.astype(dtype=np.float32) - return normalized_layout - - def layout_to_fbs_matrix(self, fields): - """ - return specified embeddings as a flatbuffer, using the cellxgene matrix fbs encoding. - - * returns only first two dimensions, with name {ename}_0 and {ename}_1, - where {ename} is the embedding name. - * client assumes each will be individually centered & scaled (isotropically) - to a [0, 1] range. - * does not support filtering - - """ - embeddings = self.get_embedding_names() if fields is None or len(fields) == 0 else fields - layout_data = [] - with ServerTiming.time("layout.query"): - for ename in embeddings: - embedding = self.get_embedding_array(ename, 2) - normalized_layout = DataAdaptor.normalize_embedding(embedding) - layout_data.append(pd.DataFrame(normalized_layout, columns=[f"{ename}_0", f"{ename}_1"])) - - with ServerTiming.time("layout.encode"): - if layout_data: - df = pd.concat(layout_data, axis=1, copy=False) - else: - df = pd.DataFrame() - fbs = encode_matrix_fbs(df, col_idx=df.columns, row_idx=None) - - return fbs - - def get_last_mod_time(self): - try: - lastmod = self.get_data_locator().lastmodtime() - except RuntimeError: - lastmod = None - return lastmod - - def summarize_var(self, method, filter, query_hash): - if method != "mean": - raise UnsupportedSummaryMethod("Unknown gene set summary method.") - - obs_selector, var_selector = self._filter_to_mask(filter) - if obs_selector is not None: - raise FilterError("filtering on obs unsupported") - - # if no filter, just return zeros. We don't have a use case - # for summarizing the entire X without a filter, and it would - # potentially be quite compute / memory intensive. - if var_selector is None or np.count_nonzero(var_selector) == 0: - mean = np.zeros((self.get_shape()[0], 1), dtype=np.float32) - else: - X = self.get_X_array(obs_selector, var_selector) - if sparse.issparse(X): - mean = X.mean(axis=1).A - else: - mean = X.mean(axis=1, keepdims=True) - - col_idx = pd.Index([query_hash]) - return encode_matrix_fbs(mean, col_idx=col_idx, row_idx=None) diff --git a/backend/czi_hosted/data_common/matrix_loader.py b/backend/czi_hosted/data_common/matrix_loader.py deleted file mode 100644 index 53fd44b4..00000000 --- a/backend/czi_hosted/data_common/matrix_loader.py +++ /dev/null @@ -1,288 +0,0 @@ -from enum import Enum -import threading -import time - -from backend.common.utils.data_locator import DataLocator -from backend.common.errors import DatasetAccessError -from contextlib import contextmanager -from http import HTTPStatus - -from backend.czi_hosted.data_common.rwlock import RWLock - - -class MatrixDataCacheItem(object): - """This class provides access and caching for a dataset. The first time a dataset is accessed, it is - opened and cached. Later accesses use the cached version. It may also be deleted by the - MatrixDataCacheManager to make room for another dataset. While a dataset is actively being used - (during the lifetime of a api request), a reader lock is locked. During that time, the dataset cannot - be removed.""" - - def __init__(self, loader): - self.loader = loader - self.data_adaptor = None - self.data_lock = RWLock() - - def acquire_existing(self): - """If the data_adaptor exists, take a read lock and return it, else return None""" - self.data_lock.r_acquire() - if self.data_adaptor: - return self.data_adaptor - - self.data_lock.r_release() - return None - - def acquire_and_open(self, app_config, dataset_config=None): - """returns the data_adaptor if cached. opens the data_adaptor if not. - In either case, the a reader lock is taken. Must call release when - the data_adaptor is no longer needed""" - self.data_lock.r_acquire() - if self.data_adaptor: - return self.data_adaptor - self.data_lock.r_release() - - self.data_lock.w_acquire() - # the data may have been loaded while waiting on the lock - if not self.data_adaptor: - try: - self.loader.pre_load_validation() - self.data_adaptor = self.loader.open(app_config, dataset_config) - except Exception as e: - # necessary to hold the reader lock after an exception, since - # the release will occur when the context exits. - self.data_lock.w_demote() - raise DatasetAccessError(str(e)) - - # demote the write lock to a read lock. - self.data_lock.w_demote() - return self.data_adaptor - - def release(self): - """Release the reader lock""" - self.data_lock.r_release() - - def delete(self): - """Clear resources used by this dataset""" - with self.data_lock.w_locked(): - if self.data_adaptor: - self.data_adaptor.cleanup() - self.data_adaptor = None - - def attempt_delete(self): - """Delete, but only if the write lock can be immediately locked. Return True if the delete happened""" - if self.data_lock.w_acquire_non_blocking(): - if self.data_adaptor: - try: - self.data_adaptor.cleanup() - self.data_adaptor = None - except Exception: - # catch all exceptions to ensure the lock is released - pass - - self.data_lock.w_release() - return True - else: - return False - - -class MatrixDataCacheInfo(object): - def __init__(self, cache_item, timestamp): - # The MatrixDataCacheItem in the cache - self.cache_item = cache_item - # The last time the cache_item was accessed - self.last_access = timestamp - # The number of times the cache_item was accessed (used for testing) - self.num_access = 1 - - -class MatrixDataCacheManager(object): - """A class to manage the cached datasets. This is intended to be used as a context manager - for handling api requests. When the context is created, the data_adator is either loaded or - retrieved from a cache. In either case, the reader lock is taken during this time, and release - when the context ends. This class currently implements a simple least recently used cache, - which can delete a dataset from the cache to make room for a new one. - - This is the intended usage pattern: - - m = MatrixDataCacheManager(max_cached=..., timelimmit_s = ...) - with m.data_adaptor(location, app_config) as data_adaptor: - # use the data_adaptor for some operation - """ - - # FIXME: If the number of active datasets exceeds the max_cached, then each request could - # lead to a dataset being deleted and a new only being opened: the cache will get thrashed. - # In this case, we may need to send back a 503 (Server Unavailable), or some other error message. - - # NOTE: If the actual dataset is changed. E.g. a new set of datafiles replaces an existing set, - # then the cache will not react to this, however once the cache time limit is reached, the dataset - # will automatically be refreshed. - - def __init__(self, max_cached, timelimit_s=None): - # key is tuple(url_dataroot, location), value is a MatrixDataCacheInfo - self.datasets = {} - - # lock to protect the datasets - self.lock = threading.Lock() - - # The number of datasets to cache. When max_cached is reached, the least recently used - # cache is replaced with the newly requested one. - # TODO: This is very simple. This can be improved by taking into account how much space is actually - # taken by each dataset, instead of arbitrarily picking a max datasets to cache. - self.max_cached = max_cached - - # items are automatically removed from the cache once this time limit is reached - self.timelimit_s = timelimit_s - - @contextmanager - def data_adaptor(self, url_dataroot, location, app_config): - # create a loader for to this location if it does not already exist - - delete_adaptor = None - data_adaptor = None - cache_item = None - - key = (url_dataroot, location) - with self.lock: - self.evict_old_datasets() - info = self.datasets.get(key) - if info is not None: - info.last_access = time.time() - info.num_access += 1 - self.datasets[key] = info - data_adaptor = info.cache_item.acquire_existing() - cache_item = info.cache_item - - if data_adaptor is None: - while True: - if len(self.datasets) < self.max_cached: - break - - items = list(self.datasets.items()) - items = sorted(items, key=lambda x: x[1].last_access) - # close the least recently used loader - oldest = items[0] - oldest_cache = oldest[1].cache_item - oldest_key = oldest[0] - del self.datasets[oldest_key] - delete_adaptor = oldest_cache - - loader = MatrixDataLoader(location, app_config=app_config) - cache_item = MatrixDataCacheItem(loader) - item = MatrixDataCacheInfo(cache_item, time.time()) - self.datasets[key] = item - - try: - assert cache_item - if delete_adaptor: - delete_adaptor.delete() - if data_adaptor is None: - dataset_config = app_config.get_dataset_config(url_dataroot) - data_adaptor = cache_item.acquire_and_open(app_config, dataset_config) - yield data_adaptor - except DatasetAccessError: - cache_item.release() - with self.lock: - del self.datasets[key] - cache_item.delete() - cache_item = None - raise - - finally: - if cache_item: - cache_item.release() - - def evict_old_datasets(self): - # must be called with the lock held - if self.timelimit_s is None: - return - - now = time.time() - to_del = [] - for key, info in self.datasets.items(): - if (now - info.last_access) > self.timelimit_s: - # remove the data_cache when if it has been in the cache too long - to_del.append((key, info)) - - for key, info in to_del: - # try and get the write_lock for the dataset. - # if this returns false, it means the dataset is being used, and should - # not be removed. - if info.cache_item.attempt_delete(): - del self.datasets[key] - - -class MatrixDataType(Enum): - H5AD = "h5ad" - CXG = "cxg" - UNKNOWN = "unknown" - - -class MatrixDataLoader(object): - def __init__(self, location, matrix_data_type=None, app_config=None): - """ location can be a string or DataLocator """ - region_name = None if app_config is None else app_config.server_config.data_locator__s3__region_name - self.location = DataLocator(location, region_name=region_name) - if not self.location.exists(): - raise DatasetAccessError("Dataset does not exist.", HTTPStatus.NOT_FOUND) - - # matrix_data_type is an enum value of type MatrixDataType - self.matrix_data_type = matrix_data_type - # matrix_type is a DataAdaptor type, which corresponds to the matrix_data_type - self.matrix_type = None - - if matrix_data_type is None: - self.matrix_data_type = self.__matrix_data_type() - - if not self.__matrix_data_type_allowed(app_config): - raise DatasetAccessError("Dataset does not have an allowed type.") - - if self.matrix_data_type == MatrixDataType.H5AD: - from backend.czi_hosted.data_anndata.anndata_adaptor import AnndataAdaptor - - self.matrix_type = AnndataAdaptor - elif self.matrix_data_type == MatrixDataType.CXG: - from backend.czi_hosted.data_cxg.cxg_adaptor import CxgAdaptor - - self.matrix_type = CxgAdaptor - - def __matrix_data_type(self): - if self.location.path.endswith(".h5ad"): - return MatrixDataType.H5AD - elif ".cxg" in self.location.path: - return MatrixDataType.CXG - else: - return MatrixDataType.UNKNOWN - - def __matrix_data_type_allowed(self, app_config): - if self.matrix_data_type == MatrixDataType.UNKNOWN: - return False - - if not app_config: - return True - if not app_config.is_multi_dataset(): - return True - if len(app_config.server_config.multi_dataset__allowed_matrix_types) == 0: - return True - - for val in app_config.server_config.multi_dataset__allowed_matrix_types: - try: - if self.matrix_data_type == MatrixDataType(val): - return True - except ValueError: - # Check case where multi_dataset_allowed_matrix_type does not have a - # valid MatrixDataType value. TODO: Add a feature to check - # the AppConfig for errors on startup - return False - - return False - - def pre_load_validation(self): - if self.matrix_data_type == MatrixDataType.UNKNOWN: - raise DatasetAccessError("Dataset does not have a recognized type: .h5ad or .cxg") - self.matrix_type.pre_load_validation(self.location) - - def file_size(self): - return self.matrix_type.file_size(self.location) - - def open(self, app_config, dataset_config=None): - # create and return a DataAdaptor object - return self.matrix_type.open(self.location, app_config, dataset_config) diff --git a/backend/czi_hosted/data_common/rwlock.py b/backend/czi_hosted/data_common/rwlock.py deleted file mode 100644 index f701afa1..00000000 --- a/backend/czi_hosted/data_common/rwlock.py +++ /dev/null @@ -1,135 +0,0 @@ -# -*- coding: utf-8 -*- -""" rwlock.py - - A class to implement read-write locks on top of the standard threading - library. - - This is implemented with two mutexes (threading.Lock instances) as per this - wikipedia pseudocode: - - https://en.wikipedia.org/wiki/Readers%E2%80%93writer_lock#Using_two_mutexes - - Code written by Tyler Neylon at Unbox Research. - - This file is public domain. - - Modified to add a w_demote function to convert a writer lock to a reader lock -""" - - -# _______________________________________________________________________ -# Imports - -from contextlib import contextmanager -from threading import Lock - - -# _______________________________________________________________________ -# Class - - -class RWLock(object): - """ RWLock class; this is meant to allow an object to be read from by - multiple threads, but only written to by a single thread at a time. See: - https://en.wikipedia.org/wiki/Readers%E2%80%93writer_lock - - Usage: - - from rwlock import RWLock - - my_obj_rwlock = RWLock() - - # When reading from my_obj: - with my_obj_rwlock.r_locked(): - do_read_only_things_with(my_obj) - - # When writing to my_obj: - with my_obj_rwlock.w_locked(): - mutate(my_obj) - """ - - def __init__(self): - - self.w_lock = Lock() - self.num_r_lock = Lock() - self.num_r = 0 - - # The d_lock is needed to handle the demotion case, - # so that the writer can become a reader without releasing the w_lock. - # the d_lock is held by the writer, and prevents any other thread from taking the - # num_r_lock during that time, which means the writer thread is able to take the - # num_r_lock to update the num_r. - self.d_lock = Lock() - - # ___________________________________________________________________ - # Reading methods. - - def r_acquire(self): - self.d_lock.acquire() - self.num_r_lock.acquire() - self.num_r += 1 - - if self.num_r == 1: - self.w_lock.acquire() - - self.num_r_lock.release() - self.d_lock.release() - - def r_release(self): - assert self.num_r > 0 - self.num_r_lock.acquire() - self.num_r -= 1 - if self.num_r == 0: - self.w_lock.release() - - self.num_r_lock.release() - - @contextmanager - def r_locked(self): - """ This method is designed to be used via the `with` statement. """ - try: - self.r_acquire() - yield - finally: - self.r_release() - - # ___________________________________________________________________ - # Writing methods. - - def w_acquire(self): - self.d_lock.acquire() - self.w_lock.acquire() - - def w_acquire_non_blocking(self): - # if d_lock and w_lock can be acquired without blocking, acquire and return True, - # else immediately return False. - if self.d_lock.acquire(blocking=False): - if self.w_lock.acquire(blocking=False): - return True - else: - self.d_lock.release() - return False - - def w_release(self): - self.w_lock.release() - self.d_lock.release() - - def w_demote(self): - """demote a writer lock to a reader lock""" - - # the d_lock is already held from w_acquire. - # releasing the d_lock at the end of this function allows multiple readers. - # incrementing num_r makes this thread one of those readers. - self.num_r_lock.acquire() - self.num_r += 1 - self.num_r_lock.release() - self.d_lock.release() - - @contextmanager - def w_locked(self): - """ This method is designed to be used via the `with` statement. """ - try: - self.w_acquire() - yield - finally: - self.w_release() diff --git a/backend/czi_hosted/data_cxg/__init__.py b/backend/czi_hosted/data_cxg/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/data_cxg/cxg_adaptor.py b/backend/czi_hosted/data_cxg/cxg_adaptor.py deleted file mode 100644 index a0643935..00000000 --- a/backend/czi_hosted/data_cxg/cxg_adaptor.py +++ /dev/null @@ -1,470 +0,0 @@ -import json -import logging -import os -import threading - -import numpy as np -import pandas as pd -import tiledb -from server_timing import Timing as ServerTiming - -from backend.common.constants import Axis, XApproximateDistribution -from backend.common.errors import DatasetAccessError, ConfigurationError -from backend.czi_hosted.common.immutable_kvcache import ImmutableKVCache -from backend.common.utils.type_conversion_utils import get_schema_type_hint_from_dtype -from backend.common.utils.utils import path_join -from backend.czi_hosted.compute import diffexp_cxg -from backend.czi_hosted.data_common.data_adaptor import DataAdaptor -from backend.common.fbs.matrix import encode_matrix_fbs -from backend.czi_hosted.data_cxg.cxg_util import pack_selector_from_mask - - -class CxgAdaptor(DataAdaptor): - # TODO: The tiledb context parameters should be a configuration option - tiledb_ctx = tiledb.Ctx( - {"sm.tile_cache_size": 8 * 1024 * 1024 * 1024, "sm.num_reader_threads": 32, "vfs.s3.region": "us-east-1"} - ) - - def __init__(self, data_locator, app_config=None, dataset_config=None): - super().__init__(data_locator, app_config, dataset_config) - self.lock = threading.Lock() - - self.url = data_locator.uri_or_path - if self.url[-1] != "/": - self.url += "/" - - # caching immutable state - self.lsuri_results = ImmutableKVCache(lambda key: self._lsuri(uri=key, tiledb_ctx=self.tiledb_ctx)) - self.arrays = ImmutableKVCache(lambda key: self._open_array(uri=key, tiledb_ctx=self.tiledb_ctx)) - self.schema = None - self.X_approximate_distribution = None - - self._validate_and_initialize() - - def cleanup(self): - """close all the open tiledb arrays""" - for array in self.arrays.values(): - array.close() - self.arrays.clear() - - @staticmethod - def set_tiledb_context(context_params): - """Set the tiledb context. This should be set before any instances of CxgAdaptor are created""" - try: - CxgAdaptor.tiledb_ctx = tiledb.Ctx(context_params) - tiledb.default_ctx(context_params) - - except tiledb.libtiledb.TileDBError as e: - if e.message == "Global context already initialized!": - if tiledb.default_ctx().config().dict() != CxgAdaptor.tiledb_ctx.config().dict(): - raise ConfigurationError("Cannot change tiledb configuration once it is set") - else: - raise ConfigurationError(f"Invalid tiledb context: {str(e)}") - - @staticmethod - def pre_load_validation(data_locator): - location = data_locator.uri_or_path - if not CxgAdaptor.isvalid(location): - logging.error(f"cxg matrix is not valid: {location}") - raise DatasetAccessError("cxg matrix is not valid") - - @staticmethod - def file_size(data_locator): - return 0 - - @staticmethod - def open(data_locator, app_config, dataset_config=None): - return CxgAdaptor(data_locator, app_config, dataset_config) - - def get_about(self): - return self.about if self.about else super().get_about() - - def get_title(self): - return self.title if self.title else super().get_title() - - def get_corpora_props(self): - return self.corpora_props if self.corpora_props else super().get_corpora_props() - - def get_name(self): - return "cellxgene cxg adaptor version" - - def get_library_versions(self): - return dict(tiledb=tiledb.__version__) - - def get_path(self, *urls): - return path_join(self.url, *urls) - - @staticmethod - def _lsuri(uri, tiledb_ctx): - def _cleanpath(p): - if p[-1] == "/": - return p[:-1] - else: - return p - - result = [] - tiledb.ls(uri, lambda path, type: result.append((_cleanpath(path), type)), ctx=tiledb_ctx) - return result - - def lsuri(self, uri): - """ - given a URI, do a tiledb.ls but normalizing for all path weirdness: - * S3 URIs require trailing slash. file: doesn't care. - * results on S3 *have* a trailing slash, Posix does not. - - returns list of (absolute paths, type) *without* trailing slash - in the path. - """ - if uri[-1] != "/": - uri += "/" - return self.lsuri_results[uri] - - @staticmethod - def isvalid(url): - """ - Return True if this looks like a valid CXG, False if not. Just a quick/cheap - test, not to be fully trusted. - """ - if not tiledb.object_type(url, ctx=CxgAdaptor.tiledb_ctx) == "group": - return False - if not tiledb.object_type(path_join(url, "obs"), ctx=CxgAdaptor.tiledb_ctx) == "array": - return False - if not tiledb.object_type(path_join(url, "var"), ctx=CxgAdaptor.tiledb_ctx) == "array": - return False - if not tiledb.object_type(path_join(url, "X"), ctx=CxgAdaptor.tiledb_ctx) == "array": - return False - if not tiledb.object_type(path_join(url, "emb"), ctx=CxgAdaptor.tiledb_ctx) == "group": - return False - return True - - def has_array(self, name): - a_type = tiledb.object_type(path_join(self.url, name), ctx=self.tiledb_ctx) - return a_type == "array" - - def _validate_and_initialize(self): - """ - remember, preload_validation() has already been called, so - no need to repeat anything it has done. - - Load the CXG "group" metadata and cache instance values. - Be very aware of multiple versions of the CXG object. - - CXG versions in the wild: - * version 0, aka "no version" -- can be detected by the lack - of a cxg_group_metadata array. - * version 0.1 -- metadata attache to cxg_group_metadata array. - Same as 0, except it adds group metadata. - """ - title = None - about = None - corpora_props = None - if self.has_array("cxg_group_metadata"): - # version >0 - gmd = self.open_array("cxg_group_metadata") - cxg_version = gmd.meta["cxg_version"] - # version 0.1 used a malformed/shorthand semver string. - if cxg_version == "0.1" or cxg_version == "0.2.0": - cxg_properties = json.loads(gmd.meta["cxg_properties"]) - title = cxg_properties.get("title", None) - about = cxg_properties.get("about", None) - if cxg_version == "0.2.0": - corpora_props = json.loads(gmd.meta["corpora"]) if "corpora" in gmd.meta else None - else: - # version 0 - cxg_version = "0.0" - - if cxg_version not in ["0.0", "0.1", "0.2.0"]: - raise DatasetAccessError(f"cxg matrix is not valid: {self.url}") - - if self.dataset_config.X_approximate_distribution == "auto": - raise ConfigurationError("X-approximate-distribution 'auto' mode unsupported.") - self.X_approximate_distribution = self.dataset_config.X_approximate_distribution - - self.title = title - self.about = about - self.cxg_version = cxg_version - self.corpora_props = corpora_props - - @staticmethod - def _open_array(uri, tiledb_ctx): - with tiledb.Array(uri, mode="r", ctx=tiledb_ctx) as array: - if array.schema.sparse: - return tiledb.SparseArray(uri, mode="r", ctx=tiledb_ctx) - else: - return tiledb.DenseArray(uri, mode="r", ctx=tiledb_ctx) - - def open_array(self, name): - try: - p = self.get_path(name) - return self.arrays[p] - except tiledb.libtiledb.TileDBError: - raise DatasetAccessError(name) - - def get_embedding_array(self, ename, dims=2): - array = self.open_array(f"emb/{ename}") - return array[:, 0:dims] - - def compute_diffexp_ttest(self, maskA, maskB, top_n=None, lfc_cutoff=None): - if top_n is None: - top_n = self.dataset_config.diffexp__top_n - if lfc_cutoff is None: - lfc_cutoff = self.dataset_config.diffexp__lfc_cutoff - return diffexp_cxg.diffexp_ttest( - adaptor=self, maskA=maskA, maskB=maskB, top_n=top_n, diffexp_lfc_cutoff=lfc_cutoff - ) - - def get_colors(self): - if self.cxg_version == "0.0": - return dict() - meta = self.open_array("cxg_group_metadata").meta - return json.loads(meta["cxg_category_colors"]) if "cxg_category_colors" in meta else dict() - - def __remap_indices(self, coord_range, coord_mask, coord_data): - """ - This function maps the indices in coord_data, which could be in the range [0,coord_range), to - a range that only includes the number of indices encoded in coord_mask. - coord_range is the maxinum size of the range (e.g. get_shape()[0] or get_shape()[1]) - coord_mask is a mask passed into the get_X_array, of size coord_range - coord_data are indices representing locations of non-zero values, in the range [0,coord_range). - - For example, say - coord_mask = [1,0,1,0,0,1] - coord_data = [2,0,2,2,5] - - The function computes the following: - indices = [0,2,5] - ncoord = 3 - maprange = [0,1,2] - mapindex = [0,0,1,0,0,2] - coordindices = [1,0,1,1,2] - """ - if coord_mask is None: - return coord_range, coord_data - - indices = np.where(coord_mask)[0] - ncoord = indices.shape[0] - maprange = np.arange(ncoord) - mapindex = np.zeros(indices[-1] + 1, dtype=int) - mapindex[indices] = maprange - coordindices = mapindex[coord_data] - return ncoord, coordindices - - def get_X_array(self, obs_mask=None, var_mask=None): - obs_items = pack_selector_from_mask(obs_mask) - var_items = pack_selector_from_mask(var_mask) - if obs_items is None or var_items is None: - # If either zero rows or zero columns were selected, return an empty 2d array. - shape = self.get_shape() - obs_size = 0 if obs_items is None else shape[0] if obs_mask is None else np.count_nonzero(obs_mask) - var_size = 0 if var_items is None else shape[1] if var_mask is None else np.count_nonzero(var_mask) - return np.ndarray((obs_size, var_size)) - - X = self.open_array("X") - - if X.schema.sparse: - if obs_items == slice(None) and var_items == slice(None): - data = X[:, :] - else: - data = X.multi_index[obs_items, var_items] - - nrows, obsindices = self.__remap_indices(X.shape[0], obs_mask, data.get("coords", data)["obs"]) - ncols, varindices = self.__remap_indices(X.shape[1], var_mask, data.get("coords", data)["var"]) - densedata = np.zeros((nrows, ncols), dtype=self.get_X_array_dtype()) - densedata[obsindices, varindices] = data[""] - if self.has_array("X_col_shift"): - X_col_shift = self.open_array("X_col_shift") - if var_items == slice(None): - densedata += X_col_shift[:] - else: - densedata += X_col_shift.multi_index[var_items][""] - - return densedata - - else: - if obs_items == slice(None) and var_items == slice(None): - data = X[:, :] - else: - data = X.multi_index[obs_items, var_items][""] - return data - - def get_X_approximate_distribution(self) -> XApproximateDistribution: - return self.X_approximate_distribution - - def get_shape(self): - X = self.open_array("X") - return X.shape - - def get_X_array_dtype(self): - X = self.open_array("X") - return X.dtype - - def query_var_array(self, term_name): - var = self.open_array("var") - data = var.query(attrs=[term_name])[:][term_name] - return data - - def query_obs_array(self, term_name): - var = self.open_array("obs") - try: - data = var.query(attrs=[term_name])[:][term_name] - except tiledb.libtiledb.TileDBError: - raise DatasetAccessError("query_obs") - return data - - def get_obs_names(self): - # get the index from the meta data - obs = self.open_array("obs") - meta = json.loads(obs.meta["cxg_schema"]) - index_name = meta["index"] - return index_name - - def get_obs_index(self): - obs = self.open_array("obs") - meta = json.loads(obs.meta["cxg_schema"]) - index_name = meta["index"] - data = obs.query(attrs=[index_name])[:][index_name] - return data - - def get_obs_columns(self): - obs = self.open_array("obs") - schema = obs.schema - col_names = [attr.name for attr in schema] - return pd.Index(col_names) - - def get_obs_keys(self): - obs = self.open_array("obs") - schema = obs.schema - return [attr.name for attr in schema] - - def get_var_keys(self): - var = self.open_array("var") - schema = var.schema - return [attr.name for attr in schema] - - # function to get the embedding - # this function to iterate through embeddings. - def get_embedding_names(self): - with ServerTiming.time("layout.lsuri"): - pemb = self.get_path("emb") - embeddings = [os.path.basename(p) for (p, t) in self.lsuri(pemb) if t == "array"] - if len(embeddings) == 0: - raise DatasetAccessError("cxg matrix missing embeddings") - return embeddings - - def _get_schema(self): - if self.schema: - return self.schema - - shape = self.get_shape() - dtype = self.get_X_array_dtype() - - dataframe = {"nObs": shape[0], "nVar": shape[1], **get_schema_type_hint_from_dtype(dtype)} - - annotations = {} - for ax in ("obs", "var"): - A = self.open_array(ax) - schema_hints = json.loads(A.meta["cxg_schema"]) if "cxg_schema" in A.meta else {} - if type(schema_hints) is not dict: - raise TypeError("Array schema was malformed.") - - cols = [] - for attr in A.schema: - schema = dict(name=attr.name, writable=False) - type_hint = schema_hints.get(attr.name, {}) - # type hints take precedence - if "type" in type_hint: - schema["type"] = type_hint["type"] - if schema["type"] == "categorical" and "categories" in type_hint: - schema["categories"] = type_hint["categories"] - else: - schema.update(get_schema_type_hint_from_dtype(attr.dtype)) - cols.append(schema) - - annotations[ax] = dict(columns=cols) - - if "index" in schema_hints: - annotations[ax].update({"index": schema_hints["index"]}) - - obs_layout = [] - embeddings = self.get_embedding_names() - for ename in embeddings: - A = self.open_array(f"emb/{ename}") - obs_layout.append({"name": ename, "type": "float32", "dims": [f"{ename}_{d}" for d in range(0, A.ndim)]}) - - schema = {"dataframe": dataframe, "annotations": annotations, "layout": {"obs": obs_layout}} - return schema - - def get_schema(self): - if self.schema is None: - with self.lock: - self.schema = self._get_schema() - return self.schema - - def _annotations_field_split(self, axis, fields, A, labels): - """ - fields: requested fields, may be None (all) - labels: writable user annotations dataframe, if any - - Remove redundant fields, raise KeyError on non-existant fields, - and split into three lists: - fields_to_fetch_from_cxg - fields_to_fetch_from_labels - fields_to_return - - if we have to return from labels, the fetch fields will contain the index - to join on, which may not be in fields_to_return - """ - need_labels = axis == Axis.OBS and labels is not None and not labels.empty - index_key = self.get_obs_names() if need_labels else None - - if not fields: - return (None, None, None, index_key) - - cxg_keys = frozenset([a.name for a in A.schema]) - user_anno_keys = frozenset(labels.columns.tolist()) if need_labels else frozenset() - return_keys = frozenset(fields) - - label_join_index = frozenset([index_key]) if need_labels and (return_keys & user_anno_keys) else frozenset() - - unknown_fields = return_keys - (cxg_keys | user_anno_keys) - if unknown_fields: - raise KeyError("_".join(unknown_fields)) - - return ( - list((return_keys & cxg_keys) | label_join_index), - list(return_keys & user_anno_keys), - list(return_keys), - index_key, - ) - - def annotation_to_fbs_matrix(self, axis, fields=None, labels=None): - with ServerTiming.time(f"annotations.{axis}.query"): - A = self.open_array(str(axis)) - - # may raise if fields contains unknown key - cxg_fields, anno_fields, return_fields, index_field = self._annotations_field_split(axis, fields, A, labels) - - if cxg_fields is None: - data = A[:] - elif cxg_fields: - data = A.query(attrs=cxg_fields)[:] - else: - data = {} - - df = pd.DataFrame.from_dict(data) - - if axis == Axis.OBS and labels is not None and not labels.empty: - if anno_fields is None: - assert index_field - df = df.join(labels, index_field) - elif anno_fields: - assert index_field - df = df.join(labels[anno_fields], index_field) - - if return_fields: - df = df[return_fields] - - with ServerTiming.time(f"annotations.{axis}.encode"): - fbs = encode_matrix_fbs(df, col_idx=df.columns) - - return fbs diff --git a/backend/czi_hosted/data_cxg/cxg_util.py b/backend/czi_hosted/data_cxg/cxg_util.py deleted file mode 100644 index f5759e8d..00000000 --- a/backend/czi_hosted/data_cxg/cxg_util.py +++ /dev/null @@ -1,37 +0,0 @@ -import numpy as np - - -def pack_selector_from_mask(boolarray): - """ - pack all contiguous selectors into slices. Remember that - tiledb multi_index requires INCLUSIVE indices. - """ - - if boolarray is None: - return slice(None) - - assert type(boolarray) == np.ndarray - assert boolarray.dtype == bool - - selector = np.nonzero(boolarray)[0] - return pack_selector_from_indices(selector) - - -def pack_selector_from_indices(selector): - - if len(selector) == 0: - return None - - result = [] - current = slice(selector[0], selector[0]) - for sel in selector[1:]: - if sel == current.stop + 1: - current = slice(current.start, sel) - else: - result.append(current if current.start != current.stop else current.start) - current = slice(sel, sel) - - if len(result) == 0 or result[-1] != current: - result.append(current if current.start != current.stop else current.start) - - return result diff --git a/backend/czi_hosted/db/__init__.py b/backend/czi_hosted/db/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/db/cellxgene_orm.py b/backend/czi_hosted/db/cellxgene_orm.py deleted file mode 100644 index 2860f6b1..00000000 --- a/backend/czi_hosted/db/cellxgene_orm.py +++ /dev/null @@ -1,58 +0,0 @@ -import uuid - -from sqlalchemy import Column, DateTime, ForeignKey, String, func, JSON -from sqlalchemy.dialects.postgresql import UUID -from sqlalchemy.ext.declarative import declarative_base -from sqlalchemy.orm import relationship - -Base = declarative_base() - - -class CellxGeneUser(Base): - """ - A registered CellxGene user. - Links a user to their annotations - """ - - __tablename__ = "cxguser" - - id = Column(String, primary_key=True) - created_at = Column(DateTime, nullable=False, server_default=func.now()) - updated_at = Column(DateTime, nullable=False, server_default=func.now(), onupdate=func.now()) - - # Relationships - annotations = relationship("Annotation", back_populates="cxguser") - - -class Annotation(Base): - """ - An annotation is a link between a user, a dataset and tiledb dataframe. A user can have multiple annotations for a - dataset, the most recent annotation (based on created_at) will be the default returned when queried - """ - - __tablename__ = "annotation" - - id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, unique=True, nullable=False) - tiledb_uri = Column(String) - user_id = Column(String, ForeignKey("cxguser.id"), nullable=False) - dataset_id = Column(UUID, ForeignKey("cxgdataset.id"), nullable=False) - - created_at = Column(DateTime, nullable=False, server_default=func.now()) - schema_hints = Column(JSON) - # Relationships - cxguser = relationship("CellxGeneUser", back_populates="annotations") - dataset = relationship("CellxGeneDataset", back_populates="annotations") - - -class CellxGeneDataset(Base): - """ - Datasets refer to datasets stored by cellxgene - """ - - __tablename__ = "cxgdataset" - - id = Column(UUID(as_uuid=True), primary_key=True, default=uuid.uuid4, unique=True, nullable=False) - name = Column(String, unique=True, index=True) - - created_at = Column(DateTime, nullable=False, server_default=func.now()) - annotations = relationship("Annotation", back_populates="dataset") diff --git a/backend/czi_hosted/db/create_db.py b/backend/czi_hosted/db/create_db.py deleted file mode 100644 index 58e2c6de..00000000 --- a/backend/czi_hosted/db/create_db.py +++ /dev/null @@ -1,18 +0,0 @@ -""" -Drops and recreates all tables for local testing according to cellxgene_orm.py -""" -from sqlalchemy import create_engine - -from backend.czi_hosted.db.cellxgene_orm import Base - - -def create_db(database_uri: str = "postgresql://postgres:test_pw@localhost:5432"): - engine = create_engine(database_uri) - print("Dropping tables") - Base.metadata.drop_all(engine) - print("Recreating tables") - Base.metadata.create_all(engine) - - -if __name__ == "__main__": - create_db() diff --git a/backend/czi_hosted/db/db_utils.py b/backend/czi_hosted/db/db_utils.py deleted file mode 100644 index 85230f63..00000000 --- a/backend/czi_hosted/db/db_utils.py +++ /dev/null @@ -1,71 +0,0 @@ -import typing -import uuid - -from sqlalchemy import create_engine -from sqlalchemy.orm import sessionmaker - -from backend.czi_hosted.db.cellxgene_orm import Base, CellxGeneDataset, CellxGeneUser - - -class DbUtils: - def __init__(self, database_uri: str = "postgresql://postgres:test_pw@localhost:5432"): - self.session = DBSessionMaker(database_uri).session() - self.engine = self.session.get_bind() - - def get(self, table: Base, entity_id: typing.Union[str, typing.Tuple[str]]) -> typing.Union[Base, None]: - """ - Query a table row by its primary key - :param table: SQLAlchemy Table to query - :param entity_id: Primary key of desired row - :return: SQLAlchemy Table object, None if not found - """ - return self.session.query(table).get(entity_id) - - def query(self, table_args: typing.List[Base], filter_args: typing.List[bool] = None) -> typing.List[Base]: - """ - Query the database using the current DB session - :param table_args: List of SQLAlchemy Tables to query/join - :param filter_args: List of SQLAlchemy filter conditions - :return: List of SQLAlchemy query response objects - """ - return ( - self.session.query(*table_args).filter(*filter_args).all() - if filter_args - else self.session.query(*table_args).all() - ) - - def query_for_most_recent(self, table: Base, filter_args: typing.List[bool] = None) -> Base: - try: - return self.session.query(table).filter(*filter_args).order_by(table.created_at.desc()).limit(1).all()[0] - except IndexError: - return None - - def get_or_create_dataset(self, dataset_name): - try: - dataset_id = self.query(table_args=[CellxGeneDataset], filter_args=[CellxGeneDataset.name == dataset_name])[ - 0 - ].id - except IndexError: - dataset_id = uuid.uuid4() - dataset = CellxGeneDataset(id=dataset_id, name=dataset_name) - self.session.add(dataset) - self.session.commit() - return str(dataset_id) - - def get_or_create_user(self, user_id): - try: - user_id = self.query(table_args=[CellxGeneUser], filter_args=[CellxGeneUser.id == user_id])[0].id - except IndexError: - user = CellxGeneUser(id=user_id) - self.session.add(user) - self.session.commit() - return str(user_id) - - -class DBSessionMaker: - def __init__(self, database_uri): - self.engine = create_engine(database_uri, connect_args={"connect_timeout": 5}) - self.session_maker = sessionmaker(bind=self.engine) - - def session(self, **kwargs): - return self.session_maker(**kwargs) diff --git a/backend/czi_hosted/default_config.py b/backend/czi_hosted/default_config.py deleted file mode 100644 index 214eeb31..00000000 --- a/backend/czi_hosted/default_config.py +++ /dev/null @@ -1,266 +0,0 @@ -import yaml - -default_config = """ -server: - app: - verbose: false - debug: false - host: localhost - port : null - open_browser: false - force_https: false - flask_secret_key: null - generate_cache_control_headers: false - server_timing_headers: false - csp_directives: null - - # By default, cellxgene will serve api requests from the same base url as the webpage. - # In general api_base_url and web_base_url will not need to be set. - # There are two reasons to set these parameters: - # 1. Oauth authentication is used; the oauth server will redirect back to the api_base_url after login, - # which then redirects back to the web_base_url. If the web_base_url is not set, it will default to - # the api_base_url. If oauth authentication is used, the api_base_url must be set. - # For a local test (where the server runs on "http://localhost:"), then the api_base_url may be - # set to the string "local". - # 2. The cellxgene deploymnent is in an environment where the webpage and api have - # different base urls. In this case both api_base_url and web_base_url must be set. - # It is up to the server admin to ensure that the networking is setup correctly for this environment. - api_base_url: null - web_base_url: null - - authentication: - # The authentication types may be "none", "session", "oauth" or "test" - # none: No authentication support, features like user_annotations must not be enabled. - # session: A session based userid is automatically generated. (no params needed) - # oauth: oauth2 is used for authentication; parameters are defined in params_oauth. - # test: Simple module for testing the authentication logic without connecting to an external service - type: test - insecure_test_environment: true - - params_oauth: - # url to the oauth server - oauth_api_base_url: null - # client_id of this app - client_id: null - # the client_secret known to the auth server and this app - client_secret: null - # jwt_decode_options, to specify non default decode options define - # jwt_decode_options to be a dictionary with key/values described by - # the options parameter of the jose.jwt.decode function: - # (https://python-jose.readthedocs.io/en/latest/jwt/api.html) - jwt_decode_options: null - - # if true, the jwt containing the id_token is stored in a session cookie - session_cookie: true - - # if session_cookie is false, then a regular cookie will be used. In that case - # the cookie will be defined by a dictionary of parameters. - # The keys of the dictionary match the parameters of the flask set_cookie api - # (https://flask.palletsprojects.com/en/1.1.x/api/), and with the same meaning. - # legal keys: key, max_age, expires, path, domain, secure, httponly, and samesite. - cookie: null - - multi_dataset: - # If dataroot is set, then cellxgene may serve multiple datasets. This parameter is not - # compatible with single_dataset/datapath. - # dataroot may be a string, representing the path to a directory or S3 prefix. In this - # case the datasets in that location are accessed from /d/. - # example: - # dataroot: /path/to/datasets/ - # or - # dataroot: s3://bucket/prefix/ - # - # As an alternative, dataroot can be a dictionary, where a dataset key is associated with a base_url - # and a dataroot. - # example: - # dataroot: - # d1: - # base_url: set1 - # dataroot: /path/to/set1_datasets/ - # d2: - # base_url: set2/subdir - # dataroot: /path/to/set2_datasets/ - # - # In this case, datasets can be accessed from /set1/ or - # /set2/subdir/. It is possible to have different dataset configurations - # for datasets accessed through different dataroots. For example, in one dataroot, the - # user annotations could be enabled, and in another dataroot they could be disabled. - # To specify dataroot configurations, add a new top level dictionary to the config named - # per_dataset_config. Within per_dataset_config create a dictionary for each dataroot to specialize - # ("d1" or "d2" from the example). Each of these dictionaries has the exact same form as the "dataset" - # dictionary (see below). - # When this approach is used, the values for each configuration option are checked in - # this order: per_dataset_config/, dataset, then the default values. - # - # example: - # - # per_dataset_config: - # d1: - # user_annotations: - # enable: false - # d2: - # user_annotations: - # enable: true - - dataroot: null - - # The index page when in multi-dataset mode: - # false or null: this returns a 404 code - # true: loads a test index page, which links to the datasets that are available in the dataroot - # string/URL: redirect to this URL: flask.redirect(config.multi_dataset__index) - index: false - - # A list of allowed matrix types. If an empty list, then all matrix types are allowed - allowed_matrix_types: [] - - matrix_cache: - # The maximum number of datasets that may be opened at one time. The least recently used dataset - # is evicted from the cache first. - max_datasets: 5 - - # A matrix is automatically removed from the cache after timelimit_s number of seconds. - # If timelimit_s is set to None, then there is no time limit. - timelimit_s: 30 - - single_dataset: - # If datapath is set, then cellxgene with serve a single dataset located at datapath. This parameter is not - # compatible with multi_dataset/dataroot. - datapath: null - obs_names: null - var_names: null - about: null - title: null - - diffexp: - alg_cxg: - # The number of threads to use is computed from: min(max_workers, cpu_multipler * cpu_count). - # Where cpu_count is determined at runtime. - max_workers: 64 - cpu_multiplier: 4 - - # The target number of matrix elements that are evaluated - # together in one thread. - target_workunit: 16_000_000 - - data_locator: - s3: - # s3 region name. - # if true, then the s3 location is automatically determined from the datapath or dataroot. - # if false/null, then do not set. - # if a string, then use that value (e.g. us-east-1). - region_name: true - - adaptor: - cxg_adaptor: - # The key/values under tiledb_ctx will be used to initialize the tiledb Context. - # If 'vfs.s3.region' is not set, then it will automatically use the setting from - # data_locator / s3 / region_name. - tiledb_ctx: - sm.tile_cache_size: 8589934592 - sm.num_reader_threads: 32 - - anndata_adaptor: - backed: false - - limits: - column_request_max: 32 - diffexp_cellcount_max: null - - -dataset: - app: - # Scripts can be a list of either file names (string) or dicts containing keys src, integrity and crossorigin. - # these will be injected into the index template as script tags with these attributes set. - scripts: [] - # Inline scripts are a list of file names, where the contents of the file will be injected into the index. - inline_scripts: [] - - about_legal_tos: null - about_legal_privacy: null - - # allow authentication support - authentication_enable: true - - presentation: - max_categories: 1000 - custom_colors: true - - user_annotations: - enable: true - type: local_file_csv - hosted_tiledb_array: - db_uri: null - hosted_file_directory: null - local_file_csv: - directory: null - file: null - - embeddings: - names : [] - - diffexp: - enable: true - lfc_cutoff: 0.01 - top_n: 10 - - X_approximate_distribution: normal # currently fixed config - -external: - # You can retrieve configuration parameters from this config file, the environment, - # the AWS secrets manager, or from the "cellxgene launch" command line arguments. - # They are applied in that order, meaning that if a parameter is defined in more - # than one location, the last one applied takes effect. - - # environment variables: - # This section describes how to map environment variables to configuration parameters. - # The format is a list defining an environment variable. - # Each entry in the list is a dictionary with three entries: - # name: the name of the environment variable - # path: the path within the cellxgene configuration to update. - # required: (default=False) a boolean. If true, then it is an error if the environment variable is not set. - - environment: - - name: CXG_SECRET_KEY - path: [server, app, flask_secret_key] - required: false - - name: CXG_OAUTH_CLIENT_SECRET - path: [server, authentication, params_oauth, client_secret] - required: false - - # AWS Secrets Manager - # This section describes how to map aws secrets to configuration parameters. - # The format is the region for the secrets manager, then a list of secrets. - # each secret has a name, and a list of values. - # Each entry in the list of values is a dictionary with three entries: - # key: the key of the aws secret. - # path: the path within the cellxgene configuration to update. - # required: (default=False) a boolean. If true, then it is an error if the key does not exist in the secret. - # - # example: - # aws_secrets_manager: - # region: us-west-2 - # - name: my_first_secret - # values: - # - key: flask_secret_key - # path: [server, app, flask_secret_key] - # required: true - # - key: db_uri - # path: [dataset, user_annotations, hosted_tiledb_array, db_uri] - # required: true - # - name: my_auth_secret - # values: - # - key: client_secret - # path: [server, authentication, params_oauth, client_secret] - # required: true - # - key: client_id - # path: [server, authentication, params_oauth, client_id] - # required: true - - aws_secrets_manager: - region: null - secrets: [] -""" - - -def get_default_config(): - return yaml.load(default_config, Loader=yaml.Loader) diff --git a/backend/czi_hosted/eb/.ebextensions/database.config b/backend/czi_hosted/eb/.ebextensions/database.config deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/eb/.ebextensions/enable_mod_deflate.config b/backend/czi_hosted/eb/.ebextensions/enable_mod_deflate.config deleted file mode 100644 index 3456869b..00000000 --- a/backend/czi_hosted/eb/.ebextensions/enable_mod_deflate.config +++ /dev/null @@ -1,30 +0,0 @@ -files: - "/etc/httpd/conf.d/enable_mod_deflate.conf": - mode: "000644" - owner: root - group: root - content: | - - - AddOutputFilterByType DEFLATE text/plain - AddOutputFilterByType DEFLATE text/html - AddOutputFilterByType DEFLATE application/xhtml+xml - AddOutputFilterByType DEFLATE text/xml - AddOutputFilterByType DEFLATE application/xml - AddOutputFilterByType DEFLATE application/xml+rss - AddOutputFilterByType DEFLATE application/x-javascript - AddOutputFilterByType DEFLATE text/javascript - AddOutputFilterByType DEFLATE text/css - AddOutputFilterByType DEFLATE application/octet-stream - - DeflateCompressionLevel 9 - - BrowserMatch ^Mozilla/4 gzip-only-text/html - BrowserMatch ^Mozilla/4\.0[678] no-gzip - BrowserMatch \bMSI[E] !no-gzip !gzip-only-text/html - - - Header append Vary User-Agent env=!dont-vary - - - diff --git a/backend/czi_hosted/eb/.ebextensions/wsgi_app_group_global.config b/backend/czi_hosted/eb/.ebextensions/wsgi_app_group_global.config deleted file mode 100644 index cf2ecc61..00000000 --- a/backend/czi_hosted/eb/.ebextensions/wsgi_app_group_global.config +++ /dev/null @@ -1,10 +0,0 @@ -# Configure WSGI so that it will work with numpy, scanpy, etc, which all use the -# Python SWIG, and therefore will deadlock on start. For more information, see -# https://modwsgi.readthedocs.io/en/develop/user-guides/application-issues.html#python-simplified-gil-state-api -files: - "/etc/httpd/conf.d/wsgi_custom.conf": - mode: "000644" - owner: root - group: root - content: | - WSGIApplicationGroup %{GLOBAL} diff --git a/backend/czi_hosted/eb/.gitignore b/backend/czi_hosted/eb/.gitignore deleted file mode 100644 index bca646a7..00000000 --- a/backend/czi_hosted/eb/.gitignore +++ /dev/null @@ -1,5 +0,0 @@ - -# Elastic Beanstalk Files -.elasticbeanstalk/* -!.elasticbeanstalk/*.cfg.yml -!.elasticbeanstalk/*.global.yml diff --git a/backend/czi_hosted/eb/Makefile b/backend/czi_hosted/eb/Makefile deleted file mode 100644 index f00f6a92..00000000 --- a/backend/czi_hosted/eb/Makefile +++ /dev/null @@ -1,59 +0,0 @@ -include ../../../common.mk - -.PHONY: clean -clean: - rm -f artifact.zip - rm -rf artifact.dir - - -# Build the ElasticBeanstalk configuration and deployment bundle, -# such that deployment can be done with a simple `eb deploy`. -# Presumes that a top-level `make build-client` has been done to -# create the client static assets. - -cwd := $(shell pwd) - -.PHONY: build -build: clean - mkdir artifact.dir; \ - (cd ../../.. ; \ - git ls-files backend/czi_hosted/ | cpio -pdm $(cwd)/artifact.dir ; ); \ - $(call copy_client_assets,../../../client/build,artifact.dir/backend/czi_hosted) ; \ - set -e ; \ - cp app.py artifact.dir/application.py; \ - cp -r ../../../backend/common artifact.dir/backend/common; \ - cp ../requirements.txt artifact.dir; \ - cp -r .ebextensions artifact.dir; \ - if [ -d customize ] ; then \ - if [ -f customize/config.yaml ] ; then \ - cp customize/config.yaml artifact.dir; \ - fi ; \ - if [ -f customize/Dockerfile ] ; then \ - cp customize/Dockerfile artifact.dir; \ - fi ; \ - if [ -f customize/requirements.txt ] ; then \ - pip install requirements-parser ; \ - pip install packaging ; \ - python3 check_requirements.py ../requirements.txt customize/requirements.txt; \ - cp customize/requirements.txt artifact.dir; \ - fi ; \ - if [ -d customize/deploy ] ; then \ - mkdir -p artifact.dir/backend/czi_hosted/common/web/static/cellxgene; \ - cp -r customize/deploy artifact.dir/backend/czi_hosted/common/web/static/cellxgene; \ - fi; \ - if [ -d customize/inline_scripts ] ; then \ - cp -r customize/inline_scripts/* artifact.dir/backend/czi_hosted/common/web/templates; \ - fi; \ - if [ -d customize/ebextensions ] ; then \ - cp -r customize/ebextensions/* artifact.dir/.ebextensions; \ - fi; \ - fi; \ - if [ -d customize/plugins ] ; then \ - cp -r customize/plugins artifact.dir/backend/czi_hosted/; \ - fi; \ - (cd artifact.dir; \ - cp -r backend/czi_hosted/common/web/static static; \ - zip -r ../artifact.zip . --exclude backend/czi_hosted/test/\* backend/czi_hosted/eb/\* ; ); \ - if ! grep artifact.zip .elasticbeanstalk/config.yml ; then \ - mkdir -p .elasticbeanstalk ; cat config_deploy.yaml >> .elasticbeanstalk/config.yml ; fi - diff --git a/backend/czi_hosted/eb/README.md b/backend/czi_hosted/eb/README.md deleted file mode 100644 index 306eda00..00000000 --- a/backend/czi_hosted/eb/README.md +++ /dev/null @@ -1,300 +0,0 @@ -# AWS Elastic Beanstalk - -This directory contains scripts to aid in creating and deploying cellxgene on -AWS Elastic Beanstalk. - -This will result in a variant of cellxgene, running on AWS EC2 instances, serving data from S3. -All datasets must be in the CXG (tiledb) format (see `cellxene convert --help`), -and located under a single S3 prefix, which is accessible to the instance. -In the current incarnation, no access control is available -(outside of anything you configure yourself), so this is most appropriate for public datasets. - -This is early development work, and will change significantly in the near future. -We would love feedback on it, but please assume it will change. - -## Prerequisites - -1. Some familiarity with AWS EB, S3, and IAM are needed. - -2. Install the awsebcli. - Instruction are here: - https://docs.aws.amazon.com/elasticbeanstalk/latest/dg/eb-cli3-install.html - -3. In the top level directory, run `make build-client` to create the client static assets. - -## Steps - -These steps are meant to serve as an example. -There are many more options to these commands that may be important or necessary for your environment. - -### 1. Make your matrix files available to the EB servers. - -The following choices are known to work. - -- S3 Bucket. -- POSIX filesystem (such as Lustre) -- Lustre filesystem backed by S3 - -S3 is convenient and the relatively inexpensive option. -Lustre is higher performance, but more expensive, and slightly more complex to setup and manage. -AWS supports a feature to back the Lustre filesystem with S3, which gives an easy to manage, high -performance option. - -Once the storage is in place, the next step is to copy your data files to that location. -Currently cellxgene supports a flat file organization. Each matrix file is located under -the same s3 prefix or filesystem directory. This location is specified in the configuration -as the dataroot. - -### 2. Create an elastic beanstalk application. For example: - -``` -EB_APP=cellxgene-app -eb init -p python-3.6 $EB_APP -``` - -### 3. Configuring cellxgene - -All the cellxgene configuration options can be set from a configuration file. -A yaml config file containing all of the default configuration options can be generated like this: - -`cellxgene launch --dump-default-config > myconfig.yaml` - -The config file may then be customized before the app is deployed. - -There are two ways to set the config file location, evaluated in this order: - -First, if your config file is named "config.yaml" and exists in `customize/config.yaml`, -then it will be bundled with the application zip file and installed along -side the app on the EB servers. - -Second, a potentially more flexible approach is to place your config file in a location accessible -to the EB servers, such as in S3. For example: s3://my-bucket/my-datasets/config.yaml. -Set the CXG_CONFIG_FILE environment variable to specify this location. - -Another option is to set the CXG_DATAROOT environment variable. The dataroot -is the location where the matrix files are located. -This environment variable will override the dataroot in the config file (if specified). - -### 4. Customization - -The deployment can be customized in several ways, by adding files to a directory called -`customize` which is placed in this directory. - -#### config file - -This was described in the previous section. - -#### static files - -The cellxgene server can serve additional static webpages that will be associated with the app. -These include the about_legal_tos (terms of service), and about_legal_privacy, for example. -To use this feature, do the following: - -- In this directory, create a sub directory called "customize/deploy/". -- Copy the files you want to serve into this directory -- modify your configuration file to set the location to these file: /static/cellxgene/deploy/ - -Example: you want to include an "about_legal_tos" and "about_legal_privacy" page to cellxgene. -Assume files called "tos.html" and "privacy.html" exist. - -``` -$ mkdir -p customize/deploy -$ cp /tos.html customize/deploy/tos.html -$ cp /privacy.html customize/deploy/privacy.html - -# edit config.yaml -$ grep "/static/cellxgene/deploy" config.yaml -about_legal_tos: /static/cellxgene/deploy/tos.html -about_legal_privacy: /static/cellxgene/deploy/privacy.html -``` - -#### Inline javascript scripts - -Additional scripts can be added using the server/inline_scripts config parameters. -To include these scripts in the deployment, use the following steps: - -- In this directory, create a sub directory called "customize/inline_scripts". -- Copy the script files into this directory -- Modify your configuration file to set the location to these file (leaving off customize/inline_scripts) - -For example, to add an inline script called "myscript.js": - -``` -$ mkdir -p customize/inline_scripts -$ cp /myscript.js customize/inline_scripts/myscript.js -# edit the config.yaml -$ grep inline_scripts config.yaml - inline_scripts : [ myscript.js ] -``` - -#### Plugins - -Optionally, you can add plugins to the server python code. To include a plugin in the deployment use the following steps: - -``` -$ mkdir -p customize/plugins -$ cp /.py customize/plugins/.py -``` - -#### ebextensions - -Any additional config files intended for the `.ebextensions` directory of the artifact can be added -to the `customize/ebextensions` directory. Any file found here will be copied over. - -#### requirements.txt - -A custom requirements.txt can be supplied in customize/requirements.txt. -This file must fully specify the versions of all the python modules used by the server in the deployment. -This is useful to ensure that the dependencies do not change from one deployment to the next. -Therefore the custom/requirements.txt must all have exact versions specified (e.g. anndata==0.7.1). - -This file can be generated the first time using a process like this: - -``` -# assume you are running in this directory -$ virtualenv temp -$ source temp/bin/activate -$ pip install -r ../requirements.txt -$ mkdir -p customize -$ pip freeze > customize/requirements.txt -$ deactivate -$ rm -rf temp/ -``` - -Keep the customize/requirememts.txt file, and reuse it for each deployment. -If a future cellxgene version updates its requirements by modifying a module version -or adding a new dependency, then the `make build` process will detect any -incompatibilities and raise an error. - -#### File structure for customizations - -The following diagram shows the file structure for the customization directory. - -``` -customization -+-- config.yaml -+-- deploy/ -+-- inline_scripts/ -+-- plugins/ -+-- ebextensions/ -+-- requirements.txt -``` - -### 5. Create the artifact.zip file for the application - -``` -$ make build -``` - -### 6. Flask secret key - -The application requires a secret key to be provided to flask, the web framework used by cellxgene. -There are three ways to provide the secret key: - -- In the configuration file, update the server/flask_secret_key attribute. -- In the configuration file, update the external/aws_secrets_manager section to set the - secret name and key that defines the flask secret key. -- An environment variable: `CXG_SECRET_KEY` - -### 7. Create an environment - -``` -# name of the environment -$ EB_ENV=cellxgene-env - -# type of ec2 instance to run the cellxgene server (for example) -$ EB_INSTANCE=m5.large - -# One or both of the following environment variables needs to be set -$ CXG_DATAROOT= -$ CXG_CONFIG_FILE= - -# Potentially also set an environment variable for the flask secret key, -# and other environemet variable described in the configuration file. - -$ eb create $EB_ENV --instance-type $EB_INSTANCE \ - --envvars CXG_DATAROOT=$CXG_DATAROOT,CXG_CONFIG_FILE=$CXG_CONFIG_FILE -``` - -### 8. Give the elastic beanstalk environment access to the dataroot. - -If using S3, this link may provide some useful information: -https://aws.amazon.com/premiumsupport/knowledge-center/elastic-beanstalk-s3-bucket-instance/ -If using Lustre, then this link may provide a place to start: -https://aws.amazon.com/fsx/lustre/ - -### 9. Deploy the application - -``` -$ eb deploy $EB_ENV -``` - -### 10. Open the application in a browser - -``` -$ eb open $EB_ENV -``` - -## Advanced Features - -### Authentication - -Authentication can be configured in the configuration file. Authentication is required -for User Annotations (see below). User Annotations is a feature where annotations can be -created by the user -, and -then associated with the user's id. -When the user revisits the site, their annotations will be available. - -There are three main authentication modes: null, session, or oauth. -In the configuration file specify the authentication mode by setting -`server / authentication / type`. - -#### null - -Authentication is disabled: user annotations cannot be enabled. - -#### session - -The user is associated with their client browser session. This approach is -simple to setup, but not recommended for hosted cellxgene, since the user will not have access to -their annotations when running from a different browser, or if their cookies get cleared. - -#### oauth - -A user logs into cellxgene using an identity provider (like Google), or logs in using -an email/password. This is the best option, but requires making use of an oauth service and -additional configuration of the cellxgene server. - -To see what this looks like, please look at https://cellxgene.cziscience.com/, -and view one of the cellxgene datasets. -For this server, Auth0 (auth0.com) is used for authentication, but there are other options. -There are good sources of documentation online that describe how to use one of these -services. - -The `params_oauth` section in the configuration file describes characteristics of the -authentication service, like "client_id" and "client_secret". -For security, the client_secret needs to be protected. One option is to -store it in the AWS Secrets Manager. - -### User Annotations - -User annotations can be configured in the configuration file both generally and for a specific data route. The annotations feature is only available when Authorization is enabled. -To enable Annotations, it is necessary to create a relational database and add the database uri (typically `postgresql://[user[:password]@][netloc][:port][/dbname]`) to the secrets manager under `DB_URI`. -The hosted version of cellxgene runs on AWS's [Aurora PostgreSQL](https://docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/Aurora.AuroraPostgreSQL.html) but any sqlalchemy compatible relational database should work. -Once the database is set up apply the cellxgene schema to your database by running the following inside the cellxgene repo -`PROJECT_ROOT=$(git rev-parse --show-toplevel)` -`python3` -Inside the python console -`from sqlalchemy import create_engine` -`from server.db.cellxgene_orm import Base` -`uri = "[DB_URI]”` -`engine = create_engine(uri)` - - Base.metadata.create_all(engine)` - -To check the schema was properly applied (or just to check what is in the database at any point) -ssh into your database. For a postgres database this entails running: -`psql [DB_URI]` - -You'll also need to update your IAM policies to allow the instance to write to the s3 bucket. diff --git a/backend/czi_hosted/eb/__init__.py b/backend/czi_hosted/eb/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/czi_hosted/eb/app.py b/backend/czi_hosted/eb/app.py deleted file mode 100644 index 3a54f18b..00000000 --- a/backend/czi_hosted/eb/app.py +++ /dev/null @@ -1,190 +0,0 @@ -"""cellxgene AWS elastic beanstalk application""" - -import sys -import os -import hashlib -import base64 -from urllib.parse import urlparse -from flask import json -import logging -from flask_talisman import Talisman -from flask_cors import CORS - - -if os.path.isdir("/opt/python/log"): - # This is the standard location where Amazon EC2 instances store the application logs. - logging.basicConfig( - filename="/opt/python/log/app.log", - level=logging.INFO, - format="%(asctime)s.%(msecs)03d %(levelname)s %(module)s - %(funcName)s: %(message)s", - datefmt="%Y-%m-%d %H:%M:%S", - ) - -SERVERDIR = os.path.dirname(os.path.realpath(__file__)) -sys.path.append(SERVERDIR) - -try: - from backend.czi_hosted.common.config.app_config import AppConfig - from backend.czi_hosted.app.app import Server - from backend.common.utils.data_locator import DataLocator, discover_s3_region_name -except Exception: - logging.critical("Exception importing server modules", exc_info=True) - sys.exit(1) - - -class WSGIServer(Server): - def __init__(self, app_config): - super().__init__(app_config) - - @staticmethod - def _before_adding_routes(app, app_config): - script_hashes = WSGIServer.get_csp_hashes(app, app_config) - server_config = app_config.server_config - - # add the api_base_url to the connect_src csp header. - extra_connect_src = [] - api_base_url = server_config.get_api_base_url() - if api_base_url: - parse_api_base_url = urlparse(api_base_url) - extra_connect_src = [f"{parse_api_base_url.scheme}://{parse_api_base_url.netloc}"] - - # This hash should be in sync with the script within - # `client/configuration/webpack/obsoleteHTMLTemplate.html` - - # It is _very_ difficult to generate the correct hash manually, - # consider forcing CSP to fail on the local server by intercepting the response via Requestly - # this should print the failing script's hash to console. - # See more here: https://github.com/chanzuckerberg/cellxgene/pull/1745 - obsolete_browser_script_hash = ["'sha256-/rmgOi/skq9MpiZxPv6lPb1PNSN+Uf4NaUHO/IjyfwM='"] - csp = { - "default-src": ["'self'"], - "connect-src": ["'self'"] + extra_connect_src, - "script-src": ["'self'", "'unsafe-eval'"] + obsolete_browser_script_hash + script_hashes, - "style-src": ["'self'", "'unsafe-inline'"], - "img-src": ["'self'", "https://cellxgene.cziscience.com", "data:"], - "object-src": ["'none'"], - "base-uri": ["'none'"], - "frame-ancestors": ["'none'"], - } - - if not app.debug: - csp["upgrade-insecure-requests"] = "" - - if server_config.app__csp_directives: - for k, v in server_config.app__csp_directives.items(): - if not isinstance(v, list): - v = [v] - csp[k] = csp.get(k, []) + v - - # Add the web_base_url to the CORS header - web_base_url = server_config.get_web_base_url() - if web_base_url: - web_base_url_parse = urlparse(web_base_url) - allowed_origin = f"{web_base_url_parse.scheme}://{web_base_url_parse.netloc}" - CORS(app, supports_credentials=True, origins=allowed_origin) - - Talisman( - app, force_https=server_config.app__force_https, frame_options="DENY", content_security_policy=csp, - ) - - @staticmethod - def load_static_csp_hashes(app): - csp_hashes = None - try: - with app.open_resource("../common/web/csp-hashes.json") as f: - csp_hashes = json.load(f) - except FileNotFoundError: - pass - if not isinstance(csp_hashes, dict): - csp_hashes = {} - script_hashes = [f"'{hash}'" for hash in csp_hashes.get("script-hashes", [])] - if len(script_hashes) == 0: - logging.error("Content security policy hashes are missing, falling back to unsafe-inline policy") - - return script_hashes - - @staticmethod - def compute_inline_csp_hashes(app, app_config): - dataset_configs = [app_config.default_dataset_config] + list(app_config.dataroot_config.values()) - hashes = [] - for dataset_config in dataset_configs: - inline_scripts = dataset_config.app__inline_scripts - for script in inline_scripts: - with app.open_resource(f"../common/web/templates/{script}") as f: - content = f.read() - # we use jinja2 template include, which trims final newline if present. - if content[-1] == 0x0A: - content = content[0:-1] - hash = base64.b64encode(hashlib.sha256(content).digest()) - hashes.append(f"'sha256-{hash.decode('utf-8')}'") - return hashes - - @staticmethod - def get_csp_hashes(app, app_config): - script_hashes = WSGIServer.load_static_csp_hashes(app) - script_hashes += WSGIServer.compute_inline_csp_hashes(app, app_config) - return script_hashes - - -try: - app_config = AppConfig() - - has_config = False - # config file: look first for "config.yaml" in the current working directory - config_file = "config.yaml" - config_location = DataLocator(config_file) - if config_location.exists(): - with config_location.local_handle() as lh: - logging.info(f"Configuration from {config_file}") - app_config.update_from_config_file(lh) - has_config = True - - else: - # config file: second, use the CXG_CONFIG_FILE - config_file = os.getenv("CXG_CONFIG_FILE") - if config_file: - region_name = discover_s3_region_name(config_file) - config_location = DataLocator(config_file, region_name) - if config_location.exists(): - with config_location.local_handle() as lh: - logging.info(f"Configuration from {config_file}") - app_config.update_from_config_file(lh) - has_config = True - else: - logging.critical(f"Configuration file not found {config_file}") - sys.exit(1) - - if not has_config: - logging.critical("No config file found") - sys.exit(1) - - dataroot = os.getenv("CXG_DATAROOT") - if dataroot: - logging.info("Configuration from CXG_DATAROOT") - app_config.update_server_config(multi_dataset__dataroot=dataroot) - - # overwrite configuration for the eb app - app_config.update_server_config(multi_dataset__allowed_matrix_types=["cxg"],) - - # complete config - app_config.complete_config(logging.info) - - server = WSGIServer(app_config) - debug = False - application = server.app - -except Exception: - logging.critical("Caught exception during initialization", exc_info=True) - sys.exit(1) - -if app_config.is_multi_dataset(): - logging.info(f"starting server with multi_dataset__dataroot={app_config.server_config.multi_dataset__dataroot}") -else: - logging.info(f"starting server with single_dataset__datapath={app_config.server_config.single_dataset__datapath}") - -if __name__ == "__main__": - try: - application.run(host=app_config.server_config.app__host, debug=debug, threaded=not debug, use_debugger=False) - except Exception: - logging.critical("Caught exception during initialization", exc_info=True) - sys.exit(1) diff --git a/backend/czi_hosted/eb/check_config.py b/backend/czi_hosted/eb/check_config.py deleted file mode 100644 index 223a21b3..00000000 --- a/backend/czi_hosted/eb/check_config.py +++ /dev/null @@ -1,38 +0,0 @@ -import sys -import argparse -import yaml - -from backend.czi_hosted.common.config.app_config import AppConfig - -def main(): - parser = argparse.ArgumentParser("A script to check hosted configuration files") - parser.add_argument("config_file", help="the configuration file") - parser.add_argument( - "-s", - "--show", - default=False, - action="store_true", - help="print the configuration. NOTE: this may print secret values to stdout", - ) - - args = parser.parse_args() - - app_config = AppConfig() - try: - app_config.update_from_config_file(args.config_file) - app_config.complete_config() - except Exception as e: - print(f"Error: {str(e)}") - print("FAIL:", args.config_file) - sys.exit(1) - - if args.show: - yaml_config = app_config.config_to_dict() - yaml.dump(yaml_config, sys.stdout) - - print("PASS:", args.config_file) - sys.exit(0) - - -if __name__ == "__main__": - main() diff --git a/backend/czi_hosted/eb/check_requirements.py b/backend/czi_hosted/eb/check_requirements.py deleted file mode 100644 index 008afede..00000000 --- a/backend/czi_hosted/eb/check_requirements.py +++ /dev/null @@ -1,98 +0,0 @@ -"""This is a simple script to ensure the custom requirements.txt do not violate -the server requirements.txt. A hosted cellxgene deployment may specify the exact -version requirements on all the modules, and may add additional modules. -This script is meant to aid in making that list of custom requirements easier to maintain. -If cellxgene adds a new dependency, or changes the version requirements of an existing -dependency, then this script can check if the custom requirements are still valid""" - -import sys -import requirements -from packaging.version import Version -import pkg_resources - - -def check(expected, custom): - """checks that the custom requirements meet all the requirements of the expected requirements. - The custom set of requirements may contain additional entries than expected. - The requirements in custom must all be exact (==). - An expected requirement must be present in custom, and must match all the specs - for that requirement. - - expected : name of the expected requirement.txt file - custom : name of the custom requirements.txt file - """ - edict = parse_requirements(expected) - cdict = parse_requirements(custom) - - okay = True - - # cdict must only have exact requirements (==) - for cname, cspecs in cdict.items(): - if len(cspecs) != 1 or cspecs[0][0] != "==": - print(f"Error, spec must be an exact requirement {custom}: {cname} {str(cspecs)}") - okay = False - - for ename, especs in edict.items(): - if ename not in cdict: - print(f"Error, missing requirement from {custom}: {ename} {str(especs)}") - okay = False - continue - - cver = Version(cdict[ename][0][1]) - for espec in especs: - rokay = check_version(cver, espec[0], Version(espec[1])) - if not rokay: - print(f"Error, failed requirement from {custom}: {ename} {espec}, {cver}") - okay = False - - if okay: - print("requirements check successful") - sys.exit(0) - else: - sys.exit(1) - - -def parse_requirements(fname): - """Read a requirements file and return a dict of modules name / specification""" - try: - with open(fname, "r") as fd: - try: - # pylint: disable=no-member - rdict = {req.name: req.specs for req in requirements.parse(fd)} - except pkg_resources.RequirementParseError: - print(f"Unable to parse the requirements file: {fname}") - sys.exit(1) - except Exception as e: - print(f"Unable to open file {fname}: {str(e)}") - sys.exit(1) - - return rdict - - -# pylint: disable=too-many-return-statements -def check_version(cver, optype, ever): - """ - Simple version check. - Note: There is more complexity to comparing version (PEP440). - However the use cases in cellxgene are limited, and do not require a general solution. - """ - - if optype == "==": - return cver == ever - if optype == "!=": - return cver != ever - if optype == ">=": - return cver >= ever - if optype == ">": - return cver > ever - if optype == "<=": - return cver <= ever - if optype == "<": - return cver < ever - - print(f"Error, optype not handled: {optype}") - return False - - -if __name__ == "__main__": - check(sys.argv[1], sys.argv[2]) diff --git a/backend/czi_hosted/eb/config_deploy.yaml b/backend/czi_hosted/eb/config_deploy.yaml deleted file mode 100644 index 8c6e4cb0..00000000 --- a/backend/czi_hosted/eb/config_deploy.yaml +++ /dev/null @@ -1,2 +0,0 @@ -deploy: - artifact: artifact.zip diff --git a/backend/czi_hosted/requirements-dev.txt b/backend/czi_hosted/requirements-dev.txt deleted file mode 100644 index 12f50599..00000000 --- a/backend/czi_hosted/requirements-dev.txt +++ /dev/null @@ -1,12 +0,0 @@ -Authlib>=0.14.3 -black -bumpversion>=0.5 -codecov>=2.0.15 -parameterized>=0.7.0 -psycopg2-binary>=2.8.5 -pytest>=3.6.3 -python-jose>=3.2.0 -twine>=1.12.1 --r requirements.txt --r requirements-prepare.txt -rsa>=4.7 # not directly required, pinned by Snyk to avoid a vulnerability diff --git a/backend/czi_hosted/requirements-prepare.txt b/backend/czi_hosted/requirements-prepare.txt deleted file mode 100644 index ae6d4ca6..00000000 --- a/backend/czi_hosted/requirements-prepare.txt +++ /dev/null @@ -1,4 +0,0 @@ -python-igraph -louvain>=0.6 -scanpy -umap-learn<0.5.0 # The pinned version scanpy is not compatible with latest umap-learn diff --git a/backend/czi_hosted/requirements.txt b/backend/czi_hosted/requirements.txt deleted file mode 100644 index 504ad432..00000000 --- a/backend/czi_hosted/requirements.txt +++ /dev/null @@ -1,24 +0,0 @@ -anndata>=0.7.6 # we need to_memory(), added in 0.7.6 -boto3>=1.12.18 -click>=7.1.2 -Flask>=1.0.2,<2.0.0 # Flask 2.0 is not compatible with the latest version of Flask-RESTful (0.3.8) -Flask-Compress>=1.4.0 -Flask-Cors>=3.0.9 # CVE-2020-25032 -Flask-RESTful>=0.3.6 -flask-server-timing>=0.1.2 -flask-talisman>=0.7.0 -flatbuffers>=1.11.0,<2.0.0 # cellxgene is not compatible with 2.0.0. Requires migration -flatten-dict>=0.2.0 -fsspec>=0.4.4,<0.8.0 -gunicorn>=20.0.4 -h5py>=3.0.0 -numba>=0.51.2 -numpy>=1.17.5 -packaging>=20.0 -pandas>=1.0,!=1.1 # pandas 1.1 breaks tests, https://github.com/pandas-dev/pandas/issues/35446 -PyYAML>=5.4 # CVE-2020-14343 -scipy>=1.4 -requests>=2.22.0 -tiledb>=0.5.9,>=0.6.2,!=0.7.2, !=0.8.6 -s3fs==0.4.2 -sqlalchemy>=1.3.18 diff --git a/backend/server/Makefile b/backend/server/Makefile index 74c0dd77..bd34ec30 100644 --- a/backend/server/Makefile +++ b/backend/server/Makefile @@ -20,7 +20,3 @@ unit-test: .PHONY: test-annotations-performance test-annotations-performance: python ../test/test_server/performance/performance_test_annotations_backend.py - -.PHONY: test-annotations-scale -test-annotations-scale: - locust -f ../test/test_server/performance/scale_test_annotations.py --headless -u 30 -r 10 --host https://api.cellxgene.dev.single-cell.czi.technology/cellxgene/e/ --run-time 5m 2>&1 | tee locust_dev_stats.txt diff --git a/backend/test/fixtures/czi_hosted_dataset_config_outline.py b/backend/test/fixtures/czi_hosted_dataset_config_outline.py deleted file mode 100644 index 81ca0df7..00000000 --- a/backend/test/fixtures/czi_hosted_dataset_config_outline.py +++ /dev/null @@ -1,35 +0,0 @@ -f""" -dataset: - app: - scripts: {scripts} #list of strs (filenames) or dicts containing keys - inline_scripts: {inline_scripts} #list of strs (filenames) - - about_legal_tos: {about_legal_tos} - about_legal_privacy: {about_legal_privacy} - - authentication_enable: {authentication_enable} - - presentation: - max_categories: {max_categories} - custom_colors: {custom_colors} - - user_annotations: - enable: {enable_users_annotations} - type: {annotation_type} - hosted_tiledb_array: - db_uri: {db_uri} - hosted_file_directory: {hosted_file_directory} - local_file_csv: - directory: {local_file_csv_directory} - file: {local_file_csv_file} - - embeddings: - names: {embedding_names} - - diffexp: - enable: {enable_difexp} - lfc_cutoff: {lfc_cutoff} - top_n: {top_n} - - X_approximate_distribution: {X_approximate_distribution} -""" diff --git a/backend/test/fixtures/czi_hosted_server_config_outline.py b/backend/test/fixtures/czi_hosted_server_config_outline.py deleted file mode 100644 index a23f7d24..00000000 --- a/backend/test/fixtures/czi_hosted_server_config_outline.py +++ /dev/null @@ -1,63 +0,0 @@ -f"""server: - app: - verbose: {verbose} - debug: {debug} - host: {host} - port: {port} - open_browser: {open_browser} - force_https: {force_https} - flask_secret_key: {flask_secret_key} - generate_cache_control_headers: {generate_cache_control_headers} - server_timing_headers: {server_timing_headers} - csp_directives: {csp_directives} - api_base_url: {api_base_url} - web_base_url: {web_base_url} - authentication: - type: {auth_type} - insecure_test_environment: {insecure_test_environment} - params_oauth: - oauth_api_base_url: {oauth_api_base_url} - client_id: {client_id} - client_secret: {client_secret} - jwt_decode_options: {jwt_decode_options} - session_cookie: {session_cookie} - cookie: {cookie} - - multi_dataset: - dataroot: {dataroot} - index: {index} - allowed_matrix_types: {allowed_matrix_types} - matrix_cache: - max_datasets: {max_cached_datasets} - timelimit_s: {timelimit_s} - - single_dataset: - datapath: {dataset_datapath} - obs_names: {obs_names} - var_names: {var_names} - about: {about} - title: {title} - - diffexp: - alg_cxg: # number of threads to use is computed from: min(max_workers, cpu_multipler * cpu_count) - max_workers: {diffexp_max_workers} - cpu_multiplier: {cpu_multiplier} - target_workunit: {target_workunit} # The target number of matrix elements that are evaluated in one thread. - - data_locator: - s3: - region_name: {data_locater_region_name} - - adaptor: - cxg_adaptor: - tiledb_ctx: - sm.tile_cache_size: {cxg_tile_cache_size} - sm.num_reader_threads: {cxg_num_reader_threads} - - anndata_adaptor: - backed: {anndata_backed} - - limits: - column_request_max: {column_request_max} - diffexp_cellcount_max: {diffexp_cellcount_max} -""" diff --git a/backend/test/fixtures/database/__init__.py b/backend/test/fixtures/database/__init__.py deleted file mode 100644 index bf97d6a3..00000000 --- a/backend/test/fixtures/database/__init__.py +++ /dev/null @@ -1,79 +0,0 @@ -import string -import random - - -from sqlalchemy import func - -from backend.czi_hosted.db.cellxgene_orm import CellxGeneUser, CellxGeneDataset, Annotation, Base -from backend.czi_hosted.db.create_db import create_db -from backend.czi_hosted.db.db_utils import DbUtils - - -class TestDatabase: - def __init__(self): - local_db_uri = "postgresql://postgres:test_pw@localhost:5432" - create_db(local_db_uri) - self.db = DbUtils(local_db_uri) - self._populate_test_data() - self._populate_test_data_many() - - def _populate_test_data(self): - self._create_test_user() - self._create_test_dataset() - self._create_test_annotation() - - def _populate_test_data_many(self): - self._create_test_users() - self._create_test_datasets() - self._create_test_annotations() - - def _create_test_user(self): - user = CellxGeneUser(id="test_user_id") - user2 = CellxGeneUser(id="1234") - self.db.session.add(user) - self.db.session.add(user2) - self.db.session.commit() - - def _create_test_dataset(self): - dataset = CellxGeneDataset(name="test_dataset",) - self.db.session.add(dataset) - self.db.session.commit() - - def _create_test_annotation(self): - dataset = self.db.query([CellxGeneDataset], [CellxGeneDataset.name == "test_dataset"],)[0] - annotation = Annotation(tiledb_uri="tiledb_uri", user_id="test_user_id", dataset_id=str(dataset.id)) - self.db.session.add(annotation) - self.db.session.commit() - - @staticmethod - def get_random_string(): - letters = string.ascii_lowercase - return "".join(random.choice(letters) for i in range(12)) - - def _create_test_users(self, user_count: int = 10): - users = [] - for i in range(user_count): - users.append(CellxGeneUser(id=self.get_random_string())) - self.db.session.add_all(users) - self.db.session.commit() - - def _create_test_datasets(self, dataset_count: int = 10): - datasets = [] - for i in range(dataset_count): - datasets.append(CellxGeneDataset(name=self.get_random_string())) - self.db.session.add_all(datasets) - self.db.session.commit() - - def order_by_random(self, table: Base): - return self.db.session.query(table).order_by(func.random()).first() - - def _create_test_annotations(self, annotation_count: int = 10): - annotations = [] - for i in range(annotation_count): - dataset = self.order_by_random(CellxGeneDataset) - user = self.order_by_random(CellxGeneUser) - annotations.append( - Annotation(tiledb_uri=self.get_random_string(), user_id=user.id, dataset_id=str(dataset.id)) - ) - self.db.session.add_all(annotations) - self.db.session.commit() diff --git a/backend/test/test_czi_hosted/__init__.py b/backend/test/test_czi_hosted/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/locust/README.md b/backend/test/test_czi_hosted/locust/README.md deleted file mode 100644 index b677af6a..00000000 --- a/backend/test/test_czi_hosted/locust/README.md +++ /dev/null @@ -1,39 +0,0 @@ -# Locust Load Test - -This directory contains scripts to load test cellxgene's backend. It -primary simulates initial data loading and expression data fetch, which -are the most common data routes. It currently does not include tests -for differential expression or re-clustering routes. - -## Prerequisites - -You need: - -- Python 3.6+, and pip -- cellxgene installed -- install the locust dependencies in `requirements-locust.txt` - -## To test - -1. Choose to run cellxgene in either single dataset or data root mode. -2. Edit config.py to indicate which datasets to load: - - in single dataset mode, just set `DataSets=[""]` - - in dataroot (multi-dataset) mode, add the route names, eg, `DataSets=['foo.cxg', 'bar.cxg']` -3. Launch cellxgene in the appropriate mode -4. launch locust, specifying the correct --host argument -5. point your web browser to the locust http server, usually `http://localhost:8089/` - -### Single dataset mode - -- Edit config.py and set `DataSets=[""]` -- in a shell, run `cellxgene launch somefile.h5ad` -- launch locust in another shell, `locust --host http://localhost:5005/` (or wherever you are running cellxgene) -- point a browser to the locust port, usually http://localhost:8089/ -- run test - -### Multi-dataset mode - -- Edit config.py and set `DataSets=["datapath1", ...]` -- in a shell, run `cellxgene launch --dataroot path` - -The remainder of the steps are same as single dataset. diff --git a/backend/test/test_czi_hosted/locust/__init__.py b/backend/test/test_czi_hosted/locust/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/locust/config.py b/backend/test/test_czi_hosted/locust/config.py deleted file mode 100644 index 7b256ee2..00000000 --- a/backend/test/test_czi_hosted/locust/config.py +++ /dev/null @@ -1,15 +0,0 @@ -""" -Locust test config -""" - - -""" Data routes that will be tested """ - -# single dataset, for non-dataroot tests -# DataSets = [""] - -# multi-dataset, for dataroot tests. these are varied in size/shape -DataSets = [ - "GSE60361.cxg", - "WongAdultRetina.cxg", -] diff --git a/backend/test/test_czi_hosted/locust/locustfile.py b/backend/test/test_czi_hosted/locust/locustfile.py deleted file mode 100644 index 9e38cd7c..00000000 --- a/backend/test/test_czi_hosted/locust/locustfile.py +++ /dev/null @@ -1,165 +0,0 @@ -import json -import random - -import requests -from config import DataSets -from locust import HttpUser, SequentialTaskSet, task, between, TaskSet -from locust.clients import HttpSession -from requests.packages.urllib3.exceptions import InsecureRequestWarning - -import backend.test.decode_fbs as decode_fbs - -requests.packages.urllib3.disable_warnings(InsecureRequestWarning) - -""" -Simple locust stress test definition for cellxgene -""" - -API_SUFFIX = "api/v0.2" - - -class CellXGeneTasks(TaskSet): - """ - Simulate use against a single dataset - """ - - def on_start(self): - - self.client.verify = False - self.dataset = random.choice(DataSets) - - with self.client.get( - f"{self.dataset}/{API_SUFFIX}/schema", stream=True, catch_response=True - ) as schema_response: - if schema_response.status_code == 200: - self.schema = schema_response.json()["schema"] - else: - self.schema = None - - with self.client.get( - f"{self.dataset}/{API_SUFFIX}/config", stream=True, catch_response=True - ) as config_response: - if config_response.status_code == 200: - self.config = config_response.json()["config"] - else: - self.config = None - - with self.client.get( - f"{self.dataset}/{API_SUFFIX}/annotations/var?annotation-name={self.var_index_name()}", - headers={"Accept": "application/octet-stream"}, - catch_response=True, - ) as var_index_response: - if var_index_response.status_code == 200: - df = decode_fbs.decode_matrix_FBS(var_index_response.content) - gene_names_idx = df["col_idx"].index(self.var_index_name()) - self.gene_names = df["columns"][gene_names_idx] - else: - self.gene_names = [] - - def var_index_name(self): - if self.schema is not None: - return self.schema["annotations"]["var"]["index"] - return None - - def obs_annotation_names(self): - if self.schema is not None: - return [col["name"] for col in self.schema["annotations"]["obs"]["columns"]] - return [] - - def layout_names(self): - if self.schema is not None: - return [layout["name"] for layout in self.schema["layout"]["obs"]] - else: - return [] - - @task(2) - class InitializeClient(SequentialTaskSet): - """ - Initial loading of cellxgene - when the user hits the main route. - - Currently this sequence skips some of the static assets, which are quite small and should be served by the - HTTP server directly. - - 1. Load index.html, etc. - 2. Concurrently load /config, /schema - 3. Concurrently load /layout/obs, /annotations/var?annotation-name= - -- Does initial render -- - 4. Concurrently load all /annotations/obs and all /layouts/obs - -- Fully initialized -- - """ - - # Users hit all of the init routes as fast as they can, subject to the ordering constraints and network latency. - wait_time = between(0.01, 0.1) - - def on_start(self): - self.dataset = self.parent.dataset - self.client.verify = False - self.api_less_client = HttpSession( - base_url=self.client.base_url.replace("api.", "").replace("cellxgene/", ""), - request_success=self.client.request_success, - request_failure=self.client.request_failure, - ) - - @task - def index(self): - self.api_less_client.get(f"{self.dataset}", stream=True) - - @task - def loadConfigAndSchema(self): - self.client.get(f"{self.dataset}/{API_SUFFIX}/schema", stream=True, catch_response=True) - self.client.get(f"{self.dataset}/{API_SUFFIX}/config", stream=True, catch_response=True) - - @task - def loadBootstrapData(self): - self.client.get( - f"{self.dataset}/{API_SUFFIX}/layout/obs", headers={"Accept": "application/octet-stream"}, stream=True - ) - self.client.get( - f"{self.dataset}/{API_SUFFIX}/annotations/var?annotation-name={self.parent.var_index_name()}", - headers={"Accept": "application/octet-stream"}, - catch_response=True, - ) - - @task - def loadObsAnnotationsAndLayouts(self): - obs_names = self.parent.obs_annotation_names() - for name in obs_names: - self.client.get( - f"{self.dataset}/{API_SUFFIX}/annotations/obs?annotation-name={name}", - headers={"Accept": "application/octet-stream"}, - stream=True, - ) - - layouts = self.parent.layout_names() - for name in layouts: - self.client.get( - f"{self.dataset}/{API_SUFFIX}/annotations/obs?layout-name={name}", - headers={"Accept": "application/octet-stream"}, - stream=True, - ) - - @task - def done(self): - self.interrupt() - - @task(1) - def load_expression(self): - """ - Simulate user occasionally loading some expression data for a gene - """ - - gene_name = random.choice(self.gene_names) - filter = {"filter": {"var": {"annotation_value": [{"name": self.var_index_name(), "values": [gene_name]}]}}} - self.client.put( - f"{self.dataset}/{API_SUFFIX}/data/var", - data=json.dumps(filter), - headers={"Content-Type": "application/json", "Accept": "application/octet-stream"}, - stream=True, - ).close() - - -class CellxgeneUser(HttpUser): - tasks = [CellXGeneTasks] - - # Most ops do not require back-end interaction, so slow cadence for users - wait_time = between(10, 60) diff --git a/backend/test/test_czi_hosted/locust/requirements-locust.txt b/backend/test/test_czi_hosted/locust/requirements-locust.txt deleted file mode 100644 index c52c2541..00000000 --- a/backend/test/test_czi_hosted/locust/requirements-locust.txt +++ /dev/null @@ -1,2 +0,0 @@ -locust --r ../../../czi_hosted/requirements.txt diff --git a/backend/test/test_czi_hosted/performance/__init__.py b/backend/test/test_czi_hosted/performance/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/performance/create_test_matrix.py b/backend/test/test_czi_hosted/performance/create_test_matrix.py deleted file mode 100644 index 476b6387..00000000 --- a/backend/test/test_czi_hosted/performance/create_test_matrix.py +++ /dev/null @@ -1,44 +0,0 @@ -import anndata -import argparse -import random -import scipy -import numpy as np - - -def main(): - parser = argparse.ArgumentParser("A command to generate test h5ad files") - parser.add_argument("output", help="Name of the output file") - parser.add_argument("nobs", type=int, help="Number of observations (rows)") - parser.add_argument("nvar", type=int, help="Number of variables (columns)") - parser.add_argument("-n", "--nnz-percent", type=float, default=100, help="percent of non-zeros") - parser.add_argument("-c", "--col-shift", action="store_true", help="add a random value to each column") - parser.add_argument("--seed", type=int, default=None, help="add a random value to each column") - - args = parser.parse_args() - create_test_h5ad(args.output, args.nobs, args.nvar, args.nnz_percent, args.col_shift, args.seed) - - -def create_test_h5ad(outfile, nobs, nvar, nnz_percent=100, apply_col_shift=False, seed=None): - random.seed(seed) - np.random.seed(seed) - x = create_X_array(nobs, nvar, nnz_percent, apply_col_shift) - obsm = {"X_random": np.random.rand(nobs, 2).astype(np.float32)} - adata = anndata.AnnData(x, obsm=obsm) - adata.write(outfile) - - -def create_X_array(nobs, nvar, nnz_percent, apply_col_shift): - if nnz_percent < 100: - array = scipy.sparse.random(nobs, nvar, nnz_percent * 0.01, dtype=np.float32, format="csc") - else: - array = np.random.rand(nobs, nvar).astype(np.float32) - - if apply_col_shift: - col_shift = np.random.rand((nvar)) - array += col_shift - - return array - - -if __name__ == "__main__": - main() diff --git a/backend/test/test_czi_hosted/performance/performance_test_annotations_backend.py b/backend/test/test_czi_hosted/performance/performance_test_annotations_backend.py deleted file mode 100644 index 3272d669..00000000 --- a/backend/test/test_czi_hosted/performance/performance_test_annotations_backend.py +++ /dev/null @@ -1,216 +0,0 @@ -import json -import string -from contextlib import contextmanager -from timeit import default_timer -import concurrent.futures -import numpy as np -import requests -import sys -import pandas as pd -import random - -from backend.common.fbs.matrix import encode_matrix_fbs - -""" -Before running, sign into the dataportal, copy the cookie and paste it below. To test in staging or prod update the -url base below. It is also possible to configure the number of categories created and the number of unique labels per -category. -""" - -cookie = "" - -test_datasets = { - "smallest": { - "dataset_url": "kampmann_lab_human_AD_snRNAseq_EC_inhibitoryNeurons-53-remixed.cxg", - "name": "smallest", - "num_cells": 5270, - }, - "10k": { - "dataset_url": "krasnow_lab_human_lung_cell_atlas_smartseq2-2-remixed.cxg", - "name": "10k", - "num_cells": 9409, - }, - "80k": { - "dataset_url": "Single_cell_gene_expression_profiling_of_SARS_CoV_2_infected_human_cell_lines_H1299-27-remixed.cxg", # noqa E501 - "name": "80k", - "num_cells": 81736, - }, - "140k": {"dataset_url": "Single_cell_drug_screening_a549-42-remixed.cxg", "name": "140k", "num_cells": 143015}, - "largest": {"dataset_url": "human_cell_landscape.cxg", "name": "largest", "num_cells": 599926}, - "1million": {"dataset_url": None, "name": "1million", "num_cells": 1000000}, - "4million": {"dataset_url": None, "name": "4million", "num_cells": 4000000}, -} - -url_base = "https://api.cellxgene.dev.single-cell.czi.technology/cellxgene/e/" -annotations_category_count = [1, 10, 50] -max_labels = [5, 50, 100] - - -class PerformanceTestingAnnotations: - def __init__( - self, - datasets=test_datasets, - annotations_category_count=annotations_category_count, - max_labels=max_labels, - url_base=url_base, - ): - self.test_datasets = datasets - self.annotations_category_count = annotations_category_count - self.max_labels = max_labels - self.url_base = url_base - self.test_notes = self.create_info_dict() - - def set_cell_count(self, dataset_name): - dataset_url = self.test_datasets[dataset_name]["dataset_url"] - headers = {"Content-Type": "application/octet-stream", "Cookie": cookie} - response = self.client.get(f"{self.url_base}{dataset_url}/api/v0.2/schema", headers=headers) - cell_count = json.loads(response._content)["schema"]["dataframe"]["nObs"] - self.test_datasets[dataset_name]["cell_count"] = cell_count - - def create_info_dict(self): - request_info = {} - for dataset in self.test_datasets.keys(): - request_info[dataset] = {} - for cat_count in self.annotations_category_count: - request_info[dataset][f"num_categories_{cat_count}"] = {} - for unique_labels in self.max_labels: - request_info[dataset][f"num_categories_{cat_count}"][f"max_label_{unique_labels}"] = {} - return request_info - - def create_annotations_dict_multi_process(self, dataset_name, category_count, label_max): - annotation_dict = {} - futures = [] - categories = [f"Category{i}" for i in range(category_count)] - if not self.test_datasets[dataset_name]["num_cells"]: - self.set_cell_count(dataset_name) - with concurrent.futures.ProcessPoolExecutor(max_workers=5) as executor: - for category in categories: - futures.append( - executor.submit( - self.build_array_for_category, - category, - self.test_datasets[dataset_name]["num_cells"], - label_max, - ) - ) - for future in concurrent.futures.as_completed(futures): - try: - result = future.result() - category_name, cells = result - annotation_dict[category_name] = pd.Series(cells, dtype="category") - except Exception as e: - print(f"Issue creating the annotations dict: {e}") - return annotation_dict - - def build_array_for_category(self, category_name, cell_count, label_max): - unique_label_count = label_max - labels = self.generate_labels(unique_label_count) - cells_per_label = int(cell_count / len(labels)) - extra = cell_count % len(labels) - cells = [] - for label in labels: - cells.extend([label] * cells_per_label) - cells.extend(["extra"] * extra) - rng = np.random.default_rng() - rng.shuffle(cells) - return category_name, cells - - @staticmethod - def convert_to_fbs(annotation_dict): - df = pd.DataFrame(annotation_dict) - return encode_matrix_fbs(matrix=df, row_idx=None, col_idx=df.columns) - - @staticmethod - def generate_labels(unique_label_count): - labels = ["undefined"] - for i in range(unique_label_count): - length = random.randrange(10, 20) - labels.append(f"{i}__" + "".join(random.choice(string.ascii_letters) for z in range(length))) - return labels - - @contextmanager - def elapsed_timer(self): - start = default_timer() - elapser = lambda: default_timer() - start # noqa E731 - yield lambda: elapser() - end = default_timer() - elapser = lambda: end - start # noqa E731 - - def create_matrix(self, dataset_name, num_cat, max_labels): - with self.elapsed_timer() as elapsed: - annon_dict = self.create_annotations_dict_multi_process(dataset_name, num_cat, max_labels) - dict_size = sum(sys.getsizeof(value) for value in annon_dict.values()) / 1024 ** 2 - self.test_notes[dataset_name][f"num_categories_{num_cat}"][f"max_label_{max_labels}"]["annotation_dict"] = { - "creation_time": str(elapsed()), - "size": f"{dict_size} mb", - } - df = pd.DataFrame(annon_dict) - df_size = sys.getsizeof(df) / 1024 ** 2 - self.test_notes[dataset_name][f"num_categories_{num_cat}"][f"max_label_{max_labels}"]["data_frame"] = { - "creation_time": str(elapsed()), - "size": f"{df_size} mb", - } - try: - matrix = encode_matrix_fbs(matrix=df, row_idx=None, col_idx=df.columns) - matrix_size = sys.getsizeof(matrix) / 1024 ** 2 - self.test_notes[dataset_name][f"num_categories_{num_cat}"][f"max_label_{max_labels}"]["fbs_matrix"] = { - "creation_time": str(elapsed()), - "size": f"{matrix_size} mb", - } - return matrix - except Exception as e: - print(f"Issue creating fbs matrix: {e}, for {dataset_name}") - return [] - - def send_put_request(self, dataset_url, data): - url = self.url_base + f"{dataset_url}/api/v0.2/annotations/obs" - with self.elapsed_timer() as elapsed: - try: - headers = {"Content-Type": "application/octet-stream", "Cookie": cookie} - response = requests.put(url=url, data=data, headers=headers) - except Exception as e: - print(f"Issue with put request: {e}") - return None, elapsed() - return response, elapsed() - - def test_categories_max_label_matrix(self, dataset_name): - for unique_labels in self.max_labels: - for category_count in self.annotations_category_count: - print(f"Starting dataset: {dataset_name}, categories: {category_count}, labels: {unique_labels}") - fbs_matrix = self.create_matrix(dataset_name, category_count, unique_labels) - if self.test_datasets[dataset_name]["dataset_url"] and fbs_matrix: - response, response_time = self.send_put_request( - self.test_datasets[dataset_name]["dataset_url"], fbs_matrix - ) - if response is None: - self.test_notes[dataset_name][f"num_categories_{category_count}"][f"max_label_{unique_labels}"][ - "put_request" - ] = {"response_status": "failed", "request_time": str(response_time)} - else: - self.test_notes[dataset_name][f"num_categories_{category_count}"][f"max_label_{unique_labels}"][ - "put_request" - ] = {"response_status": response.status_code, "request_time": str(response_time)} - - -def test_all_datasets(): - """ - Run time is dependent on number of datasets, dataset size, number of categories/number being tested and number of - unique label counts being tested. However it generally takes a long time. I recommend running this in tmux - """ - perf_test = PerformanceTestingAnnotations() - for dataset_name in perf_test.test_datasets.keys(): - print(f"Testing annotation creation for: {dataset_name}") - try: - perf_test.test_categories_max_label_matrix(dataset_name) - except Exception as e: - print(f"something went wrong with {dataset_name}: {e}") - return perf_test.test_notes - - -def main(): - notes = test_all_datasets() - print(notes) - - -if __name__ == "__main__": - main() diff --git a/backend/test/test_czi_hosted/performance/run_diffexp.py b/backend/test/test_czi_hosted/performance/run_diffexp.py deleted file mode 100644 index cb6fa847..00000000 --- a/backend/test/test_czi_hosted/performance/run_diffexp.py +++ /dev/null @@ -1,116 +0,0 @@ -import sys -import argparse -import random -import time -import numpy as np - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.czi_hosted.compute import diffexp_cxg -from backend.common.compute import diffexp_generic -from backend.czi_hosted.data_common.matrix_loader import MatrixDataLoader -from backend.czi_hosted.data_cxg.cxg_adaptor import CxgAdaptor - - -def main(): - parser = argparse.ArgumentParser("A command to test diffexp") - parser.add_argument("dataset", help="name of a dataset to load") - parser.add_argument("-na", "--numA", type=int, help="number of rows in group A") - parser.add_argument("-nb", "--numB", type=int, help="number of rows in group B") - parser.add_argument("-va", "--varA", help="obs variable:value to use for group A") - parser.add_argument("-vb", "--varB", help="obs variable:value to use for group B") - parser.add_argument("-t", "--trials", default=1, type=int, help="number of trials") - parser.add_argument( - "-a", "--alg", choices=("default", "generic", "cxg"), default="default", help="algorithm to use" - ) - parser.add_argument("-s", "--show", default=False, action="store_true", help="show the results") - parser.add_argument( - "-n", "--new-selection", default=False, action="store_true", help="change the selection between each trial" - ) - parser.add_argument("--seed", default=1, type=int, help="set the random seed") - - args = parser.parse_args() - - app_config = AppConfig() - app_config.update_server_config(single_dataset__datapath=args.dataset) - app_config.update_server_config(app__verbose=True) - app_config.complete_config() - - loader = MatrixDataLoader(args.dataset) - adaptor = loader.open(app_config) - - if args.show: - if isinstance(adaptor, CxgAdaptor): - adaptor.open_array("X").schema.dump() - - random.seed(args.seed) - np.random.seed(args.seed) - rows = adaptor.get_shape()[0] - - if args.numA: - filterA = random.sample(range(rows), args.numA) - elif args.varA: - vname, vval = args.varA.split(":") - filterA = get_filter_from_obs(adaptor, vname, vval) - else: - print("must supply numA or varA") - sys.exit(1) - - if args.numB: - filterB = random.sample(range(rows), args.numB) - elif args.varB: - vname, vval = args.varB.split(":") - filterB = get_filter_from_obs(adaptor, vname, vval) - else: - print("must supply numB or varB") - sys.exit(1) - - for i in range(args.trials): - if args.new_selection: - if args.numA: - filterA = random.sample(range(rows), args.numA) - if args.numB: - filterB = random.sample(range(rows), args.numB) - - maskA = np.zeros(rows, dtype=bool) - maskA[filterA] = True - maskB = np.zeros(rows, dtype=bool) - maskB[filterB] = True - - t1 = time.time() - if args.alg == "default": - results = adaptor.compute_diffexp_ttest(maskA, maskB) - elif args.alg == "generic": - results = diffexp_generic.diffexp_ttest(adaptor, maskA, maskB) - elif args.alg == "cxg": - if not isinstance(adaptor, CxgAdaptor): - print("cxg only works with CxgAdaptor") - sys.exit(1) - results = diffexp_cxg.diffexp_ttest(adaptor, maskA, maskB) - - t2 = time.time() - print("TIME=", t2 - t1) - - if args.show: - for res in results: - print(res) - - -def get_filter_from_obs(adaptor, obsname, obsval): - attrs = adaptor.get_obs_columns() - if obsname not in attrs: - print(f"Unknown obs attr {obsname}: expected on of {attrs}") - sys.exit(1) - obsvals = adaptor.query_obs_array(obsname)[:] - obsval = type(obsvals[0])(obsval) - - vfilter = np.where(obsvals == obsval)[0] - if len(vfilter) == 0: - u = np.unique(obsvals) - print(f"Unknown value in variable {obsname}:{obsval}: expected one of {list(u)}") - sys.exit(1) - - return vfilter - - -if __name__ == "__main__": - main() diff --git a/backend/test/test_czi_hosted/performance/scale_test_annotations.py b/backend/test/test_czi_hosted/performance/scale_test_annotations.py deleted file mode 100644 index f671c3f0..00000000 --- a/backend/test/test_czi_hosted/performance/scale_test_annotations.py +++ /dev/null @@ -1,45 +0,0 @@ -import time -import random - -from locust import HttpUser, between, task - -random.seed(time.time()) -""" -To run this script sign into cellxgene in the desired environment and grab the returned cookie, update the cookie -variable below with your cookie and run the following command to see results in the terminal: -locust -f backend/test/test_czi_hosted/performance/scale_test_annotations.py --headless -u 30 -r 10 --host https://api.cellxgene.dev.single-cell.czi.technology/cellxgene/e/ --run-time 5m 2>&1 | tee locust_dev_stats.txt - -Or if you want to use the locust gui run: -locust -f backend/test/test_czi_hosted/performance/scale_test_annotations.py -u 30 -r 10 --host https://api.cellxgene.dev.single-cell.czi.technology/cellxgene/e/ - -If you want to test staging you'll need to substitute staging for dev in the host url -To test prod you'll need to replace dev.single-cell.czi.technology with cziscience.com -If you'd like to test additional datasets you'll need to add them to the dataset_urls array - -Todo @mdunitz update script to retrieve different annotation categories -- may need to create them to ensure the -categories are shared across datasets for a given user. -""" -cookie = "" - - -class WebsiteUser(HttpUser): - wait_time = between(1, 2) - dataset_urls = [ - "human_cell_landscape.cxg", - "Single_cell_drug_screening_a549-42-remixed.cxg", - "krasnow_lab_human_lung_cell_atlas_smartseq2-2-remixed.cxg", - "Single_cell_gene_expression_profiling_of_SARS_CoV_2_infected_human_cell_lines_H1299-27-remixed.cxg", - ] - - @task - def get_annotations(self): - dataset_url = random.choice(self.dataset_urls) - url = f"{dataset_url}/api/v0.2/annotations/obs?annotation-name=cell_type" - headers = {"Content-Type": "application/octet-stream", "Cookie": cookie} - self.client.get(url, headers=headers) - - @task - def get_schema(self): - dataset_url = random.choice(self.dataset_urls) - headers = {"Content-Type": "application/octet-stream", "Cookie": cookie} - self.client.get(f"{dataset_url}/api/v0.2/schema", headers=headers) diff --git a/backend/test/test_czi_hosted/test_database/__init__.py b/backend/test/test_czi_hosted/test_database/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/test_database/test_database.py b/backend/test/test_czi_hosted/test_database/test_database.py deleted file mode 100644 index 18ffe1c6..00000000 --- a/backend/test/test_czi_hosted/test_database/test_database.py +++ /dev/null @@ -1,63 +0,0 @@ -import unittest -from backend.czi_hosted.db.cellxgene_orm import CellxGeneUser, CellxGeneDataset, Annotation -from backend.czi_hosted.db.db_utils import DbUtils -from backend.test.fixtures.database import TestDatabase - - -class DatabaseTest(unittest.TestCase): - db = DbUtils("postgresql://postgres:test_pw@localhost:5432") - - @classmethod - def setUpClass(cls) -> None: - TestDatabase() - - @classmethod - def tearDownClass(cls) -> None: - del cls.db - - def test_user_creation(self): - one_user = self.db.get(table=CellxGeneUser, entity_id="test_user_id") - self.assertEqual(one_user.id, "test_user_id") - user_count = self.db.session.query(CellxGeneUser).count() - self.assertGreater(user_count, 10) - - def test_dataset_creation(self): - one_dataset = self.db.query( - table_args=[CellxGeneDataset], filter_args=[CellxGeneDataset.name == "test_dataset"] - ) - self.assertEqual(one_dataset[0].name, "test_dataset") - dataset_count = self.db.session.query(CellxGeneDataset).count() - self.assertGreater(dataset_count, 10) - - def test_annotation_creation(self): - one_annotation = self.db.query(table_args=[Annotation], filter_args=[Annotation.tiledb_uri == "tiledb_uri"])[0] - self.assertEqual(one_annotation.tiledb_uri, "tiledb_uri") - annotation_count = self.db.session.query(Annotation).count() - self.assertGreater(annotation_count, 10) - - def test_get_most_recent_annotation_for_user_dataset(self): - dataset_id = str( - self.db.query(table_args=[CellxGeneDataset], filter_args=[CellxGeneDataset.name == "test_dataset"])[0].id - ) - - # have to commit separately because created_at time written on the db server - self.db.session.add(Annotation(dataset_id=dataset_id, user_id="test_user_id", tiledb_uri="tiledb_uri_0")) - self.db.session.commit() - - self.db.session.add(Annotation(dataset_id=dataset_id, user_id="test_user_id", tiledb_uri="tiledb_uri_1")) - self.db.session.commit() - - self.db.session.add(Annotation(dataset_id=dataset_id, user_id="test_user_id", tiledb_uri="tiledb_uri_2")) - self.db.session.commit() - - self.db.session.add(Annotation(dataset_id=dataset_id, user_id="test_user_id", tiledb_uri="tiledb_uri_3")) - self.db.session.commit() - - self.db.session.add(Annotation(dataset_id=dataset_id, user_id="test_user_id", tiledb_uri="tiledb_uri_4")) - self.db.session.commit() - - most_recent_annotation = self.db.query_for_most_recent( - Annotation, [Annotation.dataset_id == dataset_id, Annotation.user_id == "test_user_id"] - ) - - self.assertEqual(most_recent_annotation.tiledb_uri, "tiledb_uri_4") diff --git a/backend/test/test_czi_hosted/unit/__init__.py b/backend/test/test_czi_hosted/unit/__init__.py deleted file mode 100644 index 31af2bd3..00000000 --- a/backend/test/test_czi_hosted/unit/__init__.py +++ /dev/null @@ -1,180 +0,0 @@ -import logging -import shutil -import tempfile -import unittest - -from os import path - -import pandas as pd -from flask_compress import Compress -from flask_cors import CORS - -from backend.czi_hosted.common.annotations.hosted_tiledb import AnnotationsHostedTileDB -from backend.czi_hosted.common.annotations.local_file_csv import AnnotationsLocalFile -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.utils.data_locator import DataLocator -from backend.common.fbs.matrix import encode_matrix_fbs -from backend.czi_hosted.data_common.matrix_loader import MatrixDataType, MatrixDataLoader -from backend.czi_hosted.db.db_utils import DbUtils -from backend.czi_hosted.app.app import Server -from backend.test import PROJECT_ROOT, FIXTURES_ROOT - - -def data_with_tmp_tiledb_annotations(ext: MatrixDataType): - tmp_dir = tempfile.mkdtemp() - fname = { - MatrixDataType.H5AD: f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad", - MatrixDataType.CXG: "test/fixtures/pbmc3k.cxg", - }[ext] - data_locator = DataLocator(fname) - config = AppConfig() - config.update_server_config( - app__flask_secret_key="secret", - multi_dataset__dataroot=data_locator.path, - authentication__type="test", - authentication__insecure_test_environment=True, - ) - config.update_default_dataset_config( - embeddings__names=["umap"], - presentation__max_categories=100, - diffexp__lfc_cutoff=0.01, - user_annotations__type="hosted_tiledb_array", - user_annotations__hosted_tiledb_array__db_uri="postgresql://postgres:test_pw@localhost:5432", - user_annotations__hosted_tiledb_array__hosted_file_directory=tmp_dir, - ) - - config.complete_config() - - data = MatrixDataLoader(data_locator.abspath()).open(config) - annotations = AnnotationsHostedTileDB( - { - "user-annotations": True, - "genesets-save": False, - }, - tmp_dir, - DbUtils("postgresql://postgres:test_pw@localhost:5432"), - ) - return data, tmp_dir, annotations - - -def data_with_tmp_annotations(ext: MatrixDataType, annotations_fixture=False): - tmp_dir = tempfile.mkdtemp() - annotations_file = path.join(tmp_dir, "test_annotations.csv") - if annotations_fixture: - shutil.copyfile(f"{FIXTURES_ROOT}/pbmc3k-annotations.csv", annotations_file) - fname = { - MatrixDataType.H5AD: f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad", - MatrixDataType.CXG: f"{FIXTURES_ROOT}/pbmc3k.cxg", - }[ext] - data_locator = DataLocator(fname) - config = AppConfig() - config.update_server_config( - app__flask_secret_key="secret", - single_dataset__obs_names=None, - single_dataset__var_names=None, - single_dataset__datapath=data_locator.path, - ) - config.update_default_dataset_config( - embeddings__names=["umap"], - presentation__max_categories=100, - diffexp__lfc_cutoff=0.01, - ) - - config.complete_config() - data = MatrixDataLoader(data_locator.abspath()).open(config) - annotations = AnnotationsLocalFile( - { - "user-annotations": True, - "genesets-save": False, - }, - None, - annotations_file, - ) - return data, tmp_dir, annotations, config - - -def make_fbs(data): - df = pd.DataFrame(data) - return encode_matrix_fbs(matrix=df, row_idx=None, col_idx=df.columns) - - -def skip_if(condition, reason: str): - def decorator(f): - def wraps(self, *args, **kwargs): - if condition(self): - self.skipTest(reason) - else: - f(self, *args, **kwargs) - - return wraps - - return decorator - - -def app_config(data_locator, backed=False, extra_server_config={}, extra_dataset_config={}): - config = AppConfig() - config.update_server_config( - app__flask_secret_key="secret", - single_dataset__obs_names=None, - single_dataset__var_names=None, - adaptor__anndata_adaptor__backed=backed, - single_dataset__datapath=data_locator, - limits__diffexp_cellcount_max=None, - limits__column_request_max=None, - ) - config.update_default_dataset_config( - embeddings__names=["umap", "tsne", "pca"], presentation__max_categories=100, diffexp__lfc_cutoff=0.01 - ) - config.update_server_config(**extra_server_config) - config.update_default_dataset_config(**extra_dataset_config) - config.complete_config() - return config - - -class TestServer(Server): - def __init__(self, app_config): - super().__init__(app_config) - - @staticmethod - def _before_adding_routes(app, app_config): - app.config["COMPRESS_MIMETYPES"] = [ - "text/html", - "text/css", - "text/xml", - "application/json", - "application/javascript", - "application/octet-stream", - ] - Compress(app) - if app_config.server_config.app__debug: - CORS(app, supports_credentials=True) - - -class BaseTest(unittest.TestCase): - @classmethod - def setUpClass(cls, app_config=None): - cls.TEST_URL_BASE = "/d/pbmc3k.cxg/api/v0.2/" - cls.maxDiff = None - cls.app = cls.create_app(app_config) - - @classmethod - def create_app(cls, app_config=None): - if not app_config: - app_config = AppConfig() - app_config.update_server_config( - authentication__type="test", - authentication__insecure_test_environment=True, - app__flask_secret_key="testing", - app__debug=True, - multi_dataset__dataroot=f"{FIXTURES_ROOT}", - multi_dataset__index=True, - multi_dataset__allowed_matrix_types=["cxg"] - ) - app_config.complete_config(logging.info) - - app = TestServer(app_config).app - - app.testing = True - app.debug = True - - return app diff --git a/backend/test/test_czi_hosted/unit/auth/__init__.py b/backend/test/test_czi_hosted/unit/auth/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/auth/test_auth.py b/backend/test/test_czi_hosted/unit/auth/test_auth.py deleted file mode 100644 index 67a7fdcb..00000000 --- a/backend/test/test_czi_hosted/unit/auth/test_auth.py +++ /dev/null @@ -1,168 +0,0 @@ -import json -import unittest - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import FIXTURES_ROOT -from backend.test.test_czi_hosted.unit import BaseTest - - -class AuthTest(BaseTest): - def setUp(self): - self.dataset_dataroot = FIXTURES_ROOT - - def test_auth_none(self): - app_config = AppConfig() - app_config.update_server_config(app__flask_secret_key="secret") - app_config.update_server_config(authentication__type=None, multi_dataset__dataroot=self.dataset_dataroot) - app_config.update_default_dataset_config(user_annotations__enable=False) - - app_config.complete_config() - server= self.create_app(app_config) - server.testing = True - session = server.test_client() - config = json.loads(session.get(f"{self.TEST_URL_BASE}config").data) - userinfo = json.loads(session.get(f"{self.TEST_URL_BASE}userinfo").data) - self.assertNotIn("authentication", config["config"]) - self.assertIsNone(userinfo) - - def test_auth_session(self): - app_config = AppConfig() - app_config.update_server_config(app__flask_secret_key="secret") - app_config.update_server_config(authentication__type="session", multi_dataset__dataroot=self.dataset_dataroot) - app_config.update_default_dataset_config(user_annotations__enable=True) - app_config.complete_config() - - server = self.create_app(app_config) - server.auth.is_user_authenticated = lambda: True - server.testing = True - session = server.test_client() - config = json.loads(session.get(f"{self.TEST_URL_BASE}config").data) - userinfo = json.loads(session.get(f"{self.TEST_URL_BASE}userinfo").data) - - self.assertFalse(config["config"]["authentication"]["requires_client_login"]) - self.assertTrue(userinfo["userinfo"]["is_authenticated"]) - self.assertEqual(userinfo["userinfo"]["username"], "anonymous") - - def test_auth_test(self): - app_config = AppConfig() - app_config.update_server_config(app__flask_secret_key="secret") - app_config.update_server_config(authentication__type="test") - app_config.update_server_config(authentication__insecure_test_environment=True) - app_config.update_server_config( - multi_dataset__dataroot=dict( - a1=dict(dataroot=self.dataset_dataroot, base_url="auth"), - a2=dict(dataroot=self.dataset_dataroot, base_url="no-auth"), - ) - ) - - # specialize the configs - app_config.add_dataroot_config("a1", app__authentication_enable=True, user_annotations__enable=True) - app_config.add_dataroot_config("a2", app__authentication_enable=False, user_annotations__enable=False) - - app_config.complete_config() - - server=self.create_app(app_config) - server.testing = True - session = server.test_client() - - # auth datasets - config = json.loads(session.get("/auth/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get(f"/auth/pbmc3k.cxg/api/v0.2/userinfo").data) - - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - self.assertTrue(config["config"]["authentication"]["requires_client_login"]) - self.assertTrue(config["config"]["parameters"]["annotations"]) - - login_uri = config["config"]["authentication"]["login"] - logout_uri = config["config"]["authentication"]["logout"] - - self.assertEqual(login_uri, "/login?dataset=auth/pbmc3k.cxg") - self.assertEqual(logout_uri, "/logout?dataset=auth/pbmc3k.cxg") - - response = session.get(login_uri) - # check that the login redirect worked - - self.assertEqual(response.status_code, 302) - self.assertEqual(response.headers['Location'], 'http://localhost/auth/pbmc3k.cxg') - config = json.loads(session.get("/auth/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get("/auth/pbmc3k.cxg/api/v0.2/userinfo").data) - - self.assertTrue(userinfo["userinfo"]["is_authenticated"]) - self.assertEqual(userinfo["userinfo"]["username"], "test_account") - self.assertEqual(userinfo["userinfo"]["picture"], None) - self.assertTrue(config["config"]["parameters"]["annotations"]) - - response = session.get(logout_uri) - # check that the logout redirect worked - - self.assertEqual(response.status_code, 302) - config = json.loads(session.get("/auth/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get("/auth/pbmc3k.cxg/api/v0.2/userinfo").data) - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - self.assertTrue(config["config"]["parameters"]["annotations"]) - - # no-auth datasets - config = json.loads(session.get("/no-auth/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get("/no-auth/pbmc3k.cxg/api/v0.2/userinfo").data) - self.assertIsNone(userinfo) - self.assertFalse(config["config"]["parameters"]["annotations"]) - - # login with a picture - session.get(f"{login_uri}&picture=myimage.png") - userinfo = json.loads(session.get("/auth/pbmc3k.cxg/api/v0.2/userinfo").data) - self.assertTrue(userinfo["userinfo"]["is_authenticated"]) - self.assertEqual(userinfo["userinfo"]["picture"], "myimage.png") - - def test_auth_test_single(self): - app_config = AppConfig() - app_config.update_server_config(app__flask_secret_key="secret") - app_config.update_server_config( - authentication__type="test", single_dataset__datapath=f"{self.dataset_dataroot}/pbmc3k.cxg" - ) - app_config.update_server_config(authentication__insecure_test_environment=True) - - app_config.complete_config() - - server = self.create_app(app_config) - server.testing = True - session = server.test_client() - - config = json.loads(session.get("/api/v0.2/config").data) - userinfo = json.loads(session.get("/api/v0.2/userinfo").data) - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - self.assertTrue(config["config"]["authentication"]["requires_client_login"]) - self.assertTrue(config["config"]["parameters"]["annotations"]) - - login_uri = config["config"]["authentication"]["login"] - logout_uri = config["config"]["authentication"]["logout"] - - self.assertEqual(login_uri, "/login") - self.assertEqual(logout_uri, "/logout") - - - # check that the login redirect worked - with server.test_client() as session: - response = session.get(login_uri) - self.assertEqual(response.status_code, 302) - self.assertEqual(response.headers['Location'], "http://localhost/") - - config = json.loads(session.get("api/v0.2/config").data) - userinfo = json.loads(session.get("/api/v0.2/userinfo").data) - self.assertTrue(userinfo["userinfo"]["is_authenticated"]) - self.assertEqual(userinfo["userinfo"]["username"], "test_account") - self.assertTrue(config["config"]["parameters"]["annotations"]) - - response = session.get(logout_uri) - # check that the logout redirect worked - - self.assertEqual(response.status_code, 302) - self.assertEqual(response.headers['Location'], "http://localhost/") - config = json.loads(session.get("/api/v0.2/config").data) - - userinfo = json.loads(session.get("/api/v0.2/userinfo").data) - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - self.assertTrue(config["config"]["parameters"]["annotations"]) diff --git a/backend/test/test_czi_hosted/unit/auth/test_oauth.py b/backend/test/test_czi_hosted/unit/auth/test_oauth.py deleted file mode 100644 index f88d24f1..00000000 --- a/backend/test/test_czi_hosted/unit/auth/test_oauth.py +++ /dev/null @@ -1,229 +0,0 @@ -import unittest -import random -import time -import base64 -import json -import requests - -from flask import Flask, jsonify, make_response, request, redirect -from multiprocessing import Process - -import jose -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import FIXTURES_ROOT - -# This tests the oauth authentication type. -# This test starts a cellxgene server and a mock oauth server. -# API requests to login and logout and get the userinfo are made -# to the cellxgene server, which then sends requests to the mock -# oauth server. - -# number of seconds that the oauth token is valid -from backend.test.test_czi_hosted.unit import BaseTest - -TOKEN_EXPIRES = 2 - -# Create a mocked out oauth token, which servers all the endpoints needed by the oauth type. -mock_oauth_app = Flask("mock_oauth_app") - - -@mock_oauth_app.route("/authorize") -def authorize(): - callback = request.args.get("redirect_uri") - state = request.args.get("state") - return redirect(callback + f"?code=fakecode&state={state}") - - -@mock_oauth_app.route("/oauth/token", methods=["POST"]) -def token(): - now = time.time() - expires_at = now + TOKEN_EXPIRES - headers = dict(alg="RS256", kid="fake_kid") - payload = dict(name="fake_user", sub="fake_id", email="fake_user@email.com", email_verified=True, exp=expires_at) - jwt = jose.jwt.encode(claims=payload, key="mysecret", algorithm="HS256", headers=headers) - r = { - "access_token": f"access-{now}", - "id_token": jwt, - "refresh_token": f"random-{now}", - "scope": "openid profile email", - "expires_in": TOKEN_EXPIRES, - "token_type": "Bearer", - "expires_at": expires_at, - } - return make_response(jsonify(r)) - - -@mock_oauth_app.route("/v2/logout") -def logout(): - return_to = request.args.get("returnTo") - return redirect(return_to) - - -@mock_oauth_app.route("/.well-known/jwks.json") -def jwks(): - data = dict(alg="RS256", kty="RSA", use="sig", kid="fake_kid",) - return make_response(jsonify(dict(keys=[data]))) - - -# function to launch the mock oauth server -def launch_mock_oauth(mock_port): - mock_oauth_app.run(port=mock_port) - - -class AuthTest(BaseTest): - @classmethod - def setUpClass(cls): - # The port that the mock oauth server will listen on - cls.mock_port = random.randint(10000, 12000) - cls.dataset_dataroot = FIXTURES_ROOT - cls.mock_oauth_process = Process(target=launch_mock_oauth, args=(cls.mock_port,)) - cls.mock_oauth_process.start() - - # Verify that the mock oauth server is ready (accepting requests) before starting the tests. - - # The following lines are polling until the mock server is ready. - # The issue is we are starting a mock oauth server, then we are starting a cellxgene server, - # which will start making requests to the mock oauth server. - # So there is a race condition because the mock oauth server needs to be ready before it gets requests. - # We check to see if it is ready, and if not we wait 1 second, then try again. - # If it gets to 5 seconds, which is shouldn't, we assume something has gone wrong and fail the test. - server_okay = False - for _ in range(5): - try: - response = requests.get(f"http://localhost:{cls.mock_port}/.well-known/jwks.json") - if response.status_code == 200: - server_okay = True - break - except: # noqa: E722 - pass - - # wait one second and try again - time.sleep(1) - - assert(server_okay) - - @classmethod - def tearDownClass(cls): - cls.mock_oauth_process.terminate() - - def auth_flow(self, app_config, cookie_key=None): - - app_config.update_server_config( - app__api_base_url="local", - authentication__type="oauth", - authentication__params_oauth__oauth_api_base_url=f"http://localhost:{self.mock_port}", - authentication__params_oauth__client_id="mock_client_id", - authentication__params_oauth__client_secret="mock_client_secret", - authentication__params_oauth__jwt_decode_options={"verify_signature": False, "verify_iss": False}, - ) - - app_config.update_server_config(multi_dataset__dataroot=self.dataset_dataroot) - app_config.complete_config() - - server= self.create_app(app_config) - server.testing = True - session = server.test_client() - - # auth datasets - config = json.loads(session.get("/d/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get("/d/pbmc3k.cxg/api/v0.2/userinfo").data) - - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - self.assertTrue(config["config"]["authentication"]["requires_client_login"]) - self.assertTrue(config["config"]["parameters"]["annotations"]) - - login_uri = config["config"]["authentication"]["login"] - logout_uri = config["config"]["authentication"]["logout"] - - self.assertEqual(login_uri, "http://localhost:5005/login?dataset=d/pbmc3k.cxg/") - self.assertEqual(logout_uri, "http://localhost:5005/logout?dataset=d/pbmc3k.cxg/") - - response = session.get(login_uri) - # check that the login redirect worked - - self.assertEqual(response.status_code, 302) - - config = json.loads(session.get("/d/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get("/d/pbmc3k.cxg/api/v0.2/userinfo").data) - - self.assertTrue(userinfo["userinfo"]["is_authenticated"]) - self.assertEqual(userinfo["userinfo"]["username"], "fake_user") - self.assertEqual(userinfo["userinfo"]["email"], "fake_user@email.com") - self.assertTrue(config["config"]["parameters"]["annotations"]) - - if cookie_key: - cookie = session.cookies.get(cookie_key) - token = json.loads(base64.b64decode(cookie)) - access_token_before = token.get("access_token") - id_token_before = token.get("id_token") - - # let the token expire - time.sleep(TOKEN_EXPIRES + 1) - - # check that refresh works - session.get(login_uri) - userinfo = json.loads(session.get(f"/d/pbmc3k.cxg/api/v0.2/userinfo").data) - self.assertTrue(userinfo["userinfo"]["is_authenticated"]) - self.assertEqual(userinfo["userinfo"]["username"], "fake_user") - - cookie = session.cookies.get(cookie_key) - token = json.loads(base64.b64decode(cookie)) - access_token_after = token.get("access_token") - id_token_after = token.get("id_token") - - self.assertNotEqual(access_token_before, access_token_after) - self.assertNotEqual(id_token_before, id_token_after) - - # invalid cookie is rejected - session.cookies.set(cookie_key, "TEST_" + cookie) - self.assertTrue(cookie_key in session.cookies) - response = session.get(f"{server}/d/pbmc3k.cxg/api/v0.2/userinfo") - # this is not an error, the invalid cookie is just ignored. - self.assertEqual(response.status_code, 200) - userinfo = json.loads(response.data) - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - - # invalid id_token is rejected - test_token = token - test_token["id_token"] = "TEST_" + id_token_after - encoded_cookie = base64.b64encode(json.dumps(test_token).encode()).decode() - session.cookies.set(cookie_key, encoded_cookie) - response = session.get(f"{server}/d/pbmc3k.cxg/api/v0.2/userinfo") - # this is not an error, the invalid id_token is just ignored. - self.assertEqual(response.status_code, 200) - userinfo = json.loads(response.data) - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - - r = session.get(logout_uri) - # check that the logout redirect worked - - self.assertEqual(r.history[0].status_code, 302) - self.assertEqual(r.url, f"{server}/d/pbmc3k.cxg/") - config = json.loads(session.get(f"{server}/d/pbmc3k.cxg/api/v0.2/config").data) - userinfo = json.loads(session.get(f"{server}/d/pbmc3k.cxg/api/v0.2/userinfo").data) - self.assertFalse(userinfo["userinfo"]["is_authenticated"]) - self.assertIsNone(userinfo["userinfo"]["username"]) - self.assertTrue(config["config"]["parameters"]["annotations"]) - - @unittest.skip("turn on when we utilizing auth in the explorer") - def test_auth_oauth_session(self): - # test with session cookies - app_config = AppConfig() - app_config.update_server_config(app__flask_secret_key="secret") - app_config.update_server_config(authentication__params_oauth__session_cookie=True,) - self.auth_flow(app_config) - - @unittest.skip("turn on when we utilizing auth in the explorer") - def test_auth_oauth_cookie(self): - # test with specified cookie - app_config = AppConfig() - app_config.update_server_config(app__flask_secret_key="secret") - app_config.update_server_config( - authentication__params_oauth__session_cookie=False, - authentication__params_oauth__cookie=dict(key="test_cxguser", httponly=True, max_age=60), - ) - - self.auth_flow(app_config, "test_cxguser") diff --git a/backend/test/test_czi_hosted/unit/cli/__init__.py b/backend/test/test_czi_hosted/unit/cli/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/cli/test_launch.py b/backend/test/test_czi_hosted/unit/cli/test_launch.py deleted file mode 100644 index 5550e775..00000000 --- a/backend/test/test_czi_hosted/unit/cli/test_launch.py +++ /dev/null @@ -1,27 +0,0 @@ -import filecmp -import os -import shutil -import unittest - -import yaml - -from backend.czi_hosted.default_config import default_config -from backend.test import FIXTURES_ROOT - - -class CLIPLaunchTests(unittest.TestCase): - tmp_dir = os.path.join(FIXTURES_ROOT, "dump_configs") - - @classmethod - def setUpClass(cls) -> None: - os.mkdir(cls.tmp_dir) - - @classmethod - def tearDownClass(cls) -> None: - shutil.rmtree(cls.tmp_dir) - - def test_dump_default_config(self): - os.system(f"cellxgene launch --dump-default-config > {self.tmp_dir}/test_config_dump.txt") - with open(f"{self.tmp_dir}/expected_config_dump.txt", "w") as expected_config: - expected_config.write(yaml.dump(default_config)) - filecmp.cmp(f"{self.tmp_dir}/expected_config_dump.txt", f"{self.tmp_dir}/test_config_dump.txt") diff --git a/backend/test/test_czi_hosted/unit/cli/test_prepare.py b/backend/test/test_czi_hosted/unit/cli/test_prepare.py deleted file mode 100644 index d4c78fdf..00000000 --- a/backend/test/test_czi_hosted/unit/cli/test_prepare.py +++ /dev/null @@ -1,15 +0,0 @@ -import unittest - -import pandas as pd - -from backend.czi_hosted.cli.prepare import make_index_unique - - -class CLIPrepareTests(unittest.TestCase): - """ Test cases for CLI prepare logic """ - - def test_make_index_unique(self): - index = pd.Index(["SNORD113", "SNORD113", "SNORD113-1"]) - result = make_index_unique(index) - expected = pd.Index(["SNORD113", "SNORD113-2", "SNORD113-1"]) - self.assertTrue(all(left == right for left, right in zip(result.values, expected.values))) diff --git a/backend/test/test_czi_hosted/unit/cli/test_upgrade.py b/backend/test/test_czi_hosted/unit/cli/test_upgrade.py deleted file mode 100644 index a9ae85d9..00000000 --- a/backend/test/test_czi_hosted/unit/cli/test_upgrade.py +++ /dev/null @@ -1,28 +0,0 @@ -import unittest - -from backend.czi_hosted.cli.upgrade import validate_version_str, split_version, version_gt - - -class CLIUpgradeTests(unittest.TestCase): - """ Test cases for CLI logic """ - - def test_validate_version_str(self): - self.assertTrue(validate_version_str("0.1.2")) - self.assertTrue(validate_version_str("0.1.2-RC", release_only=False)) - self.assertFalse(validate_version_str("0.1")) - self.assertFalse(validate_version_str("0.1.2.3")) - self.assertFalse(validate_version_str("0.1.2-RC")) - - def test_split_version_str(self): - self.assertEqual(split_version("0.1.2"), [0, 1, 2]) - with self.assertRaises(AttributeError): - split_version("0.1") - - def test_assert_verstion_gt(self): - self.assertTrue(version_gt("1.0.0", "0.1.1")) - self.assertTrue(version_gt("0.1.0", "0.0.1")) - self.assertTrue(version_gt("0.0.1", "0.0.0")) - self.assertFalse(version_gt("0.0.0", "0.0.0")) - self.assertFalse(version_gt("0.0.0", "0.0.1")) - self.assertFalse(version_gt("0.0.1", "0.1.0")) - self.assertFalse(version_gt("0.1.1", "1.0.0")) diff --git a/backend/test/test_czi_hosted/unit/common/__init__.py b/backend/test/test_czi_hosted/unit/common/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/common/config/__init__.py b/backend/test/test_czi_hosted/unit/common/config/__init__.py deleted file mode 100644 index 1cfebb17..00000000 --- a/backend/test/test_czi_hosted/unit/common/config/__init__.py +++ /dev/null @@ -1,274 +0,0 @@ -import os -import shutil -import random -import yaml - -from backend.test import FIXTURES_ROOT -from backend.test.test_czi_hosted.unit import BaseTest - - - -class ConfigTests(BaseTest): - tmp_fixtures_directory = os.path.join(FIXTURES_ROOT, "tmp_dir") - - @classmethod - def tearDownClass(cls) -> None: - shutil.rmtree(cls.tmp_fixtures_directory) - - @classmethod - def setUpClass(cls) -> None: - os.makedirs(cls.tmp_fixtures_directory) - - def custom_server_config( - self, - verbose="false", - debug="false", - host="localhost", - port="null", - open_browser="false", - force_https="false", - flask_secret_key="secret", - generate_cache_control_headers="false", - server_timing_headers="false", - csp_directives="null", - api_base_url="null", - web_base_url="null", - auth_type="session", - insecure_test_environment="false", - oauth_api_base_url="null", - client_id="null", - client_secret="null", - jwt_decode_options="null", - session_cookie="true", - cookie="null", - dataroot="null", - index="false", - allowed_matrix_types=[], - max_cached_datasets=5, - timelimit_s=5, - dataset_datapath="null", - obs_names="null", - var_names="null", - about="null", - title="null", - diffexp_max_workers=64, - cpu_multiplier=4, - target_workunit="16_000_000", - data_locater_region_name="us-east-1", - cxg_tile_cache_size=8589934592, - cxg_num_reader_threads=32, - anndata_backed="false", - column_request_max=32, - diffexp_cellcount_max="null", - config_file_name="server_config.yaml", - ): - configfile = os.path.join(self.tmp_fixtures_directory, config_file_name) - server_config_outline_path = os.path.join(FIXTURES_ROOT, "czi_hosted_server_config_outline.py") - with open(server_config_outline_path, "r") as config_skeleton: - config = config_skeleton.read() - server_config = eval(config) - with open(configfile, "w") as server_config_file: - server_config_file.write(server_config) - return configfile - - def custom_app_config( - self, - verbose="false", - debug="false", - host="localhost", - port="null", - open_browser="false", - force_https="false", - flask_secret_key="secret", - generate_cache_control_headers="false", - server_timing_headers="false", - csp_directives="null", - api_base_url="null", - web_base_url="null", - auth_type="session", - oauth_api_base_url="null", - client_id="null", - client_secret="null", - jwt_decode_options="null", - session_cookie="true", - cookie="null", - dataroot="null", - index="false", - allowed_matrix_types=[], - max_cached_datasets=5, - timelimit_s=5, - dataset_datapath="null", - obs_names="null", - var_names="null", - about="null", - title="null", - diffexp_max_workers=64, - cpu_multiplier=4, - target_workunit="16_000_000", - data_locater_region_name="us-east-1", - cxg_tile_cache_size=8589934592, - cxg_num_reader_threads=32, - anndata_backed="false", - column_request_max=32, - diffexp_cellcount_max="null", - scripts=[], - inline_scripts=[], - about_legal_tos="null", - about_legal_privacy="null", - authentication_enable="true", - max_categories=1000, - custom_colors="true", - enable_users_annotations="true", - annotation_type="local_file_csv", - db_uri="null", - hosted_file_directory="null", - local_file_csv_directory="null", - local_file_csv_file="null", - embedding_names=[], - enable_difexp="true", - lfc_cutoff=0.01, - top_n=10, - environment=None, - aws_secrets_manager_region=None, - aws_secrets_manager_secrets=[], - X_approximate_distribution="normal", - config_file_name="app_config.yml", - ): - random_num = random.randrange(999999) - configfile = os.path.join(self.tmp_fixtures_directory, config_file_name) - server_config = self.custom_server_config( - verbose=verbose, - debug=debug, - host=host, - port=port, - open_browser=open_browser, - force_https=force_https, - flask_secret_key=flask_secret_key, - generate_cache_control_headers=generate_cache_control_headers, - server_timing_headers=server_timing_headers, - csp_directives=csp_directives, - api_base_url=api_base_url, - web_base_url=web_base_url, - auth_type=auth_type, - oauth_api_base_url=oauth_api_base_url, - client_id=client_id, - client_secret=client_secret, - jwt_decode_options=jwt_decode_options, - session_cookie=session_cookie, - cookie=cookie, - dataroot=dataroot, - index=index, - allowed_matrix_types=allowed_matrix_types, - max_cached_datasets=max_cached_datasets, - timelimit_s=timelimit_s, - dataset_datapath=dataset_datapath, - obs_names=obs_names, - var_names=var_names, - about=about, - title=title, - diffexp_max_workers=diffexp_max_workers, - cpu_multiplier=cpu_multiplier, - target_workunit=target_workunit, - data_locater_region_name=data_locater_region_name, - cxg_tile_cache_size=cxg_tile_cache_size, - cxg_num_reader_threads=cxg_num_reader_threads, - anndata_backed=anndata_backed, - column_request_max=column_request_max, - diffexp_cellcount_max=diffexp_cellcount_max, - config_file_name=f"temp_server_config_{random_num}.yml", - ) - dataset_config = self.custom_dataset_config( - scripts=scripts, - inline_scripts=inline_scripts, - about_legal_tos=about_legal_tos, - about_legal_privacy=about_legal_privacy, - authentication_enable=authentication_enable, - max_categories=max_categories, - custom_colors=custom_colors, - enable_users_annotations=enable_users_annotations, - annotation_type=annotation_type, - db_uri=db_uri, - hosted_file_directory=hosted_file_directory, - local_file_csv_directory=local_file_csv_directory, - local_file_csv_file=local_file_csv_file, - embedding_names=embedding_names, - enable_difexp=enable_difexp, - lfc_cutoff=lfc_cutoff, - top_n=top_n, - X_approximate_distribution=X_approximate_distribution, - config_file_name=f"temp_dataset_config_{random_num}.yml", - ) - external_config = self.custom_external_config( - environment=environment, - aws_secrets_manager_region=aws_secrets_manager_region, - aws_secrets_manager_secrets=aws_secrets_manager_secrets, - config_file_name=f"temp_external_config_{random_num}.yml", - ) - - with open(configfile, "w") as app_config_file: - app_config_file.write(open(server_config).read()) - app_config_file.write(open(dataset_config).read()) - app_config_file.write(open(external_config).read()) - - return configfile - - def custom_dataset_config( - self, - scripts=[], - inline_scripts=[], - about_legal_tos="null", - about_legal_privacy="null", - authentication_enable="true", - max_categories=1000, - custom_colors="true", - enable_users_annotations="true", - annotation_type="local_file_csv", - db_uri="null", - hosted_file_directory="null", - local_file_csv_directory="null", - local_file_csv_file="null", - embedding_names=[], - enable_difexp="true", - lfc_cutoff=0.01, - top_n=10, - X_approximate_distribution="normal", - config_file_name="dataset_config.yml", - ): - configfile = os.path.join(self.tmp_fixtures_directory, config_file_name) - dataset_config_outline_path = os.path.join(FIXTURES_ROOT, "czi_hosted_dataset_config_outline.py") - with open(dataset_config_outline_path, "r") as config_skeleton: - config = config_skeleton.read() - dataset_config = eval(config) - with open(configfile, "w") as dataset_config_file: - dataset_config_file.write(dataset_config) - - return configfile - - def custom_external_config( - self, - environment=None, - aws_secrets_manager_region=None, - aws_secrets_manager_secrets=[], - config_file_name="external_config.yaml", - ): - # set to the default if environment is None - if environment is None: - environment = [ - dict(name="CXG_SECRET_KEY", path=["server", "app", "flask_secret_key"], required=False), - dict( - name="CXG_OAUTH_CLIENT_SECRET", - path=["server", "authentication", "params_oauth", "client_secret"], - required=False, - ), - ] - external_config = { - "external": { - "environment": environment, - "aws_secrets_manager": {"region": aws_secrets_manager_region, "secrets": aws_secrets_manager_secrets}, - } - } - - configfile = os.path.join(self.tmp_fixtures_directory, config_file_name) - with open(configfile, "w") as external_config_file: - yaml.dump(external_config, external_config_file) - return configfile diff --git a/backend/test/test_czi_hosted/unit/common/config/test_app_config.py b/backend/test/test_czi_hosted/unit/common/config/test_app_config.py deleted file mode 100644 index f6e7bc31..00000000 --- a/backend/test/test_czi_hosted/unit/common/config/test_app_config.py +++ /dev/null @@ -1,220 +0,0 @@ -import os -import tempfile -import unittest - -import yaml - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.errors import ConfigurationError -from backend.czi_hosted.default_config import default_config -from backend.test import FIXTURES_ROOT -from backend.test.test_czi_hosted.unit.common.config import ConfigTests - - -class AppConfigTest(ConfigTests): - def setUp(self): - self.config_file_name = f"{unittest.TestCase.id(self).split('.')[-1]}.yml" - self.config = AppConfig() - self.config.update_server_config(app__flask_secret_key="secret") - self.config.update_server_config(multi_dataset__dataroot=FIXTURES_ROOT) - self.server_config = self.config.server_config - self.config.complete_config() - - message_list = [] - - def noop(message): - message_list.append(message) - - messagefn = noop - self.context = dict(messagefn=messagefn, messages=message_list) - - def get_config(self, **kwargs): - file_name = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", config_file_name=self.config_file_name, **kwargs - ) - config = AppConfig() - config.update_from_config_file(file_name) - return config - - def test_get_default_config_correctly_reads_default_config_file(self): - app_default_config = AppConfig().default_config - - expected_config = yaml.load(default_config, Loader=yaml.Loader) - - server_config = app_default_config["server"] - dataset_config = app_default_config["dataset"] - - expected_server_config = expected_config["server"] - expected_dataset_config = expected_config["dataset"] - - self.assertDictEqual(app_default_config, expected_config) - self.assertDictEqual(server_config, expected_server_config) - self.assertDictEqual(dataset_config, expected_dataset_config) - - def test_get_dataset_config_returns_default_dataset_config_for_single_datasets(self): - datapath = f"{FIXTURES_ROOT}/1e4dfec4-c0b2-46ad-a04e-ff3ffb3c0a8f.h5ad" - file_name = self.custom_app_config(dataset_datapath=datapath, config_file_name=self.config_file_name) - config = AppConfig() - config.update_from_config_file(file_name) - - self.assertEqual(config.get_dataset_config(""), config.default_dataset_config) - - def test_update_server_config_updates_server_config_and_config_status(self): - config = self.get_config() - config.complete_config() - config.check_config() - config.update_server_config(multi_dataset__dataroot=FIXTURES_ROOT) - with self.assertRaises(ConfigurationError): - config.server_config.check_config() - - def test_write_config_outputs_yaml_with_all_config_vars(self): - config = self.get_config() - config.write_config(f"{FIXTURES_ROOT}/tmp_dir/write_config.yml") - with open(f"{FIXTURES_ROOT}/tmp_dir/{self.config_file_name}", "r") as default_config: - default_config_yml = yaml.safe_load(default_config) - - with open(f"{FIXTURES_ROOT}/tmp_dir/write_config.yml", "r") as output_config: - output_config_yml = yaml.safe_load(output_config) - self.maxDiff = None - self.assertEqual(default_config_yml, output_config_yml) - - def test_update_app_config(self): - config = AppConfig() - config.update_server_config(app__verbose=True, multi_dataset__dataroot="datadir") - vars = config.server_config.changes_from_default() - self.assertCountEqual(vars, [("app__verbose", True, False), ("multi_dataset__dataroot", "datadir", None)]) - - config = AppConfig() - config.update_default_dataset_config(app__scripts=(), app__inline_scripts=()) - vars = config.server_config.changes_from_default() - self.assertCountEqual(vars, []) - - config = AppConfig() - config.update_default_dataset_config(app__scripts=[], app__inline_scripts=[]) - vars = config.default_dataset_config.changes_from_default() - self.assertCountEqual(vars, []) - - config = AppConfig() - config.update_default_dataset_config(app__scripts=("a", "b"), app__inline_scripts=["c", "d"]) - vars = config.default_dataset_config.changes_from_default() - self.assertCountEqual(vars, [("app__scripts", ["a", "b"], []), ("app__inline_scripts", ["c", "d"], [])]) - - def test_configfile_no_dataset_section(self): - # test a config file without a dataset section - - with tempfile.TemporaryDirectory() as tempdir: - configfile = os.path.join(tempdir, "config.yaml") - with open(configfile, "w") as fconfig: - config = """ - server: - app: - flask_secret_key: secret - multi_dataset: - dataroot: test_dataroot - - """ - fconfig.write(config) - - app_config = AppConfig() - app_config.update_from_config_file(configfile) - server_changes = app_config.server_config.changes_from_default() - dataset_changes = app_config.default_dataset_config.changes_from_default() - self.assertEqual( - server_changes, - [("app__flask_secret_key", "secret", None), ("multi_dataset__dataroot", "test_dataroot", None)], - ) - self.assertEqual(dataset_changes, []) - - def test_configfile_no_server_section(self): - # test a config file without a dataset section - - with tempfile.TemporaryDirectory() as tempdir: - configfile = os.path.join(tempdir, "config.yaml") - with open(configfile, "w") as fconfig: - config = """ - dataset: - user_annotations: - enable: false - """ - fconfig.write(config) - - app_config = AppConfig() - app_config.update_from_config_file(configfile) - server_changes = app_config.server_config.changes_from_default() - dataset_changes = app_config.default_dataset_config.changes_from_default() - self.assertEqual(server_changes, []) - self.assertEqual(dataset_changes, [("user_annotations__enable", False, True)]) - - def test_simple_update_single_config_from_path_and_value(self): - """Update a simple config parameter""" - - config = AppConfig() - config.server_config.multi_dataset__dataroot = dict( - s1=dict(dataroot="my_dataroot_s1", base_url="my_baseurl_s1"), - s2=dict(dataroot="my_dataroot_s2", base_url="my_baseurl_s2"), - ) - config.add_dataroot_config("s1") - config.add_dataroot_config("s2") - - # test simple value in server - config.update_single_config_from_path_and_value(["server", "app", "flask_secret_key"], "mysecret") - self.assertEqual(config.server_config.app__flask_secret_key, "mysecret") - - # test simple value in default dataset - config.update_single_config_from_path_and_value( - ["dataset", "user_annotations", "hosted_tiledb_array", "db_uri"], "mydburi", - ) - self.assertEqual(config.default_dataset_config.user_annotations__hosted_tiledb_array__db_uri, "mydburi") - self.assertEqual(config.dataroot_config["s1"].user_annotations__hosted_tiledb_array__db_uri, "mydburi") - self.assertEqual(config.dataroot_config["s2"].user_annotations__hosted_tiledb_array__db_uri, "mydburi") - - # test simple value in specific dataset - config.update_single_config_from_path_and_value( - ["per_dataset_config", "s1", "user_annotations", "hosted_tiledb_array", "db_uri"], "s1dburi" - ) - self.assertEqual(config.default_dataset_config.user_annotations__hosted_tiledb_array__db_uri, "mydburi") - self.assertEqual(config.dataroot_config["s1"].user_annotations__hosted_tiledb_array__db_uri, "s1dburi") - self.assertEqual(config.dataroot_config["s2"].user_annotations__hosted_tiledb_array__db_uri, "mydburi") - - # error checking - bad_paths = [ - ( - ["dataset", "does", "not", "exist"], - "unknown config parameter at path: '['dataset', 'does', 'not', 'exist']'", - ), - (["does", "not", "exist"], "path must start with 'server', 'dataset', or 'per_dataset_config'"), - ([], "path must start with 'server', 'dataset', or 'per_dataset_config'"), - (["per_dataset_config"], "missing dataroot when using per_dataset_config: got '['per_dataset_config']'"), - ( - ["per_dataset_config", "unknown"], - "unknown dataroot when using per_dataset_config: got '['per_dataset_config', 'unknown']'," - " dataroots specified in config are ['s1', 's2']", - ), - ([1, 2, 3], "path must be a list of strings, got '[1, 2, 3]'"), - ("string", "path must be a list of strings, got 'string'"), - ] - for bad_path, error_message in bad_paths: - with self.assertRaises(ConfigurationError) as config_error: - config.update_single_config_from_path_and_value(bad_path, "value") - - self.assertEqual(config_error.exception.message, error_message) - - def test_dict_update_single_config_from_path_and_value(self): - """Update a config parameter that has a value of dict""" - - # the path leads to a dict config param, set the config parameter to the new value - config = AppConfig() - config.update_single_config_from_path_and_value( - ["server", "authentication", "params_oauth", "cookie"], dict(key="mykey1", max_age=100) - ) - self.assertEqual(config.server_config.authentication__params_oauth__cookie, dict(key="mykey1", max_age=100)) - - # the path leads to an entry within a dict config param, the value is simple - config = AppConfig() - config.server_config.authentication__params_oauth__cookie = dict(key="mykey1", max_age=100) - config.update_single_config_from_path_and_value( - ["server", "authentication", "params_oauth", "cookie", "httponly"], True, - ) - self.assertEqual( - config.server_config.authentication__params_oauth__cookie, dict(key="mykey1", max_age=100, httponly=True) - ) diff --git a/backend/test/test_czi_hosted/unit/common/config/test_base_config.py b/backend/test/test_czi_hosted/unit/common/config/test_base_config.py deleted file mode 100644 index 959fbfd4..00000000 --- a/backend/test/test_czi_hosted/unit/common/config/test_base_config.py +++ /dev/null @@ -1,66 +0,0 @@ -import unittest - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import FIXTURES_ROOT -from backend.common.errors import ConfigurationError -from backend.test.test_czi_hosted.unit.common.config import ConfigTests - - -class BaseConfigTest(ConfigTests): - def setUp(self): - self.config_file_name = f"{unittest.TestCase.id(self).split('.')[-1]}.yml" - self.config = AppConfig() - self.config.update_server_config(app__flask_secret_key="secret") - self.config.update_server_config(multi_dataset__dataroot=FIXTURES_ROOT) - self.server_config = self.config.server_config - self.config.complete_config() - - message_list = [] - - def noop(message): - message_list.append(message) - - messagefn = noop - self.context = dict(messagefn=messagefn, messages=message_list) - - def get_config(self, **kwargs): - file_name = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", config_file_name=self.config_file_name, **kwargs - ) - config = AppConfig() - config.update_from_config_file(file_name) - return config - - def test_mapping_creation_returns_map_of_server_and_dataset_config(self): - config = AppConfig() - mapping = config.default_dataset_config.create_mapping(config.default_config) - self.assertIsNotNone(mapping["server__app__verbose"]) - self.assertIsNotNone(mapping["dataset__presentation__max_categories"]) - self.assertIsNotNone(mapping["server__multi_dataset__allowed_matrix_types"]) - - def test_changes_from_default_returns_list_of_nondefault_config_values(self): - config = self.get_config(verbose="true", lfc_cutoff=0.05) - server_changes = config.server_config.changes_from_default() - dataset_changes = config.default_dataset_config.changes_from_default() - - self.assertEqual( - server_changes, - [ - ("app__verbose", True, False), - ("app__flask_secret_key", "secret", None), - ('authentication__type', 'session', 'test'), - ('authentication__insecure_test_environment', False, True), - ("multi_dataset__dataroot", FIXTURES_ROOT, None), - ("multi_dataset__matrix_cache__timelimit_s", 5, 30), - ("data_locator__s3__region_name", "us-east-1", True), - ], - ) - self.assertEqual(dataset_changes, [("diffexp__lfc_cutoff", 0.05, 0.01)]) - - def test_check_config_throws_error_if_attr_has_not_been_checked(self): - config = self.get_config(verbose="true") - config.complete_config() - config.check_config() - config.update_server_config(app__verbose=False) - with self.assertRaises(ConfigurationError): - config.check_config() diff --git a/backend/test/test_czi_hosted/unit/common/config/test_dataset_config.py b/backend/test/test_czi_hosted/unit/common/config/test_dataset_config.py deleted file mode 100644 index 149e5373..00000000 --- a/backend/test/test_czi_hosted/unit/common/config/test_dataset_config.py +++ /dev/null @@ -1,253 +0,0 @@ -import json -import os -import tempfile - -import unittest -from unittest.mock import patch - -from backend.czi_hosted.common.annotations.hosted_tiledb import AnnotationsHostedTileDB -from backend.czi_hosted.common.annotations.local_file_csv import AnnotationsLocalFile -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.czi_hosted.common.config.base_config import BaseConfig -from backend.test import PROJECT_ROOT, FIXTURES_ROOT - -from backend.common.errors import ConfigurationError -from backend.test.test_czi_hosted.unit.common.config import ConfigTests - - -class TestDatasetConfig(ConfigTests): - def setUp(self): - self.config_file_name = f"{unittest.TestCase.id(self).split('.')[-1]}.yml" - self.config = AppConfig() - self.config.update_server_config(app__flask_secret_key="secret") - self.config.update_server_config(multi_dataset__dataroot=FIXTURES_ROOT) - self.dataset_config = self.config.default_dataset_config - self.config.complete_config() - message_list = [] - - def noop(message): - message_list.append(message) - - messagefn = noop - self.context = dict(messagefn=messagefn, messages=message_list) - - def get_config(self, **kwargs): - file_name = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", config_file_name=self.config_file_name, **kwargs - ) - config = AppConfig() - config.update_from_config_file(file_name) - return config - - def test_init_datatset_config_sets_vars_from_default_config(self): - config = AppConfig() - self.assertEqual(config.default_dataset_config.presentation__max_categories, 1000) - self.assertEqual(config.default_dataset_config.user_annotations__type, "local_file_csv") - self.assertEqual(config.default_dataset_config.diffexp__lfc_cutoff, 0.01) - - @patch("backend.czi_hosted.common.config.dataset_config.BaseConfig.validate_correct_type_of_configuration_attribute") - def test_complete_config_checks_all_attr(self, mock_check_attrs): - mock_check_attrs.side_effect = BaseConfig.validate_correct_type_of_configuration_attribute() - self.dataset_config.complete_config(self.context) - self.assertEqual(mock_check_attrs.call_count, 19) - - def test_app_sets_script_vars(self): - config = self.get_config(scripts=["path/to/script"]) - config.default_dataset_config.handle_app() - - self.assertEqual(config.default_dataset_config.app__scripts, [{"src": "path/to/script"}]) - - config = self.get_config(scripts=[{"src": "path/to/script", "more": "different/script/path"}]) - config.default_dataset_config.handle_app() - self.assertEqual( - config.default_dataset_config.app__scripts, [{"src": "path/to/script", "more": "different/script/path"}] - ) - - config = self.get_config(scripts=["path/to/script", "different/script/path"]) - config.default_dataset_config.handle_app() - # TODO @madison -- is this the desired functionality? - self.assertEqual( - config.default_dataset_config.app__scripts, [{"src": "path/to/script"}, {"src": "different/script/path"}] - ) - - config = self.get_config(scripts=[{"more": "different/script/path"}]) - with self.assertRaises(ConfigurationError): - config.default_dataset_config.handle_app() - - def test_handle_user_annotations_ensures_auth_is_enabled_with_valid_auth_type(self): - config = self.get_config(enable_users_annotations="true", authentication_enable="false") - config.server_config.complete_config(self.context) - with self.assertRaises(ConfigurationError): - config.default_dataset_config.handle_user_annotations(self.context) - - config = self.get_config(enable_users_annotations="true", authentication_enable="true", auth_type="pretend") - with self.assertRaises(ConfigurationError): - config.server_config.complete_config(self.context) - - def test_handle_user_annotations__adds_warning_message_if_annotation_vars_set_when_annotations_disabled(self): - config = self.get_config( - enable_users_annotations="false", authentication_enable="false", db_uri="shouldnt/be/set" - ) - config.default_dataset_config.handle_user_annotations(self.context) - - self.assertEqual(self.context["messages"], ["Warning: db_uri ignored as annotations are disabled."]) - - @patch("backend.czi_hosted.common.config.dataset_config.DbUtils") - def test_handle_user_annotations__instantiates_user_annotations_class_correctly(self, mock_db_utils): - mock_db_utils.return_value = "123" - config = self.get_config( - enable_users_annotations="true", authentication_enable="true", annotation_type="local_file_csv" - ) - config.server_config.complete_config(self.context) - config.default_dataset_config.handle_user_annotations(self.context) - self.assertIsInstance(config.default_dataset_config.user_annotations, AnnotationsLocalFile) - - config = self.get_config( - enable_users_annotations="true", - authentication_enable="true", - annotation_type="hosted_tiledb_array", - db_uri="gotta/set/this", - hosted_file_directory="and/this", - ) - config.server_config.complete_config(self.context) - config.default_dataset_config.handle_user_annotations(self.context) - self.assertIsInstance(config.default_dataset_config.user_annotations, AnnotationsHostedTileDB) - - config = self.get_config( - enable_users_annotations="true", authentication_enable="true", annotation_type="NOT_REAL" - ) - config.server_config.complete_config(self.context) - with self.assertRaises(ConfigurationError): - config.default_dataset_config.handle_user_annotations(self.context) - - def test_handle_local_file_csv_annotations__sets_dir_if_not_passed_in(self): - config = self.get_config( - enable_users_annotations="true", authentication_enable="true", annotation_type="local_file_csv" - ) - config.server_config.complete_config(self.context) - config.default_dataset_config.handle_local_file_csv_annotations() - self.assertIsInstance(config.default_dataset_config.user_annotations, AnnotationsLocalFile) - cwd = os.getcwd() - self.assertEqual(config.default_dataset_config.user_annotations._get_output_dir(), cwd) - - def test_handle_diffexp__raises_warning_for_large_datasets(self): - config = self.get_config(lfc_cutoff=0.02, enable_difexp="true", top_n=15) - config.server_config.complete_config(self.context) - config.default_dataset_config.handle_diffexp(self.context) - self.assertEqual(len(self.context["messages"]), 0) - - def test_multi_dataset(self): - config = AppConfig() - # test for illegal url_dataroots - for illegal in ("../b", "!$*", "\\n", "", "(bad)"): - config.update_server_config( - app__flask_secret_key="secret", - multi_dataset__dataroot={"tag": {"base_url": illegal, "dataroot": f"{PROJECT_ROOT}/example-dataset"}}, - ) - with self.assertRaises(ConfigurationError): - config.complete_config() - - # test for legal url_dataroots - for legal in ("d", "this.is-okay_", "a/b"): - config.update_server_config( - app__flask_secret_key="secret", - multi_dataset__dataroot={"tag": {"base_url": legal, "dataroot": f"{PROJECT_ROOT}/example-dataset"}}, - ) - config.complete_config() - - # test that multi dataroots work end to end - config.update_server_config( - app__flask_secret_key="secret", - multi_dataset__dataroot=dict( - s1=dict(dataroot=f"{PROJECT_ROOT}/example-dataset", base_url="set1/1/2"), - s2=dict(dataroot=f"{FIXTURES_ROOT}", base_url="set2"), - s3=dict(dataroot=f"{FIXTURES_ROOT}", base_url="set3"), - ), - ) - - # Change this default to test if the dataroot overrides below work. - config.update_default_dataset_config(app__about_legal_tos="tos_default.html") - - # specialize the configs for set1 - config.add_dataroot_config( - "s1", user_annotations__enable=False, diffexp__enable=True, app__about_legal_tos="tos_set1.html" - ) - - # specialize the configs for set2 - config.add_dataroot_config( - "s2", user_annotations__enable=True, diffexp__enable=False, app__about_legal_tos="tos_set2.html" - ) - - # no specializations for set3 (they get the default dataset config) - config.complete_config() - - server = self.create_app(config) - - server.testing = True - session = server.test_client() - - response = session.get("/set1/1/2/pbmc3k.h5ad/api/v0.2/config") - data_config = json.loads(response.data) - - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - assert data_config["config"]["parameters"]["annotations"] is False - assert data_config["config"]["parameters"]["disable-diffexp"] is False - assert data_config["config"]["parameters"]["about_legal_tos"] == "tos_set1.html" - - response = session.get("/set2/pbmc3k.cxg/api/v0.2/config") - data_config = json.loads(response.data) - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - assert data_config["config"]["parameters"]["annotations"] is True - assert data_config["config"]["parameters"]["about_legal_tos"] == "tos_set2.html" - - response = session.get("/set3/pbmc3k.cxg/api/v0.2/config") - data_config = json.loads(response.data) - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - assert data_config["config"]["parameters"]["annotations"] is True - assert data_config["config"]["parameters"]["disable-diffexp"] is False - assert data_config["config"]["parameters"]["about_legal_tos"] == "tos_default.html" - - response = session.get("/health") - - assert json.loads(response.data)["status"] == "pass" - - def test_configfile_with_specialization(self): - # test that per_dataset_config config load the default config, then the specialized config - - with tempfile.TemporaryDirectory() as tempdir: - configfile = os.path.join(tempdir, "config.yaml") - with open(configfile, "w") as fconfig: - config = """ - server: - multi_dataset: - dataroot: - test: - base_url: test - dataroot: fake_dataroot - - dataset: - user_annotations: - enable: false - type: hosted_tiledb_array - hosted_tiledb_array: - db_uri: fake_db_uri - hosted_file_directory: fake_dir - - per_dataset_config: - test: - user_annotations: - enable: true - """ - fconfig.write(config) - - app_config = AppConfig() - app_config.update_from_config_file(configfile) - - test_config = app_config.dataroot_config["test"] - - # test config from default - self.assertEqual(test_config.user_annotations__type, "hosted_tiledb_array") - self.assertEqual(test_config.user_annotations__hosted_tiledb_array__db_uri, "fake_db_uri") - - # test config from specialization - self.assertTrue(test_config.user_annotations__enable) diff --git a/backend/test/test_czi_hosted/unit/common/config/test_external_config.py b/backend/test/test_czi_hosted/unit/common/config/test_external_config.py deleted file mode 100644 index 6db40023..00000000 --- a/backend/test/test_czi_hosted/unit/common/config/test_external_config.py +++ /dev/null @@ -1,243 +0,0 @@ -import json -import os -from unittest.mock import patch - -import yaml - -from backend.common.errors import ConfigurationError -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.utils.type_conversion_utils import convert_string_to_value -from backend.test import FIXTURES_ROOT -from backend.test.test_czi_hosted.unit.common.config import ConfigTests - - -class TestExternalConfig(ConfigTests): - def test_type_convert(self): - # The values from environment variables and aws secrets are returned as strings. - # These values need to be converted to the proper types. - - self.assertEqual(convert_string_to_value("1"), int(1)) - self.assertEqual(convert_string_to_value("1.1"), float(1.1)) - self.assertEqual(convert_string_to_value("string"), "string") - self.assertEqual(convert_string_to_value("true"), True) - self.assertEqual(convert_string_to_value("True"), True) - self.assertEqual(convert_string_to_value("false"), False) - self.assertEqual(convert_string_to_value("False"), False) - self.assertEqual(convert_string_to_value("null"), None) - self.assertEqual(convert_string_to_value("None"), None) - self.assertEqual(convert_string_to_value("{'a':10, 'b':'string'}"), dict(a=int(10), b="string")) - - def test_environment_variable(self): - configfile = self.custom_external_config( - environment=[ - dict(name="DATAPATH", path=["server", "single_dataset", "datapath"], required=True), - dict(name="DIFFEXP", path=["dataset", "diffexp", "enable"], required=True), - ], - config_file_name="environment_external_config.yaml", - ) - - env = os.environ - env["DATAPATH"] = f"{FIXTURES_ROOT}/pbmc3k.cxg" - env["DIFFEXP"] = "False" - config = AppConfig() - config.update_from_config_file(configfile) - config.update_server_config(app__flask_secret_key="123 magic") - - server = self.create_app(config) - - server.testing = True - session = server.test_client() - - response = session.get("/api/v0.2/config") - data_config = json.loads(response.data) - self.assertEqual(data_config["config"]["displayNames"]["dataset"], "pbmc3k") - self.assertTrue(data_config["config"]["parameters"]["disable-diffexp"]) - - os.environ["DATAPATH"] = f"{FIXTURES_ROOT}/a95c59b4-7f5d-4b80-ad53-a694834ca18b.h5ad" - os.environ["DIFFEXP"] = "True" - - server= self.create_app(config) - - server.testing = True - session = server.test_client() - - # session = requests.Session() - response = session.get("/api/v0.2/config") - data_config = json.loads(response.data) - self.assertEqual(data_config["config"]["displayNames"]["dataset"], "a95c59b4-7f5d-4b80-ad53-a694834ca18b") - self.assertFalse(data_config["config"]["parameters"]["disable-diffexp"]) - - def test_environment_variable_errors(self): - # no name - app_config = AppConfig() - app_config.external_config.environment = [dict(required=True, path=["this", "is", "a", "path"])] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "environment: 'name' is missing") - - # required has wrong type - app_config = AppConfig() - app_config.external_config.environment = [ - dict(name="myenvar", required="optional", path=["this", "is", "a", "path"]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "environment: 'required' must be a bool") - - # no path - app_config = AppConfig() - app_config.external_config.environment = [dict(name="myenvar", required=True)] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "environment: 'path' is missing") - - # required environment variable is not set - app_config = AppConfig() - app_config.external_config.environment = [ - dict(name="THIS_ENV_IS_NOT_SET", required=True, path=["this", "is", "a", "path"]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "required environment variable 'THIS_ENV_IS_NOT_SET' not set") - - @patch("backend.czi_hosted.common.config.external_config.get_secret_key") - def test_aws_secrets_manager(self, mock_get_secret_key): - mock_get_secret_key.return_value = { - "oauth_client_secret": "mock_oauth_secret", - "db_uri": "mock_db_uri", - } - configfile = self.custom_external_config( - aws_secrets_manager_region="us-west-2", - aws_secrets_manager_secrets=[ - dict( - name="my_secret", - values=[ - dict(key="flask_secret_key", path=["server", "app", "flask_secret_key"], required=False), - dict( - key="db_uri", - path=["dataset", "user_annotations", "hosted_tiledb_array", "db_uri"], - required=True, - ), - dict( - key="oauth_client_secret", - path=["server", "authentication", "params_oauth", "client_secret"], - required=True, - ), - ], - ) - ], - config_file_name="secret_external_config.yaml", - ) - - app_config = AppConfig() - app_config.update_from_config_file(configfile) - app_config.server_config.single_dataset__datapath = f"{FIXTURES_ROOT}/pbmc3k.cxg" - app_config.server_config.app__flask_secret_key = "original" - app_config.server_config.single_dataset__datapath = f"{FIXTURES_ROOT}/pbmc3k.cxg" - - app_config.complete_config() - - self.assertEqual(app_config.server_config.app__flask_secret_key, "original") - self.assertEqual(app_config.server_config.authentication__params_oauth__client_secret, "mock_oauth_secret") - self.assertEqual(app_config.default_dataset_config.user_annotations__hosted_tiledb_array__db_uri, "mock_db_uri") - - @patch("backend.czi_hosted.common.config.external_config.get_secret_key") - def test_aws_secrets_manager_error(self, mock_get_secret_key): - mock_get_secret_key.return_value = { - "oauth_client_secret": "mock_oauth_secret", - "db_uri": "mock_db_uri", - } - - # no region - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = None - app_config.external_config.aws_secrets_manager__secrets = [ - dict(name="secret1", values=[dict(key="key1", required=True, path=["this", "is", "my", "path"])]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual( - config_error.exception.message, - "Invalid type for attribute: aws_secrets_manager__region, expected type str, got NoneType", - ) - - # missing secret name - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict(values=[dict(key="db_uri", required=True, path=["this", "is", "my", "path"])]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "aws_secrets_manager: 'name' is missing") - - # secret name wrong type - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict(name=1, values=[dict(key="db_uri", required=True, path=["this", "is", "my", "path"])]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "aws_secrets_manager: 'name' must be a string") - - # missing values name - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [dict(name="mysecret")] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "aws_secrets_manager: 'values' is missing") - - # values wrong type - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict(name="mysecret", values=dict(key="db_uri", required=True, path=["this", "is", "my", "path"])) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "aws_secrets_manager: 'values' must be a list") - - # entry missing key - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict(name="mysecret", values=[dict(required=True, path=["this", "is", "my", "path"])]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "missing 'key' in secret values: mysecret") - - # entry required is wrong type - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict(name="mysecret", values=[dict(key="db_uri", required="optional", path=["this", "is", "my", "path"])]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "wrong type for 'required' in secret values: mysecret") - - # entry missing path - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict(name="mysecret", values=[dict(key="db_uri", required=True)]) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "missing 'path' in secret values: mysecret") - - # secret missing required key - app_config = AppConfig() - app_config.external_config.aws_secrets_manager__region = "us-west-2" - app_config.external_config.aws_secrets_manager__secrets = [ - dict( - name="mysecret", - values=[dict(key="KEY_DOES_NOT_EXIST", required=True, path=["this", "is", "a", "path"])], - ) - ] - with self.assertRaises(ConfigurationError) as config_error: - app_config.complete_config() - self.assertEqual(config_error.exception.message, "required secret 'mysecret:KEY_DOES_NOT_EXIST' not set") diff --git a/backend/test/test_czi_hosted/unit/common/config/test_server_config.py b/backend/test/test_czi_hosted/unit/common/config/test_server_config.py deleted file mode 100644 index 674656d7..00000000 --- a/backend/test/test_czi_hosted/unit/common/config/test_server_config.py +++ /dev/null @@ -1,324 +0,0 @@ -import json -import os -import unittest -from unittest.mock import patch - - -from backend.czi_hosted.common.config.base_config import BaseConfig -from backend.common.utils.utils import find_available_port -from backend.test import PROJECT_ROOT, FIXTURES_ROOT - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.errors import ConfigurationError -from backend.test.test_czi_hosted.unit.common.config import ConfigTests - - -class TestServerConfig(ConfigTests): - def setUp(self): - self.config_file_name = f"{unittest.TestCase.id(self).split('.')[-1]}.yml" - self.config = AppConfig() - self.config.update_server_config(app__flask_secret_key="secret") - self.config.update_server_config(multi_dataset__dataroot=FIXTURES_ROOT) - self.server_config = self.config.server_config - self.config.complete_config() - - message_list = [] - - def noop(message): - message_list.append(message) - - messagefn = noop - self.context = dict(messagefn=messagefn, messages=message_list) - - def get_config(self, **kwargs): - file_name = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", config_file_name=self.config_file_name, **kwargs - ) - config = AppConfig() - config.update_from_config_file(file_name) - return config - - def test_init_raises_error_if_default_config_is_invalid(self): - invalid_config = self.get_config(port="not_valid") - with self.assertRaises(ConfigurationError): - invalid_config.complete_config() - - @patch("backend.czi_hosted.common.config.server_config.BaseConfig.validate_correct_type_of_configuration_attribute") - def test_complete_config_checks_all_attr(self, mock_check_attrs): - mock_check_attrs.side_effect = BaseConfig.validate_correct_type_of_configuration_attribute() - self.server_config.complete_config(self.context) - self.assertEqual(mock_check_attrs.call_count, 41) - - def test_handle_app__throws_error_if_port_doesnt_exist(self): - config = self.get_config(port=99999999) - with self.assertRaises(ConfigurationError): - config.server_config.handle_app(self.context) - - @patch("backend.czi_hosted.common.config.server_config.discover_s3_region_name") - def test_handle_data_locator_works_for_default_types(self, mock_discover_region_name): - mock_discover_region_name.return_value = None - # Default config - self.assertEqual(self.config.server_config.data_locator__s3__region_name, None) - # hard coded - config = self.get_config() - self.assertEqual(config.server_config.data_locator__s3__region_name, "us-east-1") - # incorrectly formatted - dataroot = { - "d1": {"base_url": "set1", "dataroot": "/path/to/set1_datasets/"}, - "d2": {"base_url": "set2/subdir", "dataroot": "s3://shouldnt/work"}, - } - file_name = self.custom_app_config( - dataroot=dataroot, config_file_name=self.config_file_name, data_locater_region_name="true" - ) - config = AppConfig() - config.update_from_config_file(file_name) - with self.assertRaises(ConfigurationError): - config.server_config.handle_data_locator() - - @patch("backend.czi_hosted.common.config.server_config.discover_s3_region_name") - def test_handle_data_locator_can_read_from_dataroot(self, mock_discover_region_name): - mock_discover_region_name.return_value = "us-west-2" - dataroot = { - "d1": {"base_url": "set1", "dataroot": "/path/to/set1_datasets/"}, - "d2": {"base_url": "set2/subdir", "dataroot": "s3://hosted-cellxgene-dev"}, - } - file_name = self.custom_app_config( - dataroot=dataroot, config_file_name=self.config_file_name, data_locater_region_name="true" - ) - config = AppConfig() - config.update_from_config_file(file_name) - config.server_config.handle_data_locator() - self.assertEqual(config.server_config.data_locator__s3__region_name, "us-west-2") - mock_discover_region_name.assert_called_once_with("s3://hosted-cellxgene-dev") - - def test_handle_app___can_use_envar_port(self): - config = self.get_config(port=24) - self.assertEqual(config.server_config.app__port, 24) - - # Note if the port is set in the config file it will NOT be overwritten by a different envvar - os.environ["CXG_SERVER_PORT"] = "4008" - self.config = AppConfig() - self.config.update_server_config(app__flask_secret_key="secret") - self.config.server_config.handle_app(self.context) - self.assertEqual(self.config.server_config.app__port, 4008) - del os.environ["CXG_SERVER_PORT"] - - def test_handle_app__can_get_secret_key_from_envvar_or_config_file_with_envvar_given_preference(self): - config = self.get_config(flask_secret_key="KEY_FROM_FILE") - self.assertEqual(config.server_config.app__flask_secret_key, "KEY_FROM_FILE") - - os.environ["CXG_SECRET_KEY"] = "KEY_FROM_ENV" - config.external_config.handle_environment(self.context) - self.assertEqual(config.server_config.app__flask_secret_key, "KEY_FROM_ENV") - - def test_handle_app__sets_web_base_url(self): - config = self.get_config(web_base_url="anything.com") - self.assertEqual(config.server_config.app__web_base_url, "anything.com") - - def test_handle_auth__gets_client_secret_from_envvars_or_config_with_envvars_given_preference(self): - config = self.get_config(client_secret="KEY_FROM_FILE") - config.server_config.handle_authentication() - self.assertEqual(config.server_config.authentication__params_oauth__client_secret, "KEY_FROM_FILE") - - os.environ["CXG_OAUTH_CLIENT_SECRET"] = "KEY_FROM_ENV" - config.external_config.handle_environment(self.context) - - self.assertEqual(config.server_config.authentication__params_oauth__client_secret, "KEY_FROM_ENV") - - def test_handle_data_source__errors_when_passed_zero_or_two_dataroots(self): - file_name = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", - config_file_name="two_data_roots.yml", - dataset_datapath=f"{FIXTURES_ROOT}/pbmc3k-CSC-gz.h5ad", - ) - config = AppConfig() - config.update_from_config_file(file_name) - with self.assertRaises(ConfigurationError): - config.server_config.handle_data_source() - - file_name = self.custom_app_config(config_file_name="zero_roots.yml") - config = AppConfig() - config.update_from_config_file(file_name) - with self.assertRaises(ConfigurationError): - config.server_config.handle_data_source() - - @unittest.skip("skip when running in github action") - def test_get_api_base_url_works(self): - # test the api_base_url feature, and that it can contain a path - config = AppConfig() - backend_port = find_available_port("localhost", 10000) - config.update_server_config( - app__flask_secret_key="secret", - app__api_base_url=f"http://localhost:{backend_port}/additional/path", - multi_dataset__dataroot=f"{PROJECT_ROOT}/example-dataset", - multi_dataset__allowed_matrix_types=["cxg"], - ) - - config.complete_config() - server = self.create_app(config) - server.testing = True - session = server.test_client() - response = session.get(f"/additional/path/d/pbmc3k.h5ad/api/v0.2/config") - - self.assertEqual(response.status_code, 200) - data_config = json.loads(response.data) - self.assertEqual(data_config["config"]["displayNames"]["dataset"], "pbmc3k") - - # test the health check at the correct url - response = session.get(f"/additional/path/health") - assert json.loads(response.data)["status"] == "pass" - - def test_get_web_base_url_works(self): - config = self.get_config(web_base_url="www.thisisawebsite.com") - web_base_url = config.server_config.get_web_base_url() - self.assertEqual(web_base_url, "www.thisisawebsite.com") - - config = self.get_config(web_base_url="local", port=12) - web_base_url = config.server_config.get_web_base_url() - self.assertEqual(web_base_url, "http://localhost:12") - - config = self.get_config(web_base_url="www.thisisawebsite.com/") - web_base_url = config.server_config.get_web_base_url() - self.assertEqual(web_base_url, "www.thisisawebsite.com") - - config = self.get_config(api_base_url="www.api_base.com/") - web_base_url = config.server_config.get_web_base_url() - self.assertEqual(web_base_url, "www.api_base.com") - - def test_config_for_single_dataset(self): - file_name = self.custom_app_config( - config_file_name="single_dataset.yml", dataset_datapath=f"{FIXTURES_ROOT}/pbmc3k.cxg" - ) - config = AppConfig() - config.update_from_config_file(file_name) - config.server_config.handle_single_dataset(self.context) - self.assertIsNotNone(config.server_config.matrix_data_cache_manager) - - file_name = self.custom_app_config( - config_file_name="single_dataset_with_about.yml", - about="www.cziscience.com", - dataset_datapath=f"{FIXTURES_ROOT}/pbmc3k.cxg", - ) - config = AppConfig() - config.update_from_config_file(file_name) - with self.assertRaises(ConfigurationError): - config.server_config.handle_single_dataset(self.context) - - def test_multi_dataset_raises_error_for_illegal_routes(self): - # test for illegal url_dataroots - for illegal in ("../b", "!$*", "\\n", "", "(bad)"): - self.config.update_server_config( - multi_dataset__dataroot={"tag": {"base_url": illegal, "dataroot": f"{PROJECT_ROOT}/example-dataset"}} - ) - with self.assertRaises(ConfigurationError): - self.config.complete_config() - - def test_multidataset_works_for_legal_routes(self): - # test for legal url_dataroots - for legal in ("d", "this.is-okay_", "a/b"): - self.config.update_server_config( - multi_dataset__dataroot={"tag": {"base_url": legal, "dataroot": f"{PROJECT_ROOT}/example-dataset"}} - ) - self.config.complete_config() - - @patch("backend.czi_hosted.app.app.render_template") - def test_mulitdatasets_work_e2e(self, mock_render_template): - mock_render_template.return_value = "something" - # test that multi dataroots work end to end - self.config.update_server_config( - multi_dataset__dataroot=dict( - s1=dict(dataroot=f"{PROJECT_ROOT}/example-dataset", base_url="set1/1/2"), - s2=dict(dataroot=f"{FIXTURES_ROOT}", base_url="set2"), - s3=dict(dataroot=f"{FIXTURES_ROOT}", base_url="set3"), - ) - ) - - # Change this default to test if the dataroot overrides below work. - self.config.update_default_dataset_config(app__about_legal_tos="tos_default.html") - - # specialize the configs for set1 - self.config.add_dataroot_config( - "s1", user_annotations__enable=False, diffexp__enable=True, app__about_legal_tos="tos_set1.html" - ) - - # specialize the configs for set2 - self.config.add_dataroot_config( - "s2", user_annotations__enable=True, diffexp__enable=False, app__about_legal_tos="tos_set2.html" - ) - - # no specializations for set3 (they get the default dataset config) - self.config.complete_config() - - server = self.create_app(self.config) - server.auth.requires_client_login = lambda: False - server.testing = True - session = server.test_client() - - response = session.get(f"/set1/1/2/pbmc3k.h5ad/api/v0.2/config") - - data_config = json.loads(response.data) - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - assert data_config["config"]["parameters"]["annotations"] is False - assert data_config["config"]["parameters"]["disable-diffexp"] is False - assert data_config["config"]["parameters"]["about_legal_tos"] == "tos_set1.html" - - response = session.get("/set2/pbmc3k.cxg/api/v0.2/config") - - data_config = json.loads(response.data) - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - assert data_config["config"]["parameters"]["annotations"] is True - assert data_config["config"]["parameters"]["about_legal_tos"] == "tos_set2.html" - - response = session.get("/set3/pbmc3k.cxg/api/v0.2/config") - data_config = json.loads(response.data) - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - assert data_config["config"]["parameters"]["annotations"] is True - assert data_config["config"]["parameters"]["disable-diffexp"] is False - assert data_config["config"]["parameters"]["about_legal_tos"] == "tos_default.html" - - response = session.get("/health") - assert json.loads(response.data)["status"] == "pass" - - # access a dataset (no slash) - response = session.get("/set2/pbmc3k.cxg") - self.assertEqual(response.status_code, 200) - - # access a dataset (with slash) - response = session.get("/set2/pbmc3k.cxg/") - self.assertEqual(response.status_code, 200) - - @patch("backend.czi_hosted.common.config.server_config.diffexp_tiledb.set_config") - def test_handle_diffexp(self, mock_tiledb_config): - custom_config_file = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", - cpu_multiplier=3, - diffexp_max_workers=1, - target_workunit=4, - config_file_name=self.config_file_name, - ) - config = AppConfig() - config.update_from_config_file(custom_config_file) - config.server_config.handle_diffexp() - # called with the min of diffexp_max_workers and cpus*cpu_multiplier - mock_tiledb_config.assert_called_once_with(1, 4) - - @patch("backend.czi_hosted.data_cxg.cxg_adaptor.CxgAdaptor.set_tiledb_context") - def test_handle_adaptor(self, mock_tiledb_context): - custom_config = self.custom_app_config( - dataroot=f"{FIXTURES_ROOT}", cxg_tile_cache_size=10, cxg_num_reader_threads=2 - ) - config = AppConfig() - config.update_from_config_file(custom_config) - config.server_config.handle_adaptor() - mock_tiledb_context.assert_called_once_with( - {"sm.tile_cache_size": 10, "sm.num_reader_threads": 2, "vfs.s3.region": "us-east-1"} - ) - - def test_test_auth_only_in_insecure(self): - - config = self.get_config(auth_type="test") - with self.assertRaises(ConfigurationError): - config.complete_config() - - config.update_server_config(authentication__insecure_test_environment=True) - config.complete_config() diff --git a/backend/test/test_czi_hosted/unit/common/test_api.py b/backend/test/test_czi_hosted/unit/common/test_api.py deleted file mode 100644 index 6072ee53..00000000 --- a/backend/test/test_czi_hosted/unit/common/test_api.py +++ /dev/null @@ -1,505 +0,0 @@ -import json -import os -import time -from http import HTTPStatus -import hashlib - -import requests - - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import decode_fbs -from backend.test.fixtures.fixtures import pbmc3k_colors -from backend.test.test_czi_hosted.unit import BaseTest, skip_if - -BAD_FILTER = {"filter": {"obs": {"annotation_value": [{"name": "xyz"}]}}} - -class EndPoints(BaseTest): - @classmethod - def setUpClass(cls, app_config=None): - super().setUpClass(app_config) - cls.app.testing = True - cls.client = cls.app.test_client() - os.environ["SKIP_STATIC"] = "True" - for i in range(90): - try: - result = cls.client.get(f"{cls.TEST_URL_BASE}schema") - cls.schema = json.loads(result.data) - except requests.exceptions.ConnectionError: - time.sleep(1) - - def test_initialize(self): - endpoint = "schema" - url = f"{self.TEST_URL_BASE}{endpoint}" - result = self.client.get(url) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertEqual(result_data["schema"]["dataframe"]["nObs"], 2638) - self.assertEqual(len(result_data["schema"]["annotations"]["obs"]), 2) - self.assertEqual( - len(result_data["schema"]["annotations"]["obs"]["columns"]), 5 - ) - - def test_config(self): - endpoint = "config" - url = f"{self.TEST_URL_BASE}{endpoint}" - result = self.client.get(url) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertIn("library_versions", result_data["config"]) - self.assertEqual(result_data["config"]["displayNames"]["dataset"], "pbmc3k") - - def test_get_layout_fbs(self): - endpoint = "layout/obs" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 8) - self.assertIsNotNone(df["columns"]) - self.assertSetEqual( - set(df["col_idx"]), - {"pca_0", "pca_1", "tsne_0", "tsne_1", "umap_0", "umap_1", "draw_graph_fr_0", "draw_graph_fr_1"}, - ) - self.assertIsNone(df["row_idx"]) - self.assertEqual(len(df["columns"]), df["n_cols"]) - - def test_bad_filter(self): - endpoint = "data/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.client.put(url, headers=header, json=BAD_FILTER) - self.assertEqual(result.status_code, HTTPStatus.BAD_REQUEST) - - def test_get_annotations_obs_fbs(self): - endpoint = "annotations/obs" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 5) - self.assertIsNotNone(df["columns"]) - self.assertIsNone(df["row_idx"]) - self.assertEqual(len(df["columns"]), df["n_cols"]) - obs_index_col_name = self.schema["schema"]["annotations"]["obs"]["index"] - self.assertCountEqual( - df["col_idx"], - [obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain"], - ) - - def test_get_annotations_obs_keys_fbs(self): - endpoint = "annotations/obs" - query = "annotation-name=n_genes&annotation-name=percent_mito" - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 2) - self.assertIsNotNone(df["columns"]) - self.assertIsNone(df["row_idx"]) - self.assertEqual(len(df["columns"]), df["n_cols"]) - self.assertCountEqual(df["col_idx"], ["n_genes", "percent_mito"]) - - def test_get_annotations_obs_error(self): - endpoint = "annotations/obs" - query = "annotation-name=notakey" - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.BAD_REQUEST) - -# TEMP: Testing count 15 to match hardcoded values for diffexp -# TODO(#1281): Switch back to dynamic values - def test_diff_exp(self): - endpoint = "diffexp/obs" - url = f"{self.TEST_URL_BASE}{endpoint}" - params = { - "mode": "topN", - "set1": {"filter": {"obs": {"annotation_value": [{"name": "louvain", "values": ["NK cells"]}]}}}, - "set2": {"filter": {"obs": {"annotation_value": [{"name": "louvain", "values": ["CD8 T cells"]}]}}}, - "count": 15, - } - result = self.client.post(url, json=params) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertEqual(len(result_data['positive']), 15) - self.assertEqual(len(result_data['negative']), 15) - - def test_diff_exp_indices(self): - endpoint = "diffexp/obs" - url = f"{self.TEST_URL_BASE}{endpoint}" - params = { - "mode": "topN", - "count": 15, - "set1": {"filter": {"obs": {"index": [[0, 500]]}}}, - "set2": {"filter": {"obs": {"index": [[500, 1000]]}}}, - } - result = self.client.post(url, json=params) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertEqual(len(result_data['positive']), 15) - self.assertEqual(len(result_data['negative']), 15) - - def test_get_annotations_var_fbs(self): - endpoint = "annotations/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 1838) - self.assertEqual(df["n_cols"], 2) - self.assertIsNotNone(df["columns"]) - self.assertIsNone(df["row_idx"]) - self.assertEqual(len(df["columns"]), df["n_cols"]) - var_index_col_name = self.schema["schema"]["annotations"]["var"]["index"] - self.assertCountEqual(df["col_idx"], [var_index_col_name, "n_cells"]) - - def test_get_annotations_var_keys_fbs(self): - endpoint = "annotations/var" - query = "annotation-name=n_cells" - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 1838) - self.assertEqual(df["n_cols"], 1) - self.assertIsNotNone(df["columns"]) - self.assertIsNone(df["row_idx"]) - self.assertEqual(len(df["columns"]), df["n_cols"]) - self.assertCountEqual(df["col_idx"], ["n_cells"]) - - def test_get_annotations_var_error(self): - endpoint = "annotations/var" - query = "annotation-name=notakey" - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.BAD_REQUEST) - - def test_data_mimetype_error(self): - endpoint = "data/var" - header = {"Accept": "xxx"} - url = f"{self.TEST_URL_BASE}{endpoint}" - result = self.client.put(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.NOT_ACCEPTABLE) - - def test_fbs_default(self): - endpoint = "data/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - headers = {"Accept": "application/octet-stream"} - result = self.client.put(url, headers=headers) - self.assertEqual(result.status_code, HTTPStatus.BAD_REQUEST) - - filter = {"filter": {"var": {"index": [0, 1, 4]}}} - result = self.client.put(url, headers=headers, json=filter) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - - def test_data_put_fbs(self): - endpoint = "data/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.client.put(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.BAD_REQUEST) - - def test_data_get_fbs(self): - endpoint = "data/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.BAD_REQUEST) - - def test_data_put_filter_fbs(self): - endpoint = "data/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - filter = {"filter": {"var": {"index": [0, 1, 4]}}} - result = self.client.put(url, headers=header, json=filter) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 3) - self.assertIsNotNone(df["columns"]) - self.assertIsNone(df["row_idx"]) - self.assertEqual(len(df["columns"]), df["n_cols"]) - self.assertListEqual(df["col_idx"].tolist(), [0, 1, 4]) - - def test_data_get_filter_fbs(self): - index_col_name = self.schema["schema"]["annotations"]["var"]["index"] - endpoint = "data/var" - query = f"var:{index_col_name}=SIK1" - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 1) - - def test_data_get_unknown_filter_fbs(self): - index_col_name = self.schema["schema"]["annotations"]["var"]["index"] - endpoint = "data/var" - query = f"var:{index_col_name}=UNKNOWN" - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 0) - - def test_data_put_single_var(self): - endpoint = "data/var" - url = f"{self.TEST_URL_BASE}{endpoint}" - header = {"Accept": "application/octet-stream"} - index_col_name = self.schema["schema"]["annotations"]["var"]["index"] - var_filter = {"filter": {"var": {"annotation_value": [{"name": index_col_name, "values": ["RER1"]}]}}} - result = self.client.put(url, headers=header, json=var_filter) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 1) - - def test_colors(self): - endpoint = "colors" - url = f"{self.TEST_URL_BASE}{endpoint}" - result = self.client.get(url) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertEqual(result_data, pbmc3k_colors) - - @skip_if(lambda x: os.getenv("SKIP_STATIC"), "Skip static test when running locally") - def test_static(self): - endpoint = "static" - file = "assets/favicon.ico" - url = f"{endpoint}/{file}" - result = self.client.get(url) - self.assertEqual(result.status_code, HTTPStatus.OK) - - def test_genesets_config(self): - result = self.client.get(f"{self.TEST_URL_BASE}config") - config_data = json.loads(result.data) - params = config_data["config"]["parameters"] - annotations_genesets = params["annotations_genesets"] - annotations_genesets_readonly = params["annotations_genesets_readonly"] - annotations_genesets_summary_methods = params["annotations_genesets_summary_methods"] - self.assertTrue(annotations_genesets) - self.assertTrue(annotations_genesets_readonly) - self.assertEqual(annotations_genesets_summary_methods, ["mean"]) - - def test_get_genesets(self): - endpoint = "genesets" - url = f"{self.TEST_URL_BASE}{endpoint}" - result = self.client.get(url, headers={"Accept": "application/json"}) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertIsNotNone(result_data["genesets"]) - - def test_get_summaryvar(self): - index_col_name = self.schema["schema"]["annotations"]["var"]["index"] - endpoint = "summarize/var" - - # single column - filter = f"var:{index_col_name}=F5" - query = f"method=mean&{filter}" - query_hash = hashlib.sha1(query.encode()).hexdigest() - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 1) - self.assertEqual(df["col_idx"], [query_hash]) - self.assertAlmostEqual(df["columns"][0][0], -0.110451095) - - # multi-column - col_names = ["F5", "BEB3", "SIK1"] - filter = "&".join([f"var:{index_col_name}={name}" for name in col_names]) - query = f"method=mean&{filter}" - query_hash = hashlib.sha1(query.encode()).hexdigest() - url = f"{self.TEST_URL_BASE}{endpoint}?{query}" - header = {"Accept": "application/octet-stream"} - result = self.client.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 1) - self.assertEqual(df["col_idx"], [query_hash]) - self.assertAlmostEqual(df["columns"][0][0], -0.16628358) - - def test_post_summaryvar(self): - index_col_name = self.schema["schema"]["annotations"]["var"]["index"] - endpoint = "summarize/var" - headers = {"Content-Type": "application/x-www-form-urlencoded", "Accept": "application/octet-stream"} - - # single column - filter = f"var:{index_col_name}=F5" - query = f"method=mean&{filter}" - query_hash = hashlib.sha1(query.encode()).hexdigest() - url = f"{self.TEST_URL_BASE}{endpoint}?key={query_hash}" - result = self.client.post(url, headers=headers, data=query) - - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 1) - self.assertEqual(df["col_idx"], [query_hash]) - self.assertAlmostEqual(df["columns"][0][0], -0.110451095) - - # multi-column - col_names = ["F5", "BEB3", "SIK1"] - filter = "&".join([f"var:{index_col_name}={name}" for name in col_names]) - query = f"method=mean&{filter}" - query_hash = hashlib.sha1(query.encode()).hexdigest() - url = f"{self.TEST_URL_BASE}{endpoint}?key={query_hash}" - result = self.client.post(url, headers=headers, data=query) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertEqual(df["n_rows"], 2638) - self.assertEqual(df["n_cols"], 1) - self.assertEqual(df["col_idx"], [query_hash]) - self.assertAlmostEqual(df["columns"][0][0], -0.16628358) - - - -class EndPointsCxg(EndPoints): - """Test Case for endpoints""" - @classmethod - def setUpClass(cls): - app_config = AppConfig() - app_config.update_default_dataset_config(user_annotations__enable=False) - - def test_get_genesets_json(self): - self.app.auth.is_user_authenticated = lambda: True - endpoint = "genesets" - url = f"{self.TEST_URL_BASE}{endpoint}" - result = self.client.get(url, headers={"Accept": "application/json"}) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - result_data = json.loads(result.data) - self.assertIsNotNone(result_data["genesets"]) - self.assertIsNotNone(result_data["tid"]) - - self.assertEqual( - result_data, - { - "genesets": [ - { - "genes": [ - {"gene_description": " a gene_description", "gene_symbol": "F5"}, - {"gene_description": "", "gene_symbol": "SUMO3"}, - {"gene_description": "", "gene_symbol": "SRM"}, - ], - "geneset_description": "a description", - "geneset_name": "first gene set name", - }, - { - "genes": [ - {"gene_description": "", "gene_symbol": "RER1"}, - {"gene_description": "", "gene_symbol": "SIK1"}, - ], - "geneset_description": "", - "geneset_name": "second_gene_set", - }, - {"genes": [], "geneset_description": "", "geneset_name": "third gene set"}, - {"genes": [], "geneset_description": "fourth description", "geneset_name": "fourth_gene_set"}, - {"genes": [], "geneset_description": "", "geneset_name": "fifth_dataset"}, - { - "genes": [ - {"gene_description": "", "gene_symbol": "ACD"}, - {"gene_description": "", "gene_symbol": "AATF"}, - {"gene_description": "", "gene_symbol": "F5"}, - {"gene_description": "", "gene_symbol": "PIGU"}, - ], - "geneset_description": "", - "geneset_name": "summary test", - }, - {'genes': [], 'geneset_description': '', 'geneset_name': 'geneset_to_delete'}, - {'genes': [], 'geneset_description': '', 'geneset_name': 'geneset_to_edit'}, - { - 'genes': [], - 'geneset_description': '', - 'geneset_name': 'fill_this_geneset' - }, - { - 'genes': [{'gene_description': '', 'gene_symbol': 'SIK1'}], - 'geneset_description': '', - 'geneset_name': 'empty_this_geneset' - }, - { - 'genes': [{'gene_description': '', 'gene_symbol': 'SIK1'}], - 'geneset_description': '', - 'geneset_name': 'brush_this_gene' - } - ], - "tid": 0, - }, - ) - - def test_get_genesets_csv(self): - endpoint = "genesets" - url = f"{self.TEST_URL_BASE}{endpoint}" - self.app.auth.is_user_authenticated = lambda: True - result = self.client.get(url, headers={"Accept": "text/csv"}) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "text/csv") - expected_data = """gene_set_name,gene_set_description,gene_symbol,gene_description\r -first gene set name,a description,F5, a gene_description\r -first gene set name,a description,SUMO3,\r -first gene set name,a description,SRM,\r -second_gene_set,,RER1,\r -second_gene_set,,SIK1,\r -third gene set,,,\r -fourth_gene_set,fourth description,,\r -fifth_dataset,,,\r -summary test,,ACD,\r -summary test,,AATF,\r -summary test,,F5,\r -summary test,,PIGU,\r -geneset_to_delete,,,\r -geneset_to_edit,,,\r -fill_this_geneset,,,\r -empty_this_geneset,,SIK1,\r -brush_this_gene,,SIK1,\r -""" - self.assertEqual(result.data.decode("utf-8"), expected_data) - - def test_put_genesets(self): - endpoint = "genesets" - url = f"{self.TEST_URL_BASE}{endpoint}" - - result = self.client.get(url, headers={"Accept": "application/json"}) - self.assertEqual(result.status_code, HTTPStatus.OK) - - test1 = {"tid": 3, "genesets": []} - result = self.client.put(url, json=test1) - - self.assertEqual(result.status_code, HTTPStatus.METHOD_NOT_ALLOWED) - diff --git a/backend/test/test_czi_hosted/unit/common/test_corpora.py b/backend/test/test_czi_hosted/unit/common/test_corpora.py deleted file mode 100644 index edec33bb..00000000 --- a/backend/test/test_czi_hosted/unit/common/test_corpora.py +++ /dev/null @@ -1,168 +0,0 @@ -import json -import shutil -import tempfile -import unittest -from http import HTTPStatus - -import anndata - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.czi_hosted.common.corpora import ( - corpora_get_versions_from_anndata, - corpora_is_version_supported, - corpora_get_props_from_anndata, -) -from backend.test.test_czi_hosted.unit import BaseTest -from backend.test import PROJECT_ROOT - -VERSION = "v0.2" - - -class CorporaAPITest(unittest.TestCase): - def test_corpora_get_versions_from_anndata(self): - adata = self._get_h5ad() - - if "version" in adata.uns: - del adata.uns["version"] - self.assertIsNone(corpora_get_versions_from_anndata(adata)) - - # something bogus - adata.uns["version"] = 99 - self.assertIsNone(corpora_get_versions_from_anndata(adata)) - - # something legit - adata.uns["version"] = {"corpora_schema_version": "0.0.0", "corpora_encoding_version": "9.9.9"} - self.assertEqual(corpora_get_versions_from_anndata(adata), ["0.0.0", "9.9.9"]) - - def test_corpora_is_version_supported(self): - self.assertTrue(corpora_is_version_supported("1.0.0", "0.1.0")) - self.assertFalse(corpora_is_version_supported("0.0.0", "0.1.0")) - self.assertFalse(corpora_is_version_supported("1.0.0", "0.0.0")) - - def test_corpora_get_props_from_anndata(self): - adata = self._get_h5ad() - - if "version" in adata.uns: - del adata.uns["version"] - self.assertIsNone(corpora_get_props_from_anndata(adata)) - - # something bogus - adata.uns["version"] = 99 - self.assertIsNone(corpora_get_props_from_anndata(adata)) - - # unsupported version, but missing required values - adata.uns["version"] = {"corpora_schema_version": "99.0.0", "corpora_encoding_version": "32.1.0"} - with self.assertRaises(ValueError): - corpora_get_props_from_anndata(adata) - - # legit version, but missing required values - adata.uns["version"] = {"corpora_schema_version": "1.0.0", "corpora_encoding_version": "0.1.0"} - with self.assertRaises(KeyError): - corpora_get_props_from_anndata(adata) - - some_fields = { - "version": {"corpora_schema_version": "1.0.0", "corpora_encoding_version": "0.1.0"}, - "title": "title", - "layer_descriptions": "layer_descriptions", - "organism": "organism", - "organism_ontology_term_id": "organism_ontology_term_id", - "project_name": "project_name", - "project_description": "project_description", - "contributors": json.dumps([{"contributors": "contributors"}]), - "project_links": json.dumps([{"link_name": "link_name", "link_url": "link_url", "link_type": "SUMMARY"}]), - } - for k in some_fields: - adata.uns[k] = some_fields[k] - some_fields["contributors"] = json.loads(some_fields["contributors"]) - some_fields["project_links"] = json.loads(some_fields["project_links"]) - self.assertEqual(corpora_get_props_from_anndata(adata), some_fields) - - def test_corpora_get_props_from_anndata_v110(self): - adata = self._get_h5ad() - - if "version" in adata.uns: - del adata.uns["version"] - self.assertIsNone(corpora_get_props_from_anndata(adata)) - - # legit version, but missing required values - adata.uns["version"] = {"corpora_schema_version": "1.1.0", "corpora_encoding_version": "0.1.0"} - with self.assertRaises(KeyError): - corpora_get_props_from_anndata(adata) - - # Metadata following schema 1.1.0, which removes some fields relative to 1.1.0 - some_110_fields = { - "version": {"corpora_schema_version": "1.0.0", "corpora_encoding_version": "0.1.0"}, - "title": "title", - "layer_descriptions": "layer_descriptions", - "organism": "organism", - "organism_ontology_term_id": "organism_ontology_term_id", - } - for k in some_110_fields: - adata.uns[k] = some_110_fields[k] - self.assertEqual(corpora_get_props_from_anndata(adata), some_110_fields) - - def _get_h5ad(self): - return anndata.read_h5ad(f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad") - - -class CorporaRESTAPITest(BaseTest): - """ Confirm endpoints reflect Corpora-specific features """ - - @classmethod - def setCorporaFields(cls, path): - adata = anndata.read_h5ad(path) - corpora_props = { - "version": {"corpora_schema_version": "1.0.0", "corpora_encoding_version": "0.1.0"}, - "title": "PBMC3K", - "contributors": json.dumps([{"name": "name"}]), - "layer_descriptions": {"X": "raw counts"}, - "organism": "human", - "organism_ontology_term_id": "unknown", - "project_name": "test project", - "project_description": "test description", - "project_links": json.dumps( - [{"link_name": "test link", "link_type": "SUMMARY", "link_url": "https://a.u.r.l/"}] - ), - "default_embedding": "X_tsne", - } - adata.uns.update(corpora_props) - adata.write(path) - - @classmethod - def setUpClass(cls, app_config=None): - if not app_config: - app_config = AppConfig() - cls.tmp_dir = tempfile.TemporaryDirectory() - src = f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad" - dst = f"{cls.tmp_dir.name}/pbmc3k.h5ad" - shutil.copyfile(src, dst) - cls.setCorporaFields(dst) - app_config.update_server_config(single_dataset__datapath=dst) - - super().setUpClass(app_config) - cls.app.testing = True - cls.client = cls.app.test_client() - - def setUp(self): - self.session = self.client - self.url_base = "/api/v0.2/" - - def test_config(self): - endpoint = "config" - url = f"{self.url_base}{endpoint}" - header = {"Content-Type": "application/json"} - result = self.session.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/json") - - result_data = json.loads(result.data) - self.assertIsInstance(result_data["config"]["corpora_props"], dict) - self.assertIsInstance(result_data["config"]["parameters"], dict) - - corpora_props = result_data["config"]["corpora_props"] - parameters = result_data["config"]["parameters"] - - self.assertEqual(corpora_props["version"]["corpora_schema_version"], "1.0.0") - - self.assertEqual(corpora_props["organism"], "human") - self.assertEqual(parameters["default_embedding"], "tsne") diff --git a/backend/test/test_czi_hosted/unit/common/test_nan_rest.py b/backend/test/test_czi_hosted/unit/common/test_nan_rest.py deleted file mode 100644 index a5ba0059..00000000 --- a/backend/test/test_czi_hosted/unit/common/test_nan_rest.py +++ /dev/null @@ -1,65 +0,0 @@ -from http import HTTPStatus -import math - -import backend.test.decode_fbs as decode_fbs - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import FIXTURES_ROOT -from backend.test.test_czi_hosted.unit import BaseTest - -VERSION = "v0.2" -BAD_FILTER = {"filter": {"obs": {"annotation_value": [{"name": "xyz"}]}}} - - -class WithNaNs(BaseTest): - """Test Case for endpoints""" - - @classmethod - def setUpClass(cls): - app_config = AppConfig() - app_config.update_server_config(single_dataset__datapath=f"{FIXTURES_ROOT}/nan.h5ad") - app_config.update_default_dataset_config(user_annotations__enable=True) - super().setUpClass(app_config) - cls.app.testing = True - cls.client = cls.app.test_client() - - def setUp(self): - self.session = self.client - self.url_base = "api/v0.2/" - - def test_initialize(self): - endpoint = "schema" - url = f"{self.url_base}{endpoint}" - result = self.session.get(url) - self.assertEqual(result.status_code, HTTPStatus.OK) - - def test_data(self): - endpoint = "data/var" - url = f"{self.url_base}{endpoint}" - filter = {"filter": {"var": {"index": [[0, 20]]}}} - header = {"Accept": "application/octet-stream"} - result = self.session.put(url, headers=header, json=filter) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertTrue(math.isnan(df["columns"][3][3])) - - def test_annotation_obs(self): - endpoint = "annotations/obs" - url = f"{self.url_base}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.session.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertTrue(math.isnan(df["columns"][2][0])) - - def test_annotation_var(self): - endpoint = "annotations/var" - url = f"{self.url_base}{endpoint}" - header = {"Accept": "application/octet-stream"} - result = self.session.get(url, headers=header) - self.assertEqual(result.status_code, HTTPStatus.OK) - self.assertEqual(result.headers["Content-Type"], "application/octet-stream") - df = decode_fbs.decode_matrix_FBS(result.data) - self.assertTrue(math.isnan(df["columns"][2][0])) diff --git a/backend/test/test_czi_hosted/unit/common/test_rest.py b/backend/test/test_czi_hosted/unit/common/test_rest.py deleted file mode 100644 index 8b8151b3..00000000 --- a/backend/test/test_czi_hosted/unit/common/test_rest.py +++ /dev/null @@ -1,79 +0,0 @@ -import unittest -from urllib.parse import parse_qs -from werkzeug.datastructures import MultiDict -from backend.common.errors import FilterError -from backend.czi_hosted.common.rest import _query_parameter_to_filter - - -def _qsparse(qs): - """ emulate what Flask/Werkzeug do to our QS """ - return MultiDict(parse_qs(qs)) - - -class FilterParseTests(unittest.TestCase): - """ Test cases for various filter parsing """ - - def test_queryparam_to_filter_parse(self): - # categories - self.assertEqual( - _query_parameter_to_filter(_qsparse("obs:foo=bar&var:baz=133&var:baz=A&obs:baz=foo")), - { - "obs": {"annotation_value": [{"name": "foo", "values": ["bar"]}, {"name": "baz", "values": ["foo"]}]}, - "var": {"annotation_value": [{"name": "baz", "values": ["133", "A"]}]}, - }, - ) - - # ranges - self.assertEqual( - _query_parameter_to_filter(_qsparse("obs:A=1,99&obs:B=*,100&obs:C=0,*")), - { - "obs": { - "annotation_value": [ - {"name": "A", "min": 1, "max": 99.0}, - {"name": "B", "max": 100.0}, - {"name": "C", "min": 0.0}, - ] - }, - }, - ) - - # combo - self.assertEqual( - _query_parameter_to_filter(_qsparse("var:B=YES&var:A=1,99&var:B=NO")), - { - "var": { - "annotation_value": [ - {"name": "B", "values": ["YES", "NO"]}, - {"name": "A", "min": 1.0, "max": 99.0}, - ] - }, - }, - ) - - def test_queryparam_to_filter_escaping(self): - self.assertEqual( - _query_parameter_to_filter(_qsparse("obs:var=%2521%252C%253AOK%253D&obs:A%2521=YO")), - {"obs": {"annotation_value": [{"name": "var", "values": ["!,:OK="]}, {"name": "A!", "values": ["YO"]}]}}, - ) - - def test_queryparam_to_filter_errors(self): - - # should raise FilterError - filter_errors = [ - "foo=bar", # no axis - "X=&Y=3", # no value - "X&Y=3", # no value - "moo:foo=bar", # bad axis - "obs:x=1,A", # non-numeric range - "var:X=1,2&var:X=3,4", # duplicate ranges - "var:Y=,", - "var:Y=2,", - "var:Y=,5", - "var:Y=*,", - "var:Y=,*", - "var:Y=*,*", - ] - - for qs in filter_errors: - with self.assertRaises(FilterError): - _query_parameter_to_filter(_qsparse(qs)) diff --git a/backend/test/test_czi_hosted/unit/common/test_writable_annotation.py b/backend/test/test_czi_hosted/unit/common/test_writable_annotation.py deleted file mode 100644 index 5b2faf8b..00000000 --- a/backend/test/test_czi_hosted/unit/common/test_writable_annotation.py +++ /dev/null @@ -1,317 +0,0 @@ -import json -import shutil -import unittest -from os import path, listdir -from unittest.mock import MagicMock - -import numpy as np -import pandas as pd -import tiledb -from flask import Flask - -from backend.common.errors import AnnotationCategoryNameError -from backend.czi_hosted.common.rest import annotations_put_fbs_helper, schema_get_helper -from backend.czi_hosted.data_common.matrix_loader import MatrixDataType -from backend.czi_hosted.db.cellxgene_orm import CellxGeneDataset, Annotation -from backend.test.fixtures.database import TestDatabase -from backend.test.test_czi_hosted.unit import make_fbs, data_with_tmp_tiledb_annotations, data_with_tmp_annotations -from backend.test import decode_fbs - -TestDatabase() - -class auth(object): - def get_user_id(): - return "1234" - - def get_user_name(): - return "person name" - - -class WritableTileDBStoredAnnotationTest(unittest.TestCase): - def setUp(self): - self.user_id = "1234" - self.data, self.tmp_dir, self.annotations = data_with_tmp_tiledb_annotations(MatrixDataType.H5AD) - self.data.dataset_config.user_annotations = self.annotations - self.db = self.annotations.db - self.n_rows = self.data.get_shape()[0] - self.test_dict = { - "cat_A": pd.Series(["label_A"] * self.n_rows, dtype="category"), - "cat_B": pd.Series(["label_B"] * self.n_rows, dtype="category"), - } - self.fbs = make_fbs(self.test_dict) - self.df = pd.DataFrame(self.test_dict) - self.app = Flask("fake_app") - self.app.__setattr__("auth", auth) - - def tearDown(self): - shutil.rmtree(self.tmp_dir) - - def annotation_put_fbs(self, fbs): - annotations_put_fbs_helper(self.data, fbs) - res = json.dumps({"status": "OK"}) - return res - - def test_category_name_throws_errors_for_categories_that_cant_be_converted_to_filenames(self): - with self.app.test_request_context(): - bad_category_names = make_fbs( - { - "cat_A": pd.Series(["label_A"] * self.n_rows, dtype="category"), - "cat/B": pd.Series(["label_B"] * self.n_rows, dtype="category"), - } - ) - with self.assertRaises(AnnotationCategoryNameError): - self.annotation_put_fbs(bad_category_names) - - def test_convert_to_pandas__converts_tiledb_to_pandas_df(self): - with self.app.test_request_context(): - self.annotations.write_labels(self.df, self.data) - dataset_id = self.db.query([CellxGeneDataset], [CellxGeneDataset.name == self.data.get_location()])[0].id - annotation = self.db.query_for_most_recent( - Annotation, [Annotation.user_id == self.user_id, Annotation.dataset_id == str(dataset_id)] - ) - # retrieve tiledb array - df = tiledb.open(annotation.tiledb_uri) - self.assertEqual(type(df), tiledb.array.SparseArray) - - # convert to pandas df - pandas_df = self.annotations.convert_to_pandas_df(df, annotation.schema_hints) - self.assertEqual(type(pandas_df), pd.DataFrame) - - def test_write_labels_creates_a_dataset_if_it_doesnt_exist(self): - with self.app.test_request_context(): - new_name = "new_dataset/location" - self.data.get_location = MagicMock(return_value=new_name) - num_datasets = len(self.db.query([CellxGeneDataset])) - self.annotation_put_fbs(self.fbs) - more_datasets = len(self.db.query([CellxGeneDataset])) - self.assertGreater(more_datasets, num_datasets) - - self.assertGreater(len(self.db.query([CellxGeneDataset], [CellxGeneDataset.name == new_name])), 0) - - def test_write_labels_links_to_existing_dataset(self): - with self.app.test_request_context(): - # add dataset to to db - self.annotation_put_fbs(self.fbs) - - num_datasets = len(self.db.query([CellxGeneDataset])) - - # create another annotation with the same dataset - self.annotation_put_fbs(self.fbs) - - same_num_datasets = len(self.db.query([CellxGeneDataset])) - - self.assertEqual(num_datasets, same_num_datasets) - - def test_read_labels_returns_pandas_df(self): - with self.app.test_request_context(): - self.annotation_put_fbs(self.fbs) - pandas_df = self.annotations.read_labels(self.data) - self.assertEqual(type(pandas_df), pd.DataFrame) - - def test_read_labels_returns_df_matching_original(self): - with self.app.test_request_context(): - self.annotation_put_fbs(self.fbs) - pandas_df = self.annotations.read_labels(self.data) - - self.assertEqual(pandas_df.shape, (self.n_rows, 2)) - self.assertEqual(set(pandas_df.columns), {"cat_A", "cat_B"}) - - self.assertTrue(self.data.original_obs_index.equals(pandas_df.index)) - - self.assertTrue(np.all(pandas_df["cat_A"] == ["label_A"] * self.n_rows)) - self.assertTrue(np.all(pandas_df["cat_B"] == ["label_B"] * self.n_rows)) - - def test_error_checks(self): - # verify that the expected errors are generated - with self.app.test_request_context(): - n_rows = self.data.get_shape()[0] - fbs_bad = make_fbs({"louvain": pd.Series(["undefined"] * n_rows, dtype="category")}) - - # ensure we catch attempt to overwrite non-writable data - with self.assertRaises(KeyError): - self.annotation_put_fbs(fbs_bad) - - def test_write_labels_stores_df_as_tiledb_array(self): - with self.app.test_request_context(): - self.annotations.write_labels(self.df, self.data) - # get uri - dataset_id = self.db.query([CellxGeneDataset], [CellxGeneDataset.name == self.data.get_location()])[0].id - annotation = self.db.query_for_most_recent( - Annotation, [Annotation.user_id == "1234", Annotation.dataset_id == str(dataset_id)] - ) - - df = tiledb.open(annotation.tiledb_uri) - self.assertEqual(type(df), tiledb.array.SparseArray) - - def test_remove_categories(self): - with self.app.test_request_context(): - # update empty category data, which is how annotations are removed - empty = make_fbs({}) - self.annotation_put_fbs(empty) - - # verify that the tiledb uri is an empty string. - dataset_id = self.db.query([CellxGeneDataset], [CellxGeneDataset.name == self.data.get_location()])[0].id - annotation = self.db.query_for_most_recent( - Annotation, [Annotation.user_id == self.user_id, Annotation.dataset_id == str(dataset_id)] - ) - self.assertEqual(annotation.tiledb_uri, "") - - # verify that read_labels returns None - df = self.annotations.read_labels(self.data) - self.assertIsNone(df) - - -class WritableAnnotationTest(unittest.TestCase): - def setUp(self): - self.data, self.tmp_dir, self.annotations, self.config= data_with_tmp_annotations(MatrixDataType.H5AD) - self.data.dataset_config.user_annotations = self.annotations - - def tearDown(self): - shutil.rmtree(self.tmp_dir) - - def annotation_put_fbs(self, fbs): - annotations_put_fbs_helper(self.data, fbs) - res = json.dumps({"status": "OK"}) - return res - - def test_error_checks(self): - # verify that the expected errors are generated - n_rows = self.data.get_shape()[0] - fbs_bad = make_fbs({"louvain": pd.Series(["undefined"] * n_rows, dtype="category")}) - - # ensure we catch attempt to overwrite non-writable data - with self.assertRaises(KeyError): - self.annotation_put_fbs(fbs_bad) - - def test_write_to_file(self): - # verify the file is written as expected - n_rows = self.data.get_shape()[0] - fbs = make_fbs( - { - "cat_A": pd.Series(["label_A"] * n_rows, dtype="category"), - "cat_B": pd.Series(["label_B"] * n_rows, dtype="category"), - } - ) - res = self.annotation_put_fbs(fbs) - self.assertEqual(res, json.dumps({"status": "OK"})) - self.assertTrue(path.exists(self.annotations.output_file)) - df = pd.read_csv(self.annotations.output_file, index_col=0, header=0, comment="#") - self.assertEqual(df.shape, (n_rows, 2)) - self.assertEqual(set(df.columns), {"cat_A", "cat_B"}) - self.assertTrue(self.data.original_obs_index.equals(df.index)) - self.assertTrue(np.all(df["cat_A"] == ["label_A"] * n_rows)) - self.assertTrue(np.all(df["cat_B"] == ["label_B"] * n_rows)) - - # verify complete overwrite on second attempt, AND rotation occurs - fbs = make_fbs( - { - "cat_A": pd.Series(["label_A1"] * n_rows, dtype="category"), - "cat_C": pd.Series(["label_C"] * n_rows, dtype="category"), - } - ) - res = self.annotation_put_fbs(fbs) - self.assertEqual(res, json.dumps({"status": "OK"})) - self.assertTrue(path.exists(self.annotations.output_file)) - df = pd.read_csv(self.annotations.output_file, index_col=0, header=0, comment="#") - self.assertEqual(set(df.columns), {"cat_A", "cat_C"}) - self.assertTrue(np.all(df["cat_A"] == ["label_A1"] * n_rows)) - self.assertTrue(np.all(df["cat_C"] == ["label_C"] * n_rows)) - - # rotation - name, ext = path.splitext(self.annotations.output_file) - backup_dir = f"{name}-backups" - self.assertTrue(path.isdir(backup_dir)) - found_files = listdir(backup_dir) - self.assertEqual(len(found_files), 1) - - def test_file_rotation_to_max_9(self): - # verify we stop rotation at 9 - n_rows = self.data.get_shape()[0] - fbs = make_fbs( - { - "cat_A": pd.Series(["label_A"] * n_rows, dtype="category"), - "cat_B": pd.Series(["label_B"] * n_rows, dtype="category"), - } - ) - for i in range(0, 11): - res = self.annotation_put_fbs(fbs) - self.assertEqual(res, json.dumps({"status": "OK"})) - - name, ext = path.splitext(self.annotations.output_file) - backup_dir = f"{name}-backups" - self.assertTrue(path.isdir(backup_dir)) - found_files = listdir(backup_dir) - self.assertTrue(len(found_files) <= 9) - - def test_put_get_roundtrip(self): - # verify that OBS PUTs (annotation_put_fbs) are accessible via - # GET (annotation_to_fbs_matrix) - - n_rows = self.data.get_shape()[0] - fbs = make_fbs( - { - "cat_A": pd.Series(["label_A"] * n_rows, dtype="category"), - "cat_B": pd.Series(["label_B"] * n_rows, dtype="category"), - } - ) - - # put - res = self.annotation_put_fbs(fbs) - self.assertEqual(res, json.dumps({"status": "OK"})) - - # get - labels = self.annotations.read_labels(None) - fbsAll = self.data.annotation_to_fbs_matrix("obs", None, labels) - schema = schema_get_helper(self.data) - annotations = decode_fbs.decode_matrix_FBS(fbsAll) - obs_index_col_name = schema["annotations"]["obs"]["index"] - self.assertEqual(annotations["n_rows"], n_rows) - self.assertEqual(annotations["n_cols"], 7) - self.assertIsNone(annotations["row_idx"]) - self.assertEqual( - annotations["col_idx"], - [obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain", "cat_A", "cat_B"], - ) - col_idx = annotations["col_idx"] - self.assertEqual(annotations["columns"][col_idx.index("cat_A")], ["label_A"] * n_rows) - self.assertEqual(annotations["columns"][col_idx.index("cat_B")], ["label_B"] * n_rows) - - # verify the schema was updated - all_col_schema = {c["name"]: c for c in schema["annotations"]["obs"]["columns"]} - self.assertEqual( - all_col_schema["cat_A"], - {"name": "cat_A", "type": "categorical", "categories": ["label_A"], "writable": True}, - ) - self.assertEqual( - all_col_schema["cat_B"], - {"name": "cat_B", "type": "categorical", "categories": ["label_B"], "writable": True}, - ) - - def test_put_float_data(self): - # verify that OBS PUTs (annotation_put_fbs) are accessible via - # GET (annotation_to_fbs_matrix) - - n_rows = self.data.get_shape()[0] - - # verifies that floating point with decimals fail. - fbs = make_fbs({"cat_F_FAIL": pd.Series([1.1] * n_rows, dtype=np.dtype("float"))}) - with self.assertRaises(ValueError) as exception_context: - res = self.annotation_put_fbs(fbs) - self.assertEqual(str(exception_context.exception), "Columns may not have floating point types") - - # verifies that floating point that can be converted to int passes - fbs = make_fbs({"cat_F_PASS": pd.Series([1.0] * n_rows, dtype="float")}) - res = self.annotation_put_fbs(fbs) - self.assertEqual(res, json.dumps({"status": "OK"})) - - # check read_labels - labels = self.annotations.read_labels(None) - fbsAll = self.data.annotation_to_fbs_matrix("obs", None, labels) - schema = schema_get_helper(self.data) - annotations = decode_fbs.decode_matrix_FBS(fbsAll) - self.assertEqual(annotations["n_rows"], n_rows) - all_col_schema = {c["name"]: c for c in schema["annotations"]["obs"]["columns"]} - self.assertEqual( - all_col_schema["cat_F_PASS"], - {"name": "cat_F_PASS", "type": "int32", "writable": True}, - ) diff --git a/backend/test/test_czi_hosted/unit/common/utils/__init__.py b/backend/test/test_czi_hosted/unit/common/utils/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/common/utils/test_cxg_generation_utils.py b/backend/test/test_czi_hosted/unit/common/utils/test_cxg_generation_utils.py deleted file mode 100644 index 5437b23b..00000000 --- a/backend/test/test_czi_hosted/unit/common/utils/test_cxg_generation_utils.py +++ /dev/null @@ -1,158 +0,0 @@ -import json -import unittest -from os import path, mkdir -from shutil import rmtree -from uuid import uuid4 - -import numpy as np -import tiledb -from pandas import Series, DataFrame - -from backend.czi_hosted.common.utils.cxg_generation_utils import ( - convert_dictionary_to_cxg_group, - convert_dataframe_to_cxg_array, - convert_ndarray_to_cxg_dense_array, - convert_matrix_to_cxg_array, -) -from backend.test import FIXTURES_ROOT - - -class TestCxgGenerationUtils(unittest.TestCase): - def setUp(self): - self.testing_cxg_temp_directory = f"{FIXTURES_ROOT}/{uuid4()}" - mkdir(self.testing_cxg_temp_directory) - - def tearDown(self): - if path.isdir(self.testing_cxg_temp_directory): - rmtree(self.testing_cxg_temp_directory) - - def test__convert_dictionary_to_cxg_group__writes_successfully(self): - random_dictionary = {"cookies": "chocolate_chip", "brownies": "chocolate", "cake": "double chocolate"} - dictionary_name = "favorite_desserts" - expected_array_directory = f"{self.testing_cxg_temp_directory}/{dictionary_name}" - - convert_dictionary_to_cxg_group( - self.testing_cxg_temp_directory, random_dictionary, group_metadata_name=dictionary_name - ) - - array = tiledb.open(expected_array_directory) - actual_stored_metadata = dict(array.meta.items()) - - self.assertTrue(path.isdir(expected_array_directory)) - self.assertTrue(isinstance(array, tiledb.DenseArray)) - self.assertEqual(random_dictionary, actual_stored_metadata) - - def test__convert_dataframe_to_cxg_array__writes_successfully(self): - random_int_category = Series(data=[3, 1, 2, 4], dtype=np.int64) - random_bool_category = Series(data=[True, True, False, True], dtype=np.bool_) - random_dataframe_name = f"random_dataframe_{uuid4()}" - random_dataframe = DataFrame(data={"int_category": random_int_category, "bool_category": random_bool_category}) - - convert_dataframe_to_cxg_array( - self.testing_cxg_temp_directory, random_dataframe_name, random_dataframe, "int_category", tiledb.Ctx() - ) - - expected_array_directory = f"{self.testing_cxg_temp_directory}/{random_dataframe_name}" - expected_array_metadata = { - "cxg_schema": json.dumps( - {"int_category": {"type": "int32"}, "bool_category": {"type": "boolean"}, "index": "int_category"} - ) - } - - actual_stored_dataframe_array = tiledb.open(expected_array_directory) - actual_stored_dataframe_metadata = dict(actual_stored_dataframe_array.meta.items()) - - self.assertTrue(path.isdir(expected_array_directory)) - self.assertTrue(isinstance(actual_stored_dataframe_array, tiledb.DenseArray)) - self.assertDictEqual(expected_array_metadata, actual_stored_dataframe_metadata) - self.assertTrue((actual_stored_dataframe_array[0:4]["int_category"] == random_int_category.to_numpy()).all()) - self.assertTrue((actual_stored_dataframe_array[0:4]["bool_category"] == random_bool_category.to_numpy()).all()) - - def test__convert_ndarray_to_cxg_dense_array__writes_successfully(self): - ndarray = np.random.rand(3, 2) - ndarray_name = f"{self.testing_cxg_temp_directory}/awesome_ndarray_{uuid4()}" - - convert_ndarray_to_cxg_dense_array(ndarray_name, ndarray, tiledb.Ctx()) - - actual_stored_array = tiledb.open(ndarray_name) - - self.assertTrue(path.isdir(ndarray_name)) - self.assertTrue(isinstance(actual_stored_array, tiledb.DenseArray)) - self.assertTrue((actual_stored_array[:, :] == ndarray).all()) - - def test__convert_matrix_to_cxg_array__dense_array_writes_successfully(self): - matrix = np.float32(np.random.rand(3, 2)) - matrix_name = f"{self.testing_cxg_temp_directory}/awesome_matrix_{uuid4()}" - - convert_matrix_to_cxg_array(matrix_name, matrix, False, tiledb.Ctx()) - - actual_stored_array = tiledb.open(matrix_name) - - self.assertTrue(path.isdir(matrix_name)) - self.assertTrue(isinstance(actual_stored_array, tiledb.DenseArray)) - self.assertTrue((actual_stored_array[:, :] == matrix).all()) - - def test__convert_matrix_to_cxg_array__sparse_array_only_store_nonzeros_empty_array(self): - matrix = np.zeros([3, 2]) - matrix_name = f"{self.testing_cxg_temp_directory}/awesome_zero_matrix_{uuid4()}" - - convert_matrix_to_cxg_array(matrix_name, matrix, True, tiledb.Ctx()) - - actual_stored_array = tiledb.open(matrix_name) - - self.assertTrue(path.isdir(matrix_name)) - self.assertTrue(isinstance(actual_stored_array, tiledb.SparseArray)) - self.assertTrue(actual_stored_array[:, :][""].size == 0) - - def test__convert_matrix_to_cxg_array__sparse_array_only_store_nonzeros(self): - matrix = np.zeros([3, 3]) - matrix[0, 0] = 1 - matrix[1, 1] = 1 - matrix[2, 2] = 2 - matrix_name = f"{self.testing_cxg_temp_directory}/awesome_sparse_matrix_{uuid4()}" - - convert_matrix_to_cxg_array(matrix_name, matrix, True, tiledb.Ctx()) - - actual_stored_array = tiledb.open(matrix_name) - - self.assertTrue(path.isdir(matrix_name)) - self.assertTrue(isinstance(actual_stored_array, tiledb.SparseArray)) - self.assertTrue(actual_stored_array[0, 0][""] == 1) - self.assertTrue(actual_stored_array[1, 1][""] == 1) - self.assertTrue(actual_stored_array[2, 2][""] == 2) - self.assertTrue(actual_stored_array[:, :][""].size == 3) - - def test__convert_matrix_to_cxg_array__sparse_array_with_column_encoding_empty_array(self): - matrix_name = f"{self.testing_cxg_temp_directory}/awesome_column_shift_matrix_{uuid4()}" - matrix = np.ones((3, 2)) - # The column shift will be equal to the matrix since subtracting the column shift from the matrix will create - # a matrix of zeros which is sparse. - column_shift = np.ones((3, 2)) - - convert_matrix_to_cxg_array( - matrix_name, matrix, True, tiledb.Ctx(), column_shift_for_sparse_encoding=column_shift - ) - - actual_stored_array = tiledb.open(matrix_name) - - self.assertTrue(path.isdir(matrix_name)) - self.assertTrue(isinstance(actual_stored_array, tiledb.SparseArray)) - self.assertTrue(actual_stored_array[:, :][""].size == 0) - - def test__convert_matrix_to_cxg_array__sparse_array_with_column_encoding_partial_array(self): - matrix_name = f"{self.testing_cxg_temp_directory}/awesome_column_shift_matrix_{uuid4()}" - matrix = np.ones((2, 2)) - # Only column shift the first column of ones. - column_shift = np.array([[1, 0], [1, 0]]) - - convert_matrix_to_cxg_array( - matrix_name, matrix, True, tiledb.Ctx(), column_shift_for_sparse_encoding=column_shift - ) - - actual_stored_array = tiledb.open(matrix_name) - - self.assertTrue(path.isdir(matrix_name)) - self.assertTrue(isinstance(actual_stored_array, tiledb.SparseArray)) - self.assertTrue(actual_stored_array[0, 1][""] == 1) - self.assertTrue(actual_stored_array[1, 1][""] == 1) - self.assertTrue(actual_stored_array[:, :][""].size == 2) diff --git a/backend/test/test_czi_hosted/unit/common/utils/test_matrix_utils.py b/backend/test/test_czi_hosted/unit/common/utils/test_matrix_utils.py deleted file mode 100644 index c7b3cc19..00000000 --- a/backend/test/test_czi_hosted/unit/common/utils/test_matrix_utils.py +++ /dev/null @@ -1,66 +0,0 @@ -import unittest - -import numpy as np - -from backend.czi_hosted.common.utils.matrix_utils import is_matrix_sparse, get_column_shift_encode_for_matrix - - -class TestMatrixUtils(unittest.TestCase): - def test__is_matrix_sparse__zero_and_one_hundred_percent_threshold(self): - matrix = np.array([1, 2, 3]) - - self.assertFalse(is_matrix_sparse(matrix, 0)) - self.assertTrue(is_matrix_sparse(matrix, 100)) - - def test__is_matrix_sparse__partially_populated_sparse_matrix_returns_true(self): - matrix = np.zeros([3, 4]) - matrix[2][3] = 1.0 - matrix[1][1] = 2.2 - - self.assertTrue(is_matrix_sparse(matrix, 50)) - - def test__is_matrix_sparse__partially_populated_dense_matrix_returns_false(self): - matrix = np.zeros([2, 2]) - matrix[0][0] = 1.0 - matrix[0][1] = 2.2 - matrix[1][1] = 3.7 - - self.assertFalse(is_matrix_sparse(matrix, 50)) - - def test__is_matrix_sparse__giant_matrix_returns_false_early(self): - matrix = np.ones([20000, 20]) - - with self.assertLogs(level="INFO") as logger: - self.assertFalse(is_matrix_sparse(matrix, 1)) - - # Because the function returns early a log will output the _estimate_ instead of the _exact_ percentage of - # non-zero elements in the matrix. - self.assertIn("Percentage of non-zero elements (estimate)", logger.output[0]) - - def test__is_matrix_sparse_with_column_shift_encoding__regular_sparse_returns_true(self): - matrix = np.zeros([2, 2]) - matrix[0][0] = 1.0 - - self.assertIsNotNone(get_column_shift_encode_for_matrix(matrix, 50)) - - def test__is_matrix_sparse_with_column_shift_encoding__column_shift_returns_same_value(self): - matrix = np.ones([2, 2]) - expected_column_shift = [1, 1] - - actual_column_shift = get_column_shift_encode_for_matrix(matrix, 50) - self.assertTrue((expected_column_shift == actual_column_shift).all()) - - def test__is_matrix_sparse_with_column_shift_encoding__impossible_column_shift_returns_none(self): - matrix = np.array([[1, 2], [3, 4]]) - - self.assertIsNone(get_column_shift_encode_for_matrix(matrix, 50)) - - def test__is_matrix_sparse_with_column_shift_encoding__giant_matrix_returns_false_early(self): - matrix = np.random.rand(20000, 20) - - with self.assertLogs(level="INFO") as logger: - self.assertFalse(is_matrix_sparse(matrix, 1)) - - # Because the function returns early a log will output the _estimate_ instead of the _exact_ percentage of - # non-zero elements in the matrix. - self.assertIn("Percentage of non-zero elements (estimate)", logger.output[0]) diff --git a/backend/test/test_czi_hosted/unit/common/utils/test_sanitization_utils.py b/backend/test/test_czi_hosted/unit/common/utils/test_sanitization_utils.py deleted file mode 100644 index 9ae3cede..00000000 --- a/backend/test/test_czi_hosted/unit/common/utils/test_sanitization_utils.py +++ /dev/null @@ -1,55 +0,0 @@ -import unittest - -from backend.czi_hosted.common.utils.sanitization_utils import sanitize_values_in_list, sanitize_keys_in_dictionary - - -class TestSanitizationUtils(unittest.TestCase): - def test__sanitize_values_in_list__not_strings_raises_exception(self): - keys_to_sanitize = [1, 2, 3] - - with self.assertRaises(Exception) as exception_context: - sanitize_values_in_list(keys_to_sanitize) - - self.assertIn("must contain all strings", str(exception_context.exception)) - - def test__sanitize_values_in_list__not_all_strings_raises_exception(self): - keys_to_sanitize = ["1", "2", 3] - - with self.assertRaises(Exception) as exception_context: - sanitize_values_in_list(keys_to_sanitize) - - self.assertIn("must contain all strings", str(exception_context.exception)) - - def test__sanitize_values_in_list__replace_non_ascii_character_with_underscore(self): - keys_to_sanitize = ["abc.", "~abc", "a~b/c"] - expected_sanitized_keys_dict = dict(zip(keys_to_sanitize, ["abc_", "_abc", "a_b_c"])) - - actual_sanitized_keys_dict = sanitize_values_in_list(keys_to_sanitize) - - self.assertEqual(expected_sanitized_keys_dict, actual_sanitized_keys_dict) - - def test__sanitize_keys_in_dictionary__replace_non_ascii_character_with_underscore(self): - dictionary_to_sanitize = {"abc.": 3, "~abc": 4, "a~b/c": 5} - expected_sanitized_dict = {"abc_": 3, "_abc": 4, "a_b_c": 5} - - actual_sanitized_dict = dictionary_to_sanitize - sanitize_keys_in_dictionary(actual_sanitized_dict) - - self.assertEqual(expected_sanitized_dict, actual_sanitized_dict) - - def test__sanitize_keys_in_dictionary__non_string_key_raises_exception(self): - dictionary_to_sanitize = {4: 3, "~abc": 4, "a~b/c": 5} - - with self.assertRaises(Exception) as exception_context: - sanitize_keys_in_dictionary(dictionary_to_sanitize) - - self.assertIn("must contain all strings", str(exception_context.exception)) - - def test__sanitize_keys_in_dictionary__replace_only_some_keys(self): - dictionary_to_sanitize = {"abc": 3, "~abc": 4, "a~b/c": 5} - expected_sanitized_dict = {"abc": 3, "_abc": 4, "a_b_c": 5} - - actual_sanitized_dict = dictionary_to_sanitize - sanitize_keys_in_dictionary(actual_sanitized_dict) - - self.assertEqual(expected_sanitized_dict, actual_sanitized_dict) diff --git a/backend/test/test_czi_hosted/unit/common/utils/test_utils.py b/backend/test/test_czi_hosted/unit/common/utils/test_utils.py deleted file mode 100644 index fd1f9442..00000000 --- a/backend/test/test_czi_hosted/unit/common/utils/test_utils.py +++ /dev/null @@ -1,34 +0,0 @@ -import os -import shutil -import unittest - -from backend.common.utils.utils import import_plugins -from backend.test import PROJECT_ROOT, random_string - - -class TestPlugins(unittest.TestCase): - """ Test plugin import functionality """ - - plugins_dir = f"{PROJECT_ROOT}/backend/test/test_czi_hosted/unit/plugins" - test_plugin_path = f"{plugins_dir}/foo.py" - secret = random_string(8) - - @classmethod - def setUpClass(cls) -> None: - if not os.path.isdir(cls.plugins_dir): - os.mkdir(cls.plugins_dir) - with open(cls.test_plugin_path, "w") as fh: - fh.write(f'SECRET = "{cls.secret}"\n') - - @classmethod - def tearDownClass(cls) -> None: - if os.path.isdir(cls.plugins_dir): - shutil.rmtree(cls.plugins_dir) - - def test_import_plugins(self): - self.assertTrue(os.path.isfile(self.test_plugin_path)) - loaded_modules = import_plugins("backend.test.test_czi_hosted.unit.plugins") - # test that import plugins found the file - self.assertEqual(["backend.test.test_czi_hosted.unit.plugins.foo"], [ele.__name__ for ele in loaded_modules]) - # test that the module was properly executed - self.assertEqual(self.secret, loaded_modules[0].SECRET) diff --git a/backend/test/test_czi_hosted/unit/compute/__init__.py b/backend/test/test_czi_hosted/unit/compute/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/compute/test_diffexp_cxg.py b/backend/test/test_czi_hosted/unit/compute/test_diffexp_cxg.py deleted file mode 100644 index 14ddf400..00000000 --- a/backend/test/test_czi_hosted/unit/compute/test_diffexp_cxg.py +++ /dev/null @@ -1,183 +0,0 @@ -import os -import tempfile -import unittest - -import numpy as np - -from backend.czi_hosted.compute import diffexp_cxg -from backend.common.compute import diffexp_generic -from backend.czi_hosted.compute.diffexp_cxg import diffexp_ttest -from backend.czi_hosted.converters.h5ad_data_file import H5ADDataFile -from backend.common.fbs.matrix import encode_matrix_fbs, decode_matrix_fbs -from backend.czi_hosted.data_common.matrix_loader import MatrixDataLoader -from backend.test.test_czi_hosted.performance.create_test_matrix import create_test_h5ad -from backend.test.test_czi_hosted.unit import app_config -from backend.test import PROJECT_ROOT, FIXTURES_ROOT - - -class DiffExpTest(unittest.TestCase): - """Tests the diffexp returns the expected results for one test case, using different - adaptor types and different algorithms.""" - - def load_dataset(self, path, extra_server_config={}, extra_dataset_config={}): - extra_dataset_config["X_approximate_distribution"] = "normal" # hardwired for now - config = app_config(path, extra_server_config=extra_server_config, extra_dataset_config=extra_dataset_config) - loader = MatrixDataLoader(path) - adaptor = loader.open(config) - return adaptor - - def get_mask(self, adaptor, start, stride): - """Simple function to return a mask or rows""" - rows = adaptor.get_shape()[0] - sel = list(range(start, rows, stride)) - mask = np.zeros(rows, dtype=bool) - mask[sel] = True - return mask - - def compare_diffexp_results(self, results, expects): - self.assertEqual(len(results), len(expects)) - for result, expect in zip(results, expects): - self.assertEqual(result[0], expect[0]) - self.assertTrue(np.isclose(result[1], expect[1], 1e-6, 1e-4)) - self.assertTrue(np.isclose(result[2], expect[2], 1e-6, 1e-4)) - self.assertTrue(np.isclose(result[3], expect[3], 1e-6, 1e-4)) - - - def check_1_10_2_10(self, results): - """Checks the results for a specific set of rows selections""" - - positive_expects = [ - [1712, 0.24104056, 0.0051788902660723345, 1.0], - [1575, 0.2615018, 0.007830310753043345, 1.0], - [693, 0.23106655, 0.008715846769131548, 1.0], - [916, 0.2395215, 0.009080596532247588, 1.0], - [77, 0.22927025, 0.010070392939027756, 1.0], - [782, 0.20581803, 0.010161745218916036, 1.0], - [913, 0.23841085, 0.010782030711612685, 1.0], - [910, 0.21493295, 0.014596411069229197, 1.0], - [1727, 0.21911663, 0.015168372104237176, 1.0], - [1443, 0.19814226, 0.015337080567465522, 1.0], - ] - negative_expects = [ - [956, -0.29662406, 0.0008649321884808977, 1.0], - [1124, -0.2607333, 0.0011717216548271284, 1.0], - [1809, -0.24854594, 0.0019304405196777848, 1.0], - [1754, -0.24683577, 0.005691734062127954, 1.0], - [948, -0.18708363, 0.006622111055981219, 1.0], - [1810, -0.2172082, 0.007055917428377063, 1.0], - [779, -0.21150622, 0.007202934422407284, 1.0], - [576, -0.19008157, 0.008272092578813124, 1.0], - [538, -0.21803819, 0.01062259019889307, 1.0], - [436, -0.2100364, 0.01127515110543434, 1.0], - ] - - self.compare_diffexp_results(results['positive'], positive_expects) - self.compare_diffexp_results(results['negative'], negative_expects) - - def get_X_col(self, adaptor, cols): - varmask = np.zeros(adaptor.get_shape()[1], dtype=bool) - varmask[cols] = True - return adaptor.get_X_array(None, varmask) - - def test_anndata_default(self): - """Test an anndata adaptor with its default diffexp algorithm (diffexp_generic)""" - adaptor = self.load_dataset(f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad") - maskA = self.get_mask(adaptor, 1, 10) - maskB = self.get_mask(adaptor, 2, 10) - results = adaptor.compute_diffexp_ttest(maskA, maskB, 10) - self.check_1_10_2_10(results) - - def test_cxg_default(self): - """Test a cxg adaptor with its default diffexp algorithm (diffexp_cxg)""" - adaptor = self.load_dataset(f"{FIXTURES_ROOT}/pbmc3k.cxg") - maskA = self.get_mask(adaptor, 1, 10) - maskB = self.get_mask(adaptor, 2, 10) - - # run it through the adaptor - results = adaptor.compute_diffexp_ttest(maskA, maskB, 10) - self.check_1_10_2_10(results) - - # run it directly - - results = diffexp_ttest(adaptor, maskA, maskB, 10) - self.check_1_10_2_10(results) - - def test_cxg_generic(self): - """Test a cxg adaptor with the generic adaptor""" - adaptor = self.load_dataset(f"{FIXTURES_ROOT}/pbmc3k.cxg") - maskA = self.get_mask(adaptor, 1, 10) - maskB = self.get_mask(adaptor, 2, 10) - # run it directly - results = diffexp_generic.diffexp_ttest(adaptor, maskA, maskB, 10) - self.check_1_10_2_10(results) - - def test_cxg_sparse(self): - self.sparse_diffexp(False) - - def test_cxg_sparse_col_shift(self): - self.sparse_diffexp(True) - - def sparse_diffexp(self, apply_col_shift): - with tempfile.TemporaryDirectory() as dirname: - # create a sparse matrix - h5adfile_path = os.path.join(dirname, "sparse.h5ad") - create_test_h5ad(h5adfile_path, 2000, 2000, 10, apply_col_shift) - - h5ad_file_to_convert = H5ADDataFile(h5adfile_path, use_corpora_schema=False) - - sparsename = os.path.join(dirname, "sparse.cxg") - h5ad_file_to_convert.to_cxg(sparsename, 11, True) - - adaptor_anndata = self.load_dataset(h5adfile_path, extra_dataset_config=dict(embeddings__names=[])) - - adaptor_sparse = self.load_dataset(sparsename) - assert adaptor_sparse.open_array("X").schema.sparse - assert adaptor_sparse.has_array("X_col_shift") == apply_col_shift - - densename = os.path.join(dirname, "dense.cxg") - h5ad_file_to_convert.to_cxg(densename, True, 0) - adaptor_dense = self.load_dataset(densename) - assert not adaptor_dense.open_array("X").schema.sparse - assert not adaptor_dense.has_array("X_col_shift") - - maskA = self.get_mask(adaptor_anndata, 1, 10) - maskB = self.get_mask(adaptor_anndata, 2, 10) - - diffexp_results_anndata = diffexp_generic.diffexp_ttest(adaptor_anndata, maskA, maskB, 10) - diffexp_results_sparse = diffexp_cxg.diffexp_ttest(adaptor_sparse, maskA, maskB, 10) - diffexp_results_dense = diffexp_cxg.diffexp_ttest(adaptor_dense, maskA, maskB, 10) - - self.compare_diffexp_results(diffexp_results_anndata['positive'], diffexp_results_sparse['positive']) - self.compare_diffexp_results(diffexp_results_anndata['negative'], diffexp_results_sparse['negative']) - - self.compare_diffexp_results(diffexp_results_anndata['positive'], diffexp_results_dense['positive']) - self.compare_diffexp_results(diffexp_results_anndata['negative'], diffexp_results_dense['negative']) - - topcols_pos = np.array([x[0] for x in diffexp_results_anndata['positive']]) - topcols_neg = np.array([x[0] for x in diffexp_results_anndata['negative']]) - topcols = np.concatenate((topcols_pos, topcols_neg)) - - cols_anndata = self.get_X_col(adaptor_anndata, topcols) - cols_sparse = self.get_X_col(adaptor_sparse, topcols) - cols_dense = self.get_X_col(adaptor_dense, topcols) - - assert cols_anndata.shape[0] == adaptor_sparse.get_shape()[0] - assert cols_anndata.shape[1] == len(diffexp_results_anndata['positive']) + len(diffexp_results_anndata['negative']) - - def convert(mat, cols): - return decode_matrix_fbs(encode_matrix_fbs(mat, col_idx=cols)).to_numpy() - - cols_anndata = convert(cols_anndata, topcols) - cols_sparse = convert(cols_sparse, topcols) - cols_dense = convert(cols_dense, topcols) - - x = adaptor_sparse.get_X_array() - assert x.shape == adaptor_sparse.get_shape() - - for row in range(cols_anndata.shape[0]): - for col in range(cols_anndata.shape[1]): - vanndata = cols_anndata[row][col] - vsparse = cols_sparse[row][col] - vdense = cols_dense[row][col] - self.assertTrue(np.isclose(vanndata, vsparse, 1e-6, 1e-6)) - self.assertTrue(np.isclose(vanndata, vdense, 1e-6, 1e-6)) diff --git a/backend/test/test_czi_hosted/unit/converters/__init__.py b/backend/test/test_czi_hosted/unit/converters/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/converters/schema/__init__.py b/backend/test/test_czi_hosted/unit/converters/schema/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/converters/schema/test_gene_symbol.py b/backend/test/test_czi_hosted/unit/converters/schema/test_gene_symbol.py deleted file mode 100644 index a0a825be..00000000 --- a/backend/test/test_czi_hosted/unit/converters/schema/test_gene_symbol.py +++ /dev/null @@ -1,61 +0,0 @@ -import os -import unittest - -import pandas as pd - -from backend.czi_hosted.converters.schema import gene_symbol -from backend.test import FIXTURES_ROOT - - -class TestHGNCSymbolChecker(unittest.TestCase): - - def setUp(self): - self.test_hgnc_path = os.path.join(FIXTURES_ROOT, "hgnc_example.txt.gz") - self.hgnc_checker = gene_symbol.HGNCSymbolChecker.from_hgnc_records(self.test_hgnc_path) - - def test_symbol_upgrade(self): - self.assertEqual(self.hgnc_checker.upgrade_symbol("SEPT1"), "SEPTIN1") - self.assertEqual(self.hgnc_checker.upgrade_symbol("ADRB2R"), "ADRB2") - self.assertEqual(self.hgnc_checker.upgrade_symbol("BAR"), "ADRB2") - self.assertEqual(self.hgnc_checker.upgrade_symbol("sept1"), "SEPTIN1") - self.assertEqual(self.hgnc_checker.upgrade_symbol("AdRb2R"), "ADRB2") - self.assertEqual(self.hgnc_checker.upgrade_symbol("bar"), "ADRB2") - - # Strip off seurat endings when appropriate - self.assertEqual(self.hgnc_checker.upgrade_symbol("SEPT1.1"), "SEPTIN1") - self.assertEqual(self.hgnc_checker.upgrade_symbol("ADRB2-1"), "ADRB2") - - # DIFF6 is ambiguous so don't upgrade it - self.assertEqual(self.hgnc_checker.upgrade_symbol("DIFF6"), "DIFF6") - self.assertEqual(self.hgnc_checker.upgrade_symbol("diff6"), "diff6") - - # ARG1 is approved - self.assertEqual(self.hgnc_checker.upgrade_symbol("ARG1"), "ARG1") - self.assertEqual(self.hgnc_checker.upgrade_symbol("arg1"), "ARG1") - - # HAP1 is both approved and withdrawn - self.assertEqual(self.hgnc_checker.upgrade_symbol("HAP1"), "HAP1") - self.assertEqual(self.hgnc_checker.upgrade_symbol("hap1"), "HAP1") - - # Leave unknown symbols alone - self.assertEqual(self.hgnc_checker.upgrade_symbol("NOTASYMBOL"), "NOTASYMBOL") - self.assertEqual(self.hgnc_checker.upgrade_symbol("notasymbol"), "notasymbol") - - # Upgrade HGNC ids unless you can't find it - self.assertEqual(self.hgnc_checker.upgrade_symbol("HGNC:286"), "ADRB2") - self.assertEqual(self.hgnc_checker.upgrade_symbol("HGNC:4812"), "HAP1") - self.assertEqual(self.hgnc_checker.upgrade_symbol("HGNC:123456"), "HGNC:123456") - - def test_check_symbol(self): - self.assertEqual(self.hgnc_checker.check_symbol("SEPT1"), gene_symbol.SymbolStatus.UPGRADABLE) - self.assertEqual(self.hgnc_checker.check_symbol("DIFF6"), gene_symbol.SymbolStatus.AMBIGUOUS) - self.assertEqual(self.hgnc_checker.check_symbol("NOTASYMBOL"), gene_symbol.SymbolStatus.UNKNOWN) - - # HAP1 is one of the approved and withdrawn symbols - self.assertEqual(self.hgnc_checker.check_symbol("HAP1"), gene_symbol.SymbolStatus.APPROVED) - - def test_upgrade_index(self): - index = pd.Index(["SEPT1", "DIFF6", "NOTASYMBOL", "bar", "SEPTIN1"]) - var_df = pd.DataFrame([[0] * len(index)], index=index) - upgraded_index = gene_symbol.get_upgraded_var_index(var_df, hgnc_path=self.test_hgnc_path) - self.assertEqual(upgraded_index.tolist(), ["SEPTIN1", "DIFF6", "NOTASYMBOL", "ADRB2", "SEPTIN1"]) diff --git a/backend/test/test_czi_hosted/unit/converters/schema/test_ontology.py b/backend/test/test_czi_hosted/unit/converters/schema/test_ontology.py deleted file mode 100644 index 6cda5b12..00000000 --- a/backend/test/test_czi_hosted/unit/converters/schema/test_ontology.py +++ /dev/null @@ -1,128 +0,0 @@ -import json - -import unittest.mock - -from backend.czi_hosted.converters.schema import ontology - - -class TestOntologyParsing(unittest.TestCase): - def setUp(self): - - self.curies = ["UBERON:0002048", "HsapDv:0000174", "NCBITaxon:9606", "EFO:0008995"] - - self.names = ["UBERON", "HsapDv", "NCBITaxon", "EFO"] - - self.values = ["0002048", "0000174", "9606", "0008995"] - - self.iris = [ - "http://purl.obolibrary.org/obo/UBERON_0002048", - "http://purl.obolibrary.org/obo/HsapDv_0000174", - "http://purl.obolibrary.org/obo/NCBITaxon_9606", - "http://www.ebi.ac.uk/efo/EFO_0008995", - ] - - URL_ROOT = "http://www.ebi.ac.uk/ols/api/ontologies/" - self.urls = [ - URL_ROOT + "UBERON/terms/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FUBERON_0002048", - URL_ROOT + "HsapDv/terms/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FHsapDv_0000174", - URL_ROOT + "NCBITaxon/terms/http%253A%252F%252Fpurl.obolibrary.org%252Fobo%252FNCBITaxon_9606", - URL_ROOT + "EFO/terms/http%253A%252F%252Fwww.ebi.ac.uk%252Fefo%252FEFO_0008995", - ] - - self.responses = { - "UBERON:0002048": { - "iri": "http://purl.obolibrary.org/obo/UBERON_0002048", - "description": ["Respiration organ that develops as an outpocketing of the esophagus."], - "label": "lung", - }, - "HsapDv:0000174": { - "iri": "http://purl.obolibrary.org/obo/HsapDv_0000174", - "description": ["Infant stage that refers to an infant who is over 1 and under 2 months old."], - "label": "1-month-old human stage", - }, - "NCBITaxon:9606": { - "iri": "http://purl.obolibrary.org/obo/NCBITaxon_9606", - "description": None, - "label": "Homo sapiens", - }, - "EFO:0008995": { - "iri": "http://www.ebi.ac.uk/efo/EFO_0008995", - "description": [ - ( - '10X is a "synthetic long-read" technology and works by capturing a barcoded oligo-coated ' - "gel-bead and 0.3x genome copies into a single emulsion droplet, processing the equivalent " - "of 1 million pipetting steps. Successive versions of the 10x chemistry use different " - "barcode locations to improve the sequencing yield and quality of 10x experiments." - ) - ], - "label": "10X sequencing", - }, - } - - def test_ontololgy_name(self): - for curie, expected_name in zip(self.curies, self.names): - self.assertEqual(ontology._ontology_name(curie), expected_name) - - def test_ontololgy_value(self): - for curie, expected_value in zip(self.curies, self.values): - self.assertEqual(ontology._ontology_value(curie), expected_value) - - def test_iri(self): - for curie, expected_iri in zip(self.curies, self.iris): - self.assertEqual(ontology._iri(curie), expected_iri) - - def test_ontology_info_url(self): - for curie, expected_url in zip(self.curies, self.urls): - self.assertEqual(ontology._ontology_info_url(curie), expected_url) - - def test_empty_ontology_info_url(self): - self.assertEqual(ontology._ontology_info_url(""), "") - - -class TestOntologyLookup(unittest.TestCase): - def setUp(self): - self.responses = { - "UBERON:0002048": { - "iri": "http://purl.obolibrary.org/obo/UBERON_0002048", - "description": ["Respiration organ that develops as an outpocketing of the esophagus."], - "label": "lung", - }, - "HsapDv:0000174": { - "iri": "http://purl.obolibrary.org/obo/HsapDv_0000174", - "description": ["Infant stage that refers to an infant who is over 1 and under 2 months old."], - "label": "1-month-old human stage", - }, - "NCBITaxon:9606": { - "iri": "http://purl.obolibrary.org/obo/NCBITaxon_9606", - "description": None, - "label": "Homo sapiens", - }, - "EFO:0008995": { - "iri": "http://www.ebi.ac.uk/efo/EFO_0008995", - "description": [ - ('10X is a "synthetic long-read" technology and works by capturing a barcoded oligo-coated ' - 'gel-bead and 0.3x genome copies into a single emulsion droplet, processing the equivalent ' - 'of 1 million pipetting steps. Successive versions of the 10x chemistry use different barcode ' - 'locations to improve the sequencing yield and quality of 10x experiments.') - ], - "label": "10X sequencing", - }, - } - - self.labels = { - "UBERON:0002048": "lung", - "HsapDv:0000174": "1-month-old human stage", - "NCBITaxon:9606": "Homo sapiens", - "EFO:0008995": "10X sequencing", - } - - @unittest.mock.patch("requests.get") - def test_lookup_label(self, mock_get): - - for curie, response in self.responses.items(): - mock_get.return_value.content = json.dumps(response) - mock_get.return_value.json.return_value = response - mock_get.return_value.status_code = 200 - - label = ontology.get_ontology_label(curie) - self.assertEqual(label, self.labels[curie]) diff --git a/backend/test/test_czi_hosted/unit/converters/schema/test_remix.py b/backend/test/test_czi_hosted/unit/converters/schema/test_remix.py deleted file mode 100644 index 4b4e37a4..00000000 --- a/backend/test/test_czi_hosted/unit/converters/schema/test_remix.py +++ /dev/null @@ -1,257 +0,0 @@ -import json -import os -import unittest -import unittest.mock - -import anndata -import numpy -import pandas as pd -import scanpy as sc - -from backend.czi_hosted.converters.schema import remix - -from backend.test import PROJECT_ROOT, FIXTURES_ROOT - - -class TestApplySchema(unittest.TestCase): - - def setUp(self): - self.source_h5ad_path = f"{FIXTURES_ROOT}/pbmc3k-CSC-gz.h5ad" - self.output_h5ad_path = f"{FIXTURES_ROOT}/test_remix.h5ad" - self.config_path = f"{FIXTURES_ROOT}/test_config.yaml" - self.bad_config_path = f"{FIXTURES_ROOT}/test_bad_config.yaml" - - def tearDown(self): - try: - os.remove(self.output_h5ad_path) - except OSError: - pass - - @unittest.mock.patch("backend.czi_hosted.converters.schema.ontology.get_ontology_label") - def test_apply_schema(self, mock_get_ontology_label): - mock_get_ontology_label.return_value = "test label" - remix.apply_schema(self.source_h5ad_path, self.config_path, self.output_h5ad_path) - new_adata = sc.read_h5ad(self.output_h5ad_path) - - self.assertIn("cell_type", new_adata.obs.columns) - self.assertListEqual(["test label"], new_adata.obs["cell_type"].unique().tolist()) - self.assertListEqual( - ["CL:00001", "CL:00002", "CL:00003", "CL:00004", "CL:00005", "CL:00006", "CL:00007", "CL:00008"], - sorted(new_adata.obs["cell_type_ontology_term_id"].unique().tolist()) - ) - - self.assertIn("version", new_adata.uns_keys()) - - @unittest.mock.patch("backend.czi_hosted.converters.schema.ontology.get_ontology_label") - def test_apply_bad_schema(self, mock_get_ontology_label): - mock_get_ontology_label.return_value = "test label" - remix.apply_schema(self.source_h5ad_path, self.bad_config_path, self.output_h5ad_path) - new_adata = sc.read_h5ad(self.output_h5ad_path) - - # Should refuse to write the version - self.assertNotIn("version", new_adata.uns_keys()) - -class TestFieldParsing(unittest.TestCase): - - def test_is_curie(self): - self.assertTrue(remix.is_curie("EFO:00001")) - self.assertTrue(remix.is_curie("UBERON:123456")) - self.assertTrue(remix.is_curie("HsapDv:0001")) - self.assertFalse(remix.is_curie("UBERON")) - self.assertFalse(remix.is_curie("UBERON:")) - self.assertFalse(remix.is_curie("123456")) - - def test_is_ontology_field(self): - self.assertTrue(remix.is_ontology_field("tissue_ontology_term_id")) - self.assertTrue(remix.is_ontology_field("cell_type_ontology_term_id")) - self.assertFalse(remix.is_ontology_field("cell_ontology")) - self.assertFalse(remix.is_ontology_field("method")) - - def test_get_label_field_name(self): - self.assertEqual("tissue", remix.get_label_field_name("tissue_ontology_term_id")) - self.assertEqual("cell_type", remix.get_label_field_name("cell_type_ontology_term_id")) - - def test_split_suffix(self): - self.assertEqual(("UBERON:1234", " (organoid)"), remix.split_suffix("UBERON:1234 (organoid)")) - self.assertEqual(("UBERON:1234", " (cell culture)"), remix.split_suffix("UBERON:1234 (cell culture)")) - self.assertEqual(("UBERON:1234", ""), remix.split_suffix("UBERON:1234")) - self.assertEqual(("UBERON:1234 (something)", ""), remix.split_suffix("UBERON:1234 (something)")) - - @unittest.mock.patch("backend.czi_hosted.converters.schema.ontology.get_ontology_label") - def test_get_curie_and_label(self, mock_get_ontology_label): - mock_get_ontology_label.return_value = "test label" - self.assertEqual( - remix.get_curie_and_label("UBERON:1234"), - ("UBERON:1234", "test label") - ) - self.assertEqual( - remix.get_curie_and_label("UBERON:1234 (cell culture)"), - ("UBERON:1234 (cell culture)", "test label (cell culture)") - ) - self.assertEqual( - remix.get_curie_and_label("whatever"), - ("", "whatever") - ) - - -class TestManipulateAnndata(unittest.TestCase): - - def setUp(self): - - self.cell_count = 20 - self.gene_count = 200 - X = numpy.random.randint(0, 1000, (self.cell_count, self.gene_count)) - uns = {"organism": "monkey", "experiment": "monkey experiment"} - obs = pd.DataFrame( - index=[f"Cell{d}" for d in range(self.cell_count)], - columns=["tissue", "CellType"], - data=[["lung", "epithelial"]] * (self.cell_count // 2) + [["lung", "endothelial"]] * (self.cell_count // 2) - ) - var = pd.DataFrame(index=[f"SEPT{d}" for d in range(self.gene_count)]) - - self.adata = anndata.AnnData(X=X, obs=obs, var=var, uns=uns) - - def test_safe_add_field(self): - - remix.safe_add_field(self.adata.obs, "tissue", ["monkey lung"] * self.cell_count) - self.assertEqual(self.adata.obs["tissue_original"].tolist(), ["lung"] * self.cell_count) - self.assertEqual(self.adata.obs["tissue"].tolist(), ["monkey lung"] * self.cell_count) - - remix.safe_add_field(self.adata.uns, "contributors", [{"name": "contributor1"}, {"name": "contributor2"}]) - self.assertEqual( - self.adata.uns["contributors"], - json.dumps([{"name": "contributor1"}, {"name": "contributor2"}]) - ) - - @unittest.mock.patch("backend.czi_hosted.converters.schema.ontology.get_ontology_label") - def test_remix_uns(self, mock_get_ontology_label): - mock_get_ontology_label.return_value = "Pan troglodytes" - uns_config = { - "version": { - "corpora_schema_version": "1.0.0", - "corpora_encoding_version": "0.1.0" - }, - "organism_ontology_term_id": "NCBITaxon:9598", - "contributors": [ - { - "name": "scientist", - "email": "scientist@science.com" - } - ] - } - - remix.remix_uns(self.adata, uns_config) - - self.assertEqual( - sorted(self.adata.uns_keys()), - sorted(["organism_original", "organism", "organism_ontology_term_id", - "contributors", "version", "experiment"]) - ) - - self.assertEqual(self.adata.uns['organism'], "Pan troglodytes") - self.assertEqual(self.adata.uns['organism_original'], "monkey") - self.assertEqual(self.adata.uns['organism_ontology_term_id'], "NCBITaxon:9598") - self.assertEqual(self.adata.uns['contributors'], - json.dumps([{"name": "scientist", "email": "scientist@science.com"}])) - - @unittest.mock.patch("backend.czi_hosted.converters.schema.ontology.get_ontology_label") - def test_remix_obs(self, mock_get_ontology_label): - mock_get_ontology_label.return_value = "lung (in a monkey)" - obs_config = { - "tissue_ontology_term_id": { - "tissue": { - "lung": "UBERON:00000" - } - }, - "cell_color": { - "CellType": { - "epithelial": "fuschia", - "endothelial": "khaki" - } - }, - "sex": "male" - } - - remix.remix_obs(self.adata, obs_config) - self.assertEqual( - sorted(self.adata.obs_keys()), - sorted(["tissue", "tissue_ontology_term_id", "tissue_original", "CellType", "cell_color", "sex"]) - ) - - self.assertTrue(all(v == "lung" for v in self.adata.obs.tissue_original)) - self.assertTrue(all(v == "UBERON:00000" for v in self.adata.obs.tissue_ontology_term_id)) - self.assertTrue(all(v == "lung (in a monkey)" for v in self.adata.obs.tissue)) - self.assertTrue(all(v == "male" for v in self.adata.obs.sex)) - self.assertTrue(all(v in (("epithelial", "fuschia"), ("endothelial", "khaki")) - for v in zip(self.adata.obs.CellType, self.adata.obs.cell_color))) - - -class TestFixupGeneSymbols(unittest.TestCase): - - def setUp(self): - self.seurat_path = f"{PROJECT_ROOT}/czi_hosted/test/fixtures/schema_test_data/seurat_tutorial.h5ad" - self.seurat_merged_path = f"{PROJECT_ROOT}/czi_hosted/test/fixtures/schema_test_data/seurat_tutorial_merged.h5ad" - self.sctransform_path = f"{PROJECT_ROOT}/czi_hosted/test/fixtures/schema_test_data/sctransform.h5ad" - self.sctransform_merged_path = f"{PROJECT_ROOT}/czi_hosted/test/fixtures/schema_test_data/sctransform_merged.h5ad" - - # There's lots of MALAT1, but it doesn't collide with any other names, - # so it shouldn't change during merging. - self.stable_gene = "MALAT1" - - def test_fixup_gene_symbols_seurat(self): - - if not os.path.isfile(self.seurat_path): - return unittest.skip( - "Skipping gene symbol conversion tests because test h5ads are not present. To create them, " - "run czi_hosted/test/fixtures/schema_test_data/generate_test_data.sh" - ) - - original_adata = sc.read_h5ad(self.seurat_path) - merged_adata = sc.read_h5ad(self.seurat_merged_path) - - fixup_config = {"X": "log1p", "counts": "raw", "scale.data": "log1p"} - - fixed_adata = remix.fixup_gene_symbols(original_adata, fixup_config) - - self.assertEqual( - merged_adata.layers["counts"][:, merged_adata.var.index == self.stable_gene].sum(), - fixed_adata.raw.X[:, fixed_adata.var.index == self.stable_gene].sum() - ) - self.assertAlmostEqual( - merged_adata.X[:, merged_adata.var.index == self.stable_gene].sum(), - fixed_adata.X[:, fixed_adata.var.index == self.stable_gene].sum() - ) - - self.assertAlmostEqual( - merged_adata.layers["scale.data"][:, merged_adata.var.index == self.stable_gene].sum(), - fixed_adata.layers["scale.data"][:, fixed_adata.var.index == self.stable_gene].sum() - ) - - def test_fixup_gene_symbols_sctransform(self): - - if not os.path.isfile(self.sctransform_path): - return unittest.skip( - "Skipping gene symbol conversion tests because test h5ads are not present. To create them, " - "run czi_hosted/test/fixtures/schema_test_data/generate_test_data.sh" - ) - - original_adata = sc.read_h5ad(self.sctransform_path) - merged_adata = sc.read_h5ad(self.sctransform_merged_path) - - fixup_config = {"X": "log1p", "counts": "raw"} - - fixed_adata = remix.fixup_gene_symbols(original_adata, fixup_config) - - # sctransform does a bunch of stuff, including slightly modifying the - # raw counts. So we can't assert for exact equality the way we do with - # the vanilla seurat tutorial. But, the results should still be very - # close. - merged_raw_stable = merged_adata.layers["counts"][:, merged_adata.var.index == self.stable_gene].sum() - fixed_raw_stable = fixed_adata.raw.X[:, fixed_adata.var.index == self.stable_gene].sum() - self.assertLess(abs(merged_raw_stable - fixed_raw_stable), .001 * merged_raw_stable) - - self.assertAlmostEqual( - merged_adata.X[:, merged_adata.var.index == self.stable_gene].sum(), - fixed_adata.X[:, fixed_adata.var.index == self.stable_gene].sum(), - 0 - ) diff --git a/backend/test/test_czi_hosted/unit/converters/schema/test_validate.py b/backend/test/test_czi_hosted/unit/converters/schema/test_validate.py deleted file mode 100644 index 01978222..00000000 --- a/backend/test/test_czi_hosted/unit/converters/schema/test_validate.py +++ /dev/null @@ -1,434 +0,0 @@ -import json -import unittest - -import pandas as pd -import scanpy as sc - -from backend.czi_hosted.converters.schema import validate - -from backend.test import PROJECT_ROOT - - -class TestFieldValidation(unittest.TestCase): - - def test_validate_stringified_list_of_dicts(self): - - good = json.dumps([{"a": 1}, {2: "x", "z": "y"}]) - not_stringified = [{"a": 1}, {2: "x", "z": "y"}] - not_a_list = json.dumps({"bad": "dict"}) - not_json = "oh hey!" - - self.assertTrue(validate._validate_stringified_list_of_dicts(good)) - - self.assertFalse(validate._validate_stringified_list_of_dicts(not_stringified)) - self.assertFalse(validate._validate_stringified_list_of_dicts(not_a_list)) - self.assertFalse(validate._validate_stringified_list_of_dicts(not_json)) - - def test_validate_human_readable_string(self): - - good = "oh hey!" - curie = "EFO:0001" - ensg = "ENSG000001234" - enst = "ENST000005678" - - self.assertTrue(validate._validate_human_readable_string(good)) - - self.assertFalse(validate._validate_human_readable_string(curie)) - self.assertFalse(validate._validate_human_readable_string(ensg)) - self.assertFalse(validate._validate_human_readable_string(enst)) - - def test_validate_curie(self): - - self.assertTrue(validate._validate_curie("UBERON:00001", ["UBERON", "EFO"])) - self.assertTrue(validate._validate_curie("HsapDv:00002", ["HsapDv"])) - - self.assertFalse(validate._validate_curie("HsapDv:00002", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_curie("EFO:00002 (organoid)", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_curie("EFO:00002 extra", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_curie("UBERON:ABCD", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_curie("Uberon:00002", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_curie("UBERON:", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_curie("UBERON", ["UBERON", "EFO"])) - - def test_validate_suffixed_curie(self): - - self.assertTrue(validate._validate_suffixed_curie("EFO:00001", ["UBERON", "EFO"])) - self.assertTrue(validate._validate_suffixed_curie("UBERON:00001 (cell culture)", ["UBERON", "EFO"])) - - self.assertFalse(validate._validate_suffixed_curie("HsapDv:00002 (organoid)", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("HsapDv:00002(organoid)", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("HsapDv:00002", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("EFO:00002 extra", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("UBERON:ABCD", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("Uberon:00002", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("UBERON:", ["UBERON", "EFO"])) - self.assertFalse(validate._validate_suffixed_curie("UBERON", ["UBERON", "EFO"])) - - -class TestColumnValidation(unittest.TestCase): - - def test_validate_unique(self): - unique = pd.DataFrame([["abc", "def"], ["ghi", "jkl"], ["mnop", "qrs"]], - index=["X", "Y", "Z"], columns=["col1", "col2"]) - duped = pd.DataFrame([["abc", "def"], ["ghi", "qrs"], ["abc", "qrs"]], - index=["X", "Y", "X"], columns=["col1", "col2"]) - - schema_def = {"unique": True} - - errors = validate._validate_column(unique.index, "index", "unique_df", schema_def) - self.assertFalse(errors) - - errors = validate._validate_column(duped.index, "index", "duped_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("is not unique", errors[0]) - - errors = validate._validate_column(unique["col1"], "col1", "unique_df", schema_def) - self.assertFalse(errors) - - errors = validate._validate_column(duped["col1"], "col1", "duped_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("is not unique", errors[0]) - - schema_def = {"unique": False} - errors = validate._validate_column(duped["col1"], "col1", "duped_df", schema_def) - self.assertFalse(errors) - - def test_validate_nullable(self): - non_null = pd.DataFrame([["abc", "def"], ["ghi", "jkl"], ["mnop", "qrs"]], - index=["X", "Y", "Z"], columns=["col1", "col2"]) - has_null = pd.DataFrame([["abc", "", None], ["ghi", "jkl", 1], ["mnop", "qrs", 2]], - index=["X", "Y", "Z"], columns=["col1", "col2", "col3"]) - - schema_def = {"nullable": False} - errors = validate._validate_column(non_null["col1"], "col1", "nonnull_df", schema_def) - self.assertFalse(errors) - errors = validate._validate_column(has_null["col1"], "col1", "hasnull_df", schema_def) - self.assertFalse(errors) - - errors = validate._validate_column(has_null["col2"], "col2", "hasnull_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("contains empty values", errors[0]) - errors = validate._validate_column(has_null["col3"], "col3", "hasnull_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("contains empty values", errors[0]) - - schema_def = {"nullable": True} - errors = validate._validate_column(has_null["col2"], "col2", "hasnull_df", schema_def) - self.assertFalse(errors) - - def test_human_readable(self): - hr_df = pd.DataFrame( - [["for you, a human", "UBERON:12345", "UBERON:1234 (thundercat)"], - ["hope you're well", "bit of lungs", "brain"]], - index=["ENSG00001", "ENSG00002"], - columns=["good", "curie", "suffixed_curie"]) - - schema_def = {"type": "human-readable string"} - errors = validate._validate_column(hr_df["good"], "good", "hr", schema_def) - self.assertFalse(errors) - - errors = validate._validate_column(hr_df["curie"], "curie", "hr", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("non-human-readable", errors[0]) - - errors = validate._validate_column(hr_df["suffixed_curie"], "suffixed_curie", "hr", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("non-human-readable", errors[0]) - - errors = validate._validate_column(hr_df.index, "ensg", "hr", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("non-human-readable", errors[0]) - - def test_curie(self): - - curie_df = pd.DataFrame( - [["EFO:00001", "HsapDv:00001 (cell culture)", "EFO:", "MONDO:0001 cell culture"], - ["UBERON:00002", "HsapDv:00002 (organoid)", "EFO:12345", "MONDO:0002 (baba yaga)"], - ["EFO:0000000005", "HsapDv:000004 (humanzee)", "EFO:000002", "MONDO:0004 (TMNT)"]], - index=["X", "Y", "Z"], - columns=["good", "good_suffix", "bad", "bad_suffix"]) - - # Good - schema_def = {"type": "curie", "prefixes": ["EFO", "UBERON"]} - errors = validate._validate_column(curie_df["good"], "good", "curie_df", schema_def) - self.assertFalse(errors) - - # Good suffix - schema_def = {"type": "suffixed curie", "prefixes": ["HsapDv", "WHATEVER"]} - errors = validate._validate_column(curie_df["good_suffix"], "good_suffix", "curie_df", schema_def) - self.assertFalse(errors) - - # Bad prefix - schema_def = {"type": "curie", "prefixes": ["EFO"]} - errors = validate._validate_column(curie_df["good"], "good", "curie_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("invalid ontology", errors[0]) - self.assertIn("must be curies from one of these", errors[0]) - - # Bad curies - schema_def = {"type": "curie", "prefixes": ["EFO"]} - errors = validate._validate_column(curie_df["bad"], "bad", "curie_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("invalid ontology", errors[0]) - - # Bad suffixes - schema_def = {"type": "suffixed curie", "prefixes": ["EFO"]} - errors = validate._validate_column(curie_df["bad_suffix"], "bad_suffix", "curie_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("invalid ontology", errors[0]) - - def test_enum(self): - enum_df = pd.DataFrame( - [["abc", "ghi"], - ["def", "jkl"]], - index=["X", "Y"], - columns=["col1", "col2"]) - - # All match - schema_def = {"type": "string", "enum": ["abc", "def", "xyz"]} - errors = validate._validate_column(enum_df["col1"], "col1", "enum_df", schema_def) - self.assertFalse(errors) - - # Missing value - schema_def = {"type": "string", "enum": ["abc", "xyz"]} - errors = validate._validate_column(enum_df["col1"], "col1", "enum_df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("unpermitted values", errors[0]) - - -class TestDictValidations(unittest.TestCase): - - - def test_key_presence(self): - - schema_def = {"keys": {"abc": None, "def": None}} - - dict_ = {"abc": "123", "def": "456"} - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertFalse(errors) - - # Missing keys are bad - dict_ = {"abc": "123"} - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("missing key", errors[0]) - - # Extra keys are okay - dict_ = {"abc": "123", "def": "456", "xyz": "789"} - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertFalse(errors) - - # Better not be empty come on - dict_ = {} - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 2) - - def test_nullable(self): - - schema_def = {"keys": {"abc": {"type": "string", "nullable": False}, - "def": {"type": "string", "nullable": True}}} - - dict_ = {"abc": "xyz", "def": ""} - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertFalse(errors) - - dict_ = {"abc": "", "def": ""} - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("empty value", errors[0]) - - def test_recurse(self): - - schema_def = { - "keys": { - "subdict": { - "type": "dict", - "keys": { - "subdict_key1": None, - "subdict_key2": None - } - }, - "ontology": { - "type": "curie", - "prefixes": ["ONTOLOGY"] - }, - "blob": { - "type": "stringified list of dicts" - } - } - } - - dict_ = { - "subdict": {"subdict_key1": "any", "subdict_key2": "any"}, - "ontology": "ONTOLOGY:123456", - "blob": json.dumps([{"abc": 123}, {"def": 456}]) - } - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertFalse(errors) - - dict_ = { - "subdict": {"subdict_key1": "any"}, - "ontology": "ONTOLOGY:123456", - "blob": json.dumps([{"abc": 123}, {"def": 456}]) - } - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("missing key", errors[0]) - - dict_ = { - "subdict": {"subdict_key1": "any", "subdict_key2": "any"}, - "ontology": "oh no not an ontology term", - "blob": json.dumps([{"abc": 123}, {"def": 456}]) - } - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("invalid ontology", errors[0]) - - dict_ = { - "subdict": {"subdict_key1": "any", "subdict_key2": "any"}, - "ontology": "ONTOLOGY:123456", - "blob": [{"abc": 123}, {"def": 456}] - } - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("JSON-encoded list of dicts", errors[0]) - - # Multiple errors - dict_ = { - "subdict": {"subdict_key1": "any"}, - "ontology": "oh no not an ontology term", - "blob": json.dumps([{"abc": 123}, {"def": 456}]) - } - errors = validate._validate_dict(dict_, "d", schema_def) - self.assertEqual(len(errors), 2) - - -class TestDataframeValidation(unittest.TestCase): - - def test_column_presence(self): - df = pd.DataFrame( - [["abc", "EFO:123"], - ["def", "UBERON:456"]], - columns=["hr_string", "ontology"], - index=["X", "Y"] - ) - - schema_def = { - "columns": { - "hr_string": {"type": "human-readable string"}, - "ontology": {"type": "curie", "prefixes": ["EFO", "UBERON"]} - } - } - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertFalse(errors) - - schema_def = { - "columns": { - "hr_string": {"type": "human-readable string"}, - "another_hr_string": {"type": "human-readable string"}, - "ontology": {"type": "curie", "prefixes": ["EFO", "UBERON"]} - } - } - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("missing column", errors[0]) - - # Extra is okay - df = pd.DataFrame( - [["abc", "EFO:123", "extra"], - ["def", "UBERON:456", "extra"]], - columns=["hr_string", "ontology", "extra"], - index=["X", "Y"] - ) - schema_def = { - "columns": { - "hr_string": {"type": "human-readable string"}, - "ontology": {"type": "curie", "prefixes": ["EFO", "UBERON"]} - } - } - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertFalse(errors) - - - def test_index(self): - df = pd.DataFrame( - [["abc", "123"], - ["def", "456"]], - columns=["col1", "col2"], - index=["ENSG0001", "ENSG0002"] - ) - - schema_def = {"index": {"unique": True}} - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertFalse(errors) - - schema_def = {"index": {"type": "human-readable string"}} - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("non-human-readable", errors[0]) - - df = pd.DataFrame( - [["abc", "123"], - ["def", "456"]], - columns=["col1", "col2"], - index=["ENSG0001", "ENSG0001"] - ) - schema_def = {"index": {"unique": True}} - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertEqual(len(errors), 1) - self.assertIn("is not unique", errors[0]) - - def test_recurse(self): - - df = pd.DataFrame( - [["abc", "HsapDv:0001"], - ["EFO:123", "UBERON:456"]], - columns=["hr_string", "ontology"], - index=["X", "Y"] - ) - schema_def = { - "columns": { - "hr_string": {"type": "human-readable string"}, - "ontology": {"type": "curie", "prefixes": ["EFO", "UBERON"]} - } - } - errors = validate._validate_dataframe(df, "df", schema_def) - self.assertEqual(len(errors), 2) - self.assertEqual(len([e for e in errors if "non-human-readable" in e]), 1) - self.assertEqual(len([e for e in errors if "invalid ontology" in e]), 1) - - -class TestGetSchema(unittest.TestCase): - - def test_get_schema(self): - self.assertIsInstance(validate.get_schema_definition("1.0.0"), dict) - - with self.assertRaises(ValueError): - validate.get_schema_definition("10.1.5") - - -class TestValidate(unittest.TestCase): - - def setUp(self): - self.source_h5ad_path = f"{PROJECT_ROOT}/backend/test/fixtures/pbmc3k-CSC-gz.h5ad" - - def test_shallow(self): - - adata = sc.read_h5ad(self.source_h5ad_path) - self.assertFalse(validate.validate_adata(adata, True)) - - adata.uns["version"] = { - "corpora_schema_version": "1.0.0", - "corpora_encoding_version": "0.1.0" - } - self.assertTrue(validate.validate_adata(adata, True)) - - def test_deep(self): - adata = sc.read_h5ad(self.source_h5ad_path) - self.assertFalse(validate.validate_adata(adata, False)) - - adata.uns["version"] = { - "corpora_schema_version": "1.0.0", - "corpora_encoding_version": "0.1.0" - } - self.assertFalse(validate.validate_adata(adata, False)) diff --git a/backend/test/test_czi_hosted/unit/converters/test_h5ad_data_file.py b/backend/test/test_czi_hosted/unit/converters/test_h5ad_data_file.py deleted file mode 100644 index c750ca1e..00000000 --- a/backend/test/test_czi_hosted/unit/converters/test_h5ad_data_file.py +++ /dev/null @@ -1,284 +0,0 @@ -import json -import unittest -from glob import glob -from os import remove, path -from shutil import rmtree -from uuid import uuid4 - -import anndata -import numpy as np -from pandas import Series, DataFrame -import tiledb - -from backend.czi_hosted.common.corpora import CorporaConstants -from backend.czi_hosted.converters.h5ad_data_file import H5ADDataFile - -from backend.test import PROJECT_ROOT - - -class TestH5ADDataFile(unittest.TestCase): - def setUp(self): - self.sample_anndata = self._create_sample_anndata_dataset() - self.sample_h5ad_filename = self._write_anndata_to_file(self.sample_anndata) - - self.sample_output_directory = path.splitext(self.sample_h5ad_filename)[0] + ".cxg" - - def tearDown(self): - if self.sample_h5ad_filename: - remove(self.sample_h5ad_filename) - - if path.isdir(self.sample_output_directory): - rmtree(self.sample_output_directory) - - def test__create_h5ad_data_file__non_h5ad_raises_exception(self): - non_h5ad_filename = "my_fancy_dataset.csv" - - with self.assertRaises(Exception) as exception_context: - H5ADDataFile(non_h5ad_filename) - - self.assertIn("File must be an H5AD", str(exception_context.exception)) - - def test__create_h5ad_data_file__assert_warning_outputted_if_dataset_title_or_about_given(self): - with self.assertLogs(level="WARN") as logger: - H5ADDataFile( - self.sample_h5ad_filename, - dataset_title="My Awesome Dataset", - dataset_about="http://www.awesomedataset.com", - use_corpora_schema=False, - ) - - self.assertIn("will override any metadata that is extracted", logger.output[0]) - - def test__create_h5ad_data_file__reads_anndata_successfully(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename, use_corpora_schema=False) - - self.assertTrue((h5ad_file.anndata.X == self.sample_anndata.X).all()) - self.assertEqual( - h5ad_file.anndata.obs.sort_index(inplace=True), self.sample_anndata.obs.sort_index(inplace=True) - ) - self.assertEqual( - h5ad_file.anndata.var.sort_index(inplace=True), self.sample_anndata.var.sort_index(inplace=True) - ) - - for key in h5ad_file.anndata.obsm.keys(): - self.assertIn(key, self.sample_anndata.obsm.keys()) - self.assertTrue((h5ad_file.anndata.obsm[key] == self.sample_anndata.obsm[key]).all()) - - for key in self.sample_anndata.obsm.keys(): - self.assertIn(key, h5ad_file.anndata.obsm.keys()) - self.assertTrue((h5ad_file.anndata.obsm[key] == self.sample_anndata.obsm[key]).all()) - - def test__create_h5ad_data_file__copies_index_of_obs_and_var_to_column(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename, use_corpora_schema=False) - - # The automatic name chosen for the index should be "name_0" - self.assertNotIn("name_0", self.sample_anndata.obs.columns) - self.assertIn("name_0", h5ad_file.obs.columns) - - self.assertNotIn("name_0", self.sample_anndata.var.columns) - self.assertIn("name_0", h5ad_file.var.columns) - - def test__create_h5ad_data_file__no_copy_if_obs_and_var_index_names_specified(self): - h5ad_file = H5ADDataFile( - self.sample_h5ad_filename, - use_corpora_schema=False, - obs_index_column_name="float_category", - vars_index_column_name="int_category", - ) - - self.assertNotIn("name_0", h5ad_file.obs.columns) - self.assertNotIn("name_0", h5ad_file.var.columns) - - def test__create_h5ad_data_file__obs_and_var_index_names_specified_not_unique_raises_exception(self): - - with self.assertRaises(Exception) as exception_context: - H5ADDataFile( - self.sample_h5ad_filename, - use_corpora_schema=False, - obs_index_column_name="float_category", - vars_index_column_name="bool_category", - ) - - self.assertIn("Please prepare data to contain unique values", str(exception_context.exception)) - - def test__create_h5ad_data_file__obs_and_var_index_names_specified_doesnt_exist_raises_exception(self): - with self.assertRaises(Exception) as exception_context: - H5ADDataFile( - self.sample_h5ad_filename, - use_corpora_schema=False, - obs_index_column_name="unknown_category", - vars_index_column_name="i_dont_exist", - ) - - self.assertIn("does not exist", str(exception_context.exception)) - - def test__create_h5ad_data_file__extract_about_and_title_from_dataset(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename) - - self.assertEqual(h5ad_file.dataset_title, "random_link_name") - self.assertEqual(h5ad_file.dataset_about, "www.link.com") - - def test__create_h5ad_data_file__inputted_dataset_title_and_about_overrides_extracted(self): - h5ad_file = H5ADDataFile( - self.sample_h5ad_filename, dataset_about="override_about", dataset_title="override_title" - ) - - self.assertEqual(h5ad_file.dataset_title, "override_title") - self.assertEqual(h5ad_file.dataset_about, "override_about") - - def test__to_cxg__simple_anndata_no_corpora_and_sparse(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename, use_corpora_schema=False) - h5ad_file.to_cxg(self.sample_output_directory, 100) - - self._validate_cxg_and_h5ad_content_match(self.sample_h5ad_filename, self.sample_output_directory, True) - - def test__to_cxg__simple_anndata_with_corpora_and_sparse(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename) - h5ad_file.to_cxg(self.sample_output_directory, 100) - - self._validate_cxg_and_h5ad_content_match(self.sample_h5ad_filename, self.sample_output_directory, True) - - def test__to_cxg__simple_anndata_no_corpora_and_dense(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename, use_corpora_schema=False) - h5ad_file.to_cxg(self.sample_output_directory, 0) - - self._validate_cxg_and_h5ad_content_match(self.sample_h5ad_filename, self.sample_output_directory, False) - - def test__to_cxg__simple_anndata_with_corpora_and_dense(self): - h5ad_file = H5ADDataFile(self.sample_h5ad_filename) - h5ad_file.to_cxg(self.sample_output_directory, 0) - - self._validate_cxg_and_h5ad_content_match(self.sample_h5ad_filename, self.sample_output_directory, False) - - def test__to_cxg__with_sparse_column_encoding(self): - anndata = self._create_sample_anndata_dataset() - anndata.X = np.ones((3, 4)) - sparse_with_column_shift_filename = self._write_anndata_to_file(anndata) - - h5ad_file = H5ADDataFile(sparse_with_column_shift_filename) - h5ad_file.to_cxg(self.sample_output_directory, 50) - - self._validate_cxg_and_h5ad_content_match( - sparse_with_column_shift_filename, self.sample_output_directory, False, has_column_encoding=True - ) - - # Clean up - remove(sparse_with_column_shift_filename) - - def _validate_cxg_and_h5ad_content_match(self, h5ad_filename, cxg_directory, is_sparse, has_column_encoding=False): - anndata_object = anndata.read_h5ad(h5ad_filename) - - # Array locations - metadata_array_location = f"{cxg_directory}/cxg_group_metadata" - main_x_array_location = f"{cxg_directory}/X" - embedding_array_location = f"{cxg_directory}/emb" - specific_embedding_array_location = f"{self.sample_output_directory}/emb/awesome_embedding" - obs_array_location = f"{cxg_directory}/obs" - var_array_location = f"{cxg_directory}/var" - x_col_shift_array_location = f"{cxg_directory}/X_col_shift" - - # Assert CXG structure - self.assertEqual(tiledb.object_type(cxg_directory), "group") - self.assertEqual(tiledb.object_type(obs_array_location), "array") - self.assertEqual(tiledb.object_type(var_array_location), "array") - self.assertEqual(tiledb.object_type(main_x_array_location), "array") - self.assertEqual(tiledb.object_type(embedding_array_location), "group") - self.assertEqual(tiledb.object_type(specific_embedding_array_location), "array") - - if has_column_encoding: - self.assertEqual(tiledb.object_type(x_col_shift_array_location), "array") - - # Validate metadata - metadata_array = tiledb.DenseArray(metadata_array_location, mode="r") - self.assertIn("cxg_version", metadata_array.meta) - - # Validate obs index - obs_array = tiledb.DenseArray(obs_array_location, mode="r") - expected_index_data = anndata_object.obs.index.to_numpy() - index_name = json.loads(obs_array.meta["cxg_schema"])["index"] - actual_index_data = obs_array.query(attrs=[index_name])[:][index_name] - self.assertTrue(np.array_equal(expected_index_data, actual_index_data)) - - # Validate obs columns - expected_columns = list(anndata_object.obs.columns.values) - for column_name in expected_columns: - expected_data = anndata_object.obs[column_name].to_numpy() - actual_data = obs_array.query(attrs=[column_name])[:][column_name] - self.assertTrue(np.array_equal(expected_data, actual_data)) - - # Validate var index - var_array = tiledb.DenseArray(var_array_location, mode="r") - expected_index_data = anndata_object.var.index.to_numpy() - index_name = json.loads(var_array.meta["cxg_schema"])["index"] - actual_index_data = var_array.query(attrs=[index_name])[:][index_name] - self.assertTrue(np.array_equal(expected_index_data, actual_index_data)) - - # Validate var columns - expected_columns = anndata_object.var.columns.values - for column_name in expected_columns: - expected_data = anndata_object.var[column_name].to_numpy() - actual_data = var_array.query(attrs=[column_name])[:][column_name] - self.assertTrue(np.array_equal(expected_data, actual_data)) - - # Validate embedding - expected_embedding_data = anndata_object.obsm.get("X_awesome_embedding") - embedding_array = tiledb.DenseArray(specific_embedding_array_location, mode="r") - actual_embedding_data = embedding_array[:, 0:2] - self.assertTrue(np.array_equal(expected_embedding_data, actual_embedding_data)) - - # Validate X matrix if not column shifted - if not has_column_encoding: - expected_x_data = anndata_object.X - if is_sparse: - x_array = tiledb.SparseArray(main_x_array_location, mode="r") - actual_x_data = np.reshape(x_array[:, :][""], expected_x_data.shape) - else: - x_array = tiledb.DenseArray(main_x_array_location, mode="r") - actual_x_data = x_array[:, :] - self.assertTrue(np.array_equal(expected_x_data, actual_x_data)) - - def _write_anndata_to_file(self, anndata): - temporary_filename = f"{PROJECT_ROOT}/backend/test/fixtures/{uuid4()}.h5ad" - anndata.write(temporary_filename) - - return temporary_filename - - def _create_sample_anndata_dataset(self): - # Create X - X = np.random.rand(3, 4) - - # Create obs - random_string_category = Series(data=["a", "b", "b"], dtype="category") - random_float_category = Series(data=[3.2, 1.1, 2.2], dtype=np.float32) - obs_dataframe = DataFrame( - data={"string_category": random_string_category, "float_category": random_float_category} - ) - obs = obs_dataframe - - # Create vars - random_int_category = Series(data=[3, 1, 2, 4], dtype=np.int32) - random_bool_category = Series(data=[True, True, False, True], dtype=np.bool_) - var_dataframe = DataFrame(data={"int_category": random_int_category, "bool_category": random_bool_category}) - var = var_dataframe - - # Create embeddings - random_embedding = np.random.rand(3, 2) - obsm = {"X_awesome_embedding": random_embedding} - - # Create uns corpora metadata - uns = {} - for metadata_field in CorporaConstants.REQUIRED_SIMPLE_METADATA_FIELDS: - uns[metadata_field] = "random" - - for metadata_field in CorporaConstants.OPTIONAL_JSON_ENCODED_METADATA_FIELD: - uns[metadata_field] = json.dumps({"random_key": "random_value"}) - - # Need to carefully set the corpora schema versions in order for tests to pass. - uns["version"] = {"corpora_schema_version": "1.0.0", "corpora_encoding_version": "0.1.0"} - - # Set project links to be a dictionary - uns["project_links"] = json.dumps( - [{"link_name": "random_link_name", "link_url": "www.link.com", "link_type": "SUMMARY"}] - ) - - return anndata.AnnData(X=X, obs=obs, var=var, obsm=obsm, uns=uns) diff --git a/backend/test/test_czi_hosted/unit/data_anndata/__init__.py b/backend/test/test_czi_hosted/unit/data_anndata/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/data_anndata/test_anndata_adaptor.py b/backend/test/test_czi_hosted/unit/data_anndata/test_anndata_adaptor.py deleted file mode 100644 index 7788257e..00000000 --- a/backend/test/test_czi_hosted/unit/data_anndata/test_anndata_adaptor.py +++ /dev/null @@ -1,198 +0,0 @@ -import json -import sys -import time -import unittest - -import numpy as np -import pandas as pd -import pytest -from parameterized import parameterized_class - -from backend.common.utils.data_locator import DataLocator -from backend.common.errors import FilterError -from backend.czi_hosted.data_anndata.anndata_adaptor import AnndataAdaptor -from backend.test.test_czi_hosted.unit import app_config -from backend.test import PROJECT_ROOT, FIXTURES_ROOT, decode_fbs -from backend.test.fixtures.fixtures import pbmc3k_colors - -""" -Test the anndata adaptor using the pbmc3k data set. -""" - - -@parameterized_class( - ("data_locator", "backed"), - [ - (f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad", False), - (f"{FIXTURES_ROOT}/pbmc3k-CSC-gz.h5ad", False), - (f"{FIXTURES_ROOT}/pbmc3k-CSR-gz.h5ad", False), - (f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad", True), - (f"{FIXTURES_ROOT}/pbmc3k-CSC-gz.h5ad", True), - (f"{FIXTURES_ROOT}/pbmc3k-CSR-gz.h5ad", True), - ], -) -class AdaptorTest(unittest.TestCase): - def setUp(self): - config = app_config(self.data_locator, self.backed) - self.data = AnndataAdaptor(DataLocator(self.data_locator), config) - - def test_init(self): - self.assertEqual(self.data.cell_count, 2638) - self.assertEqual(self.data.gene_count, 1838) - epsilon = 0.000_005 - self.assertTrue(self.data.data.X[0, 0] - -0.171_469_51 < epsilon) - - def test_mandatory_annotations(self): - obs_index_col_name = self.data.get_schema()["annotations"]["obs"]["index"] - self.assertIn(obs_index_col_name, self.data.data.obs) - self.assertEqual(list(self.data.data.obs.index), list(range(2638))) - var_index_col_name = self.data.get_schema()["annotations"]["var"]["index"] - self.assertIn(var_index_col_name, self.data.data.var) - self.assertEqual(list(self.data.data.var.index), list(range(1838))) - - @pytest.mark.filterwarnings("ignore:Anndata data matrix") - def test_data_type(self): - # don't run the test on the more exotic data types, as they don't - # support the astype() interface (used by this test, but not underlying app) - if isinstance(self.data.data.X, np.ndarray): - self.data.data.X = self.data.data.X.astype("float64") - with self.assertWarns(UserWarning): - self.data._validate_data_types() - - def test_filter_idx(self): - filter_ = {"filter": {"var": {"index": [1, 99, [200, 300]]}}} - fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - data = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(data["n_rows"], 2638) - self.assertEqual(data["n_cols"], 102) - - def test_filter_complex(self): - filter_ = { - "filter": {"var": {"annotation_value": [{"name": "n_cells", "min": 10}], "index": [1, 99, [200, 300]]}} - } - fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - data = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(data["n_rows"], 2638) - self.assertEqual(data["n_cols"], 91) - - def test_obs_and_var_names(self): - self.assertEqual(np.sum(self.data.data.var[self.data.get_schema()["annotations"]["var"]["index"]].isna()), 0) - self.assertEqual(np.sum(self.data.data.obs[self.data.get_schema()["annotations"]["obs"]["index"]].isna()), 0) - - def test_get_colors(self): - self.assertEqual(self.data.get_colors(), pbmc3k_colors) - - def test_get_schema(self): - with open(f"{FIXTURES_ROOT}/schema.json") as fh: - schema = json.load(fh) - self.assertDictEqual(self.data.get_schema(), schema) - - def test_schema_produces_error(self): - self.data.data.obs["time"] = pd.Series( - list([time.time() for i in range(self.data.cell_count)]), dtype="datetime64[ns]", - ) - with pytest.raises(TypeError): - self.data._create_schema() - - def test_layout(self): - fbs = self.data.layout_to_fbs_matrix(fields=None) - layout = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(layout["n_cols"], 6) - self.assertEqual(layout["n_rows"], 2638) - - X = layout["columns"][0] - self.assertTrue((X >= 0).all() and (X <= 1).all()) - Y = layout["columns"][1] - self.assertTrue((Y >= 0).all() and (Y <= 1).all()) - - def test_layout_fields(self): - """ X_pca, X_tsne, X_umap are available """ - fbs = self.data.layout_to_fbs_matrix(["pca"]) - layout = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(layout["n_cols"], 2) - self.assertEqual(layout["n_rows"], 2638) - self.assertCountEqual(layout["col_idx"], ["pca_0", "pca_1"]) - - fbs = self.data.layout_to_fbs_matrix(["tsne", "pca"]) - layout = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(layout["n_cols"], 4) - self.assertEqual(layout["n_rows"], 2638) - self.assertCountEqual(layout["col_idx"], ["tsne_0", "tsne_1", "pca_0", "pca_1"]) - - def test_annotations(self): - fbs = self.data.annotation_to_fbs_matrix("obs") - annotations = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(annotations["n_rows"], 2638) - self.assertEqual(annotations["n_cols"], 5) - obs_index_col_name = self.data.get_schema()["annotations"]["obs"]["index"] - self.assertEqual( - annotations["col_idx"], [obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain"], - ) - - fbs = self.data.annotation_to_fbs_matrix("var") - annotations = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(annotations["n_rows"], 1838) - self.assertEqual(annotations["n_cols"], 2) - var_index_col_name = self.data.get_schema()["annotations"]["var"]["index"] - self.assertEqual(annotations["col_idx"], [var_index_col_name, "n_cells"]) - - def test_annotation_fields(self): - fbs = self.data.annotation_to_fbs_matrix("obs", ["n_genes", "n_counts"]) - annotations = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(annotations["n_rows"], 2638) - self.assertEqual(annotations["n_cols"], 2) - - var_index_col_name = self.data.get_schema()["annotations"]["var"]["index"] - fbs = self.data.annotation_to_fbs_matrix("var", [var_index_col_name]) - annotations = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(annotations["n_rows"], 1838) - self.assertEqual(annotations["n_cols"], 1) - - def test_diffexp_topN(self): - f1 = {"filter": {"obs": {"index": [[0, 500]]}}} - f2 = {"filter": {"obs": {"index": [[500, 1000]]}}} - result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"])) - self.assertEqual(len(result['positive']), 10) - self.assertEqual(len(result['negative']), 10) - result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"], 20)) - self.assertEqual(len(result['positive']), 20) - self.assertEqual(len(result['negative']), 20) - - def test_data_frame(self): - f1 = {"var": {"index": [[0, 10]]}} - fbs = self.data.data_frame_to_fbs_matrix(f1, "var") - data = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(data["n_rows"], 2638) - self.assertEqual(data["n_cols"], 10) - - with self.assertRaises(ValueError): - self.data.data_frame_to_fbs_matrix(None, "obs") - - def test_filtered_data_frame(self): - filter_ = {"filter": {"var": {"annotation_value": [{"name": "n_cells", "min": 100}]}}} - fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - data = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(data["n_rows"], 2638) - self.assertEqual(data["n_cols"], 1040) - - filter_ = {"filter": {"obs": {"annotation_value": [{"name": "n_counts", "min": 3000}]}}} - with self.assertRaises(FilterError): - self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - - def test_data_named_gene(self): - var_index_col_name = self.data.get_schema()["annotations"]["var"]["index"] - filter_ = {"filter": {"var": {"annotation_value": [{"name": var_index_col_name, "values": ["RER1"]}]}}} - fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - data = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(data["n_rows"], 2638) - self.assertEqual(data["n_cols"], 1) - self.assertEqual(data["col_idx"], [4]) - - filter_ = { - "filter": {"var": {"annotation_value": [{"name": var_index_col_name, "values": ["SPEN", "TYMP", "PRMT2"]}]}} - } - fbs = self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - data = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(data["n_rows"], 2638) - self.assertEqual(data["n_cols"], 3) - self.assertTrue((data["col_idx"] == [15, 1818, 1837]).all()) diff --git a/backend/test/test_czi_hosted/unit/data_anndata/test_anndata_adaptor_data_load.py b/backend/test/test_czi_hosted/unit/data_anndata/test_anndata_adaptor_data_load.py deleted file mode 100644 index 9a258198..00000000 --- a/backend/test/test_czi_hosted/unit/data_anndata/test_anndata_adaptor_data_load.py +++ /dev/null @@ -1,86 +0,0 @@ -import unittest -import json - -from backend.common.utils.data_locator import DataLocator -from backend.czi_hosted.data_anndata.anndata_adaptor import AnndataAdaptor -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import PROJECT_ROOT - - -class DataLoadAdaptorTest(unittest.TestCase): - """ - Test file loading, including deferred loading/update. - """ - - def setUp(self): - self.data_file = DataLocator(f"{PROJECT_ROOT}/example-dataset/pbmc3k.h5ad") - config = AppConfig() - config.update_server_config(single_dataset__datapath=self.data_file.path) - config.update_server_config(app__flask_secret_key="secret") - config.complete_config() - self.data = AnndataAdaptor(self.data_file, config) - - def test_delayed_load_data(self): - self.data._create_schema() - self.assertEqual(self.data.cell_count, 2638) - self.assertEqual(self.data.gene_count, 1838) - epsilon = 0.000_005 - self.assertTrue(self.data.data.X[0, 0] - -0.171_469_51 < epsilon) - - def test_diffexp_topN(self): - f1 = {"filter": {"obs": {"index": [[0, 500]]}}} - f2 = {"filter": {"obs": {"index": [[500, 1000]]}}} - - result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"])) - - self.assertEqual(len(result['positive']), 10) - self.assertEqual(len(result['negative']), 10) - - result = json.loads(self.data.diffexp_topN(f1["filter"], f2["filter"], 20)) - self.assertEqual(len(result['positive']), 20) - self.assertEqual(len(result['negative']), 20) - - -class DataLocatorAdaptorTest(unittest.TestCase): - """ - Test various types of data locators we expect to consume - """ - - def get_basic_config(self): - config = AppConfig() - config.update_server_config( - single_dataset__obs_names=None, single_dataset__var_names=None, - ) - config.update_server_config(app__flask_secret_key="secret") - config.update_default_dataset_config( - embeddings__names=["umap"], presentation__max_categories=100, diffexp__lfc_cutoff=0.01, - ) - return config - - def stdAsserts(self, data): - """ run these each time we load the data """ - self.assertIsNotNone(data) - self.assertEqual(data.cell_count, 2638) - self.assertEqual(data.gene_count, 1838) - - def test_posix_file(self): - locator = DataLocator("../../example-dataset/pbmc3k.h5ad") - config = self.get_basic_config() - config.update_server_config(single_dataset__datapath=locator.path) - config.complete_config() - data = AnndataAdaptor(locator, config) - self.stdAsserts(data) - - def test_url_https(self): - url = "https://raw.githubusercontent.com/chanzuckerberg/cellxgene/main/example-dataset/pbmc3k.h5ad" - locator = DataLocator(url) - config = self.get_basic_config() - data = AnndataAdaptor(locator, config) - self.stdAsserts(data) - - def test_url_http(self): - url = "http://raw.githubusercontent.com/chanzuckerberg/cellxgene/main/example-dataset/pbmc3k.h5ad" - locator = DataLocator(url) - config = self.get_basic_config() - data = AnndataAdaptor(locator, config) - self.stdAsserts(data) diff --git a/backend/test/test_czi_hosted/unit/data_anndata/test_nan_anndata_adaptor.py b/backend/test/test_czi_hosted/unit/data_anndata/test_nan_anndata_adaptor.py deleted file mode 100644 index 16a20fe7..00000000 --- a/backend/test/test_czi_hosted/unit/data_anndata/test_nan_anndata_adaptor.py +++ /dev/null @@ -1,64 +0,0 @@ -import math -import unittest -import warnings - -import pytest - -from backend.common.utils.data_locator import DataLocator -from backend.common.errors import FilterError -from backend.czi_hosted.data_anndata.anndata_adaptor import AnndataAdaptor -from backend.test.test_czi_hosted.unit import app_config -from backend.test import FIXTURES_ROOT, decode_fbs - - -class NaNTest(unittest.TestCase): - def setUp(self): - self.data_locator = DataLocator(f"{FIXTURES_ROOT}/nan.h5ad") - self.config = app_config(self.data_locator.path) - - with warnings.catch_warnings(): - warnings.simplefilter("ignore", category=UserWarning) - self.data = AnndataAdaptor(self.data_locator, self.config) - self.data._create_schema() - - def test_load(self): - with self.assertLogs(level="WARN") as logger: - self.data = AnndataAdaptor(self.data_locator, self.config) - self.assertTrue(logger.output) - - def test_init(self): - self.assertEqual(self.data.cell_count, 100) - self.assertEqual(self.data.gene_count, 100) - epsilon = 0.000_005 - self.assertTrue(self.data.data.X[0, 0] - -0.171_469_51 < epsilon) - - def test_dataframe(self): - data_frame_var = decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "var")) - self.assertIsNotNone(data_frame_var) - self.assertEqual(data_frame_var["n_rows"], 100) - self.assertEqual(data_frame_var["n_cols"], 100) - self.assertTrue(math.isnan(data_frame_var["columns"][3][3])) - - with pytest.raises(FilterError): - self.data.data_frame_to_fbs_matrix("an erroneous filter", "var") - with pytest.raises(FilterError): - filter_ = {"filter": {"obs": {"index": [1, 99, [200, 300]]}}} - self.data.data_frame_to_fbs_matrix(filter_["filter"], "var") - - def test_dataframe_obs_not_implemented(self): - with self.assertRaises(ValueError) as cm: - decode_fbs.decode_matrix_FBS(self.data.data_frame_to_fbs_matrix(None, "obs")) - self.assertIsNotNone(cm.exception) - - def test_annotation(self): - annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("obs")) - obs_index_col_name = self.data.schema["annotations"]["obs"]["index"] - self.assertEqual(annotations["col_idx"], [obs_index_col_name, "n_genes", "percent_mito", "n_counts", "louvain"]) - self.assertEqual(annotations["n_rows"], 100) - self.assertTrue(math.isnan(annotations["columns"][2][0])) - - annotations = decode_fbs.decode_matrix_FBS(self.data.annotation_to_fbs_matrix("var")) - var_index_col_name = self.data.schema["annotations"]["var"]["index"] - self.assertEqual(annotations["col_idx"], [var_index_col_name, "n_cells", "var_with_nans"]) - self.assertEqual(annotations["n_rows"], 100) - self.assertTrue(math.isnan(annotations["columns"][2][0])) diff --git a/backend/test/test_czi_hosted/unit/data_common/__init__.py b/backend/test/test_czi_hosted/unit/data_common/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/data_common/fbs/__init__.py b/backend/test/test_czi_hosted/unit/data_common/fbs/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/data_common/fbs/test_matrix.py b/backend/test/test_czi_hosted/unit/data_common/fbs/test_matrix.py deleted file mode 100644 index 21389fe0..00000000 --- a/backend/test/test_czi_hosted/unit/data_common/fbs/test_matrix.py +++ /dev/null @@ -1,82 +0,0 @@ -import unittest -import pandas as pd -import numpy as np -from scipy import sparse - -from backend.test import decode_fbs -from backend.common.fbs.matrix import encode_matrix_fbs, decode_matrix_fbs - - -class FbsTests(unittest.TestCase): - """Test Case for Matrix FBS data encode/decode """ - - def test_encode_boundary(self): - """ test various boundary checks """ - - # row indexing is unsupported - with self.assertRaises(ValueError): - encode_matrix_fbs(matrix=pd.DataFrame(), row_idx=[]) - - # matrix must be 2D - with self.assertRaises(ValueError): - encode_matrix_fbs(matrix=np.zeros((3, 2, 1))) - with self.assertRaises(ValueError): - encode_matrix_fbs(matrix=np.ones((10,))) - - def fbs_checks(self, fbs, dims, expected_types, expected_column_idx): - d = decode_fbs.decode_matrix_FBS(fbs) - self.assertEqual(d["n_rows"], dims[0]) - self.assertEqual(d["n_cols"], dims[1]) - self.assertIsNone(d["row_idx"]) - self.assertEqual(len(d["columns"]), dims[1]) - for i in range(0, len(d["columns"])): - self.assertEqual(len(d["columns"][i]), dims[0]) - self.assertIsInstance(d["columns"][i], expected_types[i][0]) - if expected_types[i][1] is not None: - self.assertEqual(d["columns"][i].dtype, expected_types[i][1]) - if expected_column_idx is not None: - self.assertSetEqual(set(expected_column_idx), set(d["col_idx"])) - - def test_encode_DataFrame(self): - df = pd.DataFrame( - data={ - "a": np.zeros((10,), dtype=np.float32), - "b": np.ones((10,), dtype=np.int64), - "c": np.array([i for i in range(0, 10)], dtype=np.uint16), - "d": pd.Series(["x", "y", "z", "x", "y", "z", "a", "x", "y", "z"], dtype="category"), - } - ) - expected_types = ((np.ndarray, np.float32), (np.ndarray, np.int32), (np.ndarray, np.int32), (list, None)) - fbs = encode_matrix_fbs(matrix=df, row_idx=None, col_idx=df.columns) - self.fbs_checks(fbs, (10, 4), expected_types, ["a", "b", "c", "d"]) - - def test_encode_ndarray(self): - arr = np.zeros((3, 2), dtype=np.float32) - expected_types = ((np.ndarray, np.float32), (np.ndarray, np.float32), (np.ndarray, np.float32)) - fbs = encode_matrix_fbs(matrix=arr, row_idx=None, col_idx=None) - self.fbs_checks(fbs, (3, 2), expected_types, None) - - def test_encode_sparse(self): - csc = sparse.csc_matrix(np.array([[0, 1, 2], [3, 0, 4]])) - expected_types = ((np.ndarray, np.int32), (np.ndarray, np.int32), (np.ndarray, np.int32)) - fbs = encode_matrix_fbs(matrix=csc, row_idx=None, col_idx=None) - self.fbs_checks(fbs, (2, 3), expected_types, None) - - def test_roundtrip(self): - dfSrc = pd.DataFrame( - data={ - "a": np.zeros((10,), dtype=np.float32), - "b": np.ones((10,), dtype=np.int64), - "c": np.array([i for i in range(0, 10)], dtype=np.uint16), - "d": pd.Series(["x", "y", "z", "x", "y", "z", "a", "x", "y", "z"], dtype="category"), - } - ) - dfDst = decode_matrix_fbs(encode_matrix_fbs(matrix=dfSrc, col_idx=dfSrc.columns)) - self.assertEqual(dfSrc.shape, dfDst.shape) - self.assertEqual(set(dfSrc.columns), set(dfDst.columns)) - for c in dfSrc.columns: - self.assertTrue(c in dfDst.columns) - if isinstance(dfSrc[c], pd.Series): - self.assertTrue(np.all(dfSrc[c] == dfDst[c])) - else: - self.assertEqual(dfSrc[c], dfDst[c]) diff --git a/backend/test/test_czi_hosted/unit/data_common/test_matrix_loader.py b/backend/test/test_czi_hosted/unit/data_common/test_matrix_loader.py deleted file mode 100644 index 3b39e7c3..00000000 --- a/backend/test/test_czi_hosted/unit/data_common/test_matrix_loader.py +++ /dev/null @@ -1,126 +0,0 @@ -import os -import shutil -import tempfile -import time -import unittest - -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.common.errors import DatasetAccessError -from backend.czi_hosted.data_common.matrix_loader import MatrixDataCacheManager -from backend.test import FIXTURES_ROOT - - -class MatrixCacheTest(unittest.TestCase): - def setup(self): - pass - - def make_temporay_datasets(self, dirname, num): - source = f"{FIXTURES_ROOT}/pbmc3k.cxg" - for i in range(num): - target = os.path.join(dirname, str(i) + ".cxg") - shutil.copytree(source, target) - - def use_dataset(self, matrix_cache, dirname, app_config, dataset_index): - with matrix_cache.data_adaptor(None, os.path.join(dirname, str(dataset_index) + ".cxg"), app_config) as adaptor: - pass - return adaptor - - def use_dataset_with_error(self, matrix_cache, dirname, app_config, dataset_index): - try: - with matrix_cache.data_adaptor(None, os.path.join(dirname, str(dataset_index) + ".cxg"), app_config): - raise DatasetAccessError("something bad happened") - except DatasetAccessError: - # the MatrixDataCacheManager rethrows the exception, so catch and ignore - pass - - def get_datasets(self, matrix_cache, dirname): - datasets = matrix_cache.datasets - result = {} - for k, v in datasets.items(): - # filter out the dirname and the .cxg from the name - newk = int(k[1][len(dirname) + 1 : -4]) - result[newk] = v - - return result - - def check_datasets(self, matrix_cache, dirname, expected): - res = self.get_datasets(matrix_cache, dirname) - actual = res.keys() - self.assertSetEqual(set(actual), set(expected)) - - def test_basic(self): - with tempfile.TemporaryDirectory() as dirname: - self.make_temporay_datasets(dirname, 5) - app_config = AppConfig() - m = MatrixDataCacheManager(max_cached=3, timelimit_s=None) - - # should have only dataset 0 - self.use_dataset(m, dirname, app_config, 0) - self.check_datasets(m, dirname, [0]) - - # should have datasets 0, 1 - self.use_dataset(m, dirname, app_config, 1) - self.check_datasets(m, dirname, [0, 1]) - - # should have datasets 0, 1, 2 - self.use_dataset(m, dirname, app_config, 2) - self.check_datasets(m, dirname, [0, 1, 2]) - - # should have datasets 1, 2, 3 - self.use_dataset(m, dirname, app_config, 3) - self.check_datasets(m, dirname, [1, 2, 3]) - - # use dataset 1, making is more recent than dataset 2 - self.use_dataset(m, dirname, app_config, 1) - self.check_datasets(m, dirname, [1, 2, 3]) - - # use dataset 4, should have 1,3,4 - self.use_dataset(m, dirname, app_config, 4) - self.check_datasets(m, dirname, [1, 3, 4]) - - # use dataset 4 a few more times, get the count to 3 - self.use_dataset(m, dirname, app_config, 4) - self.use_dataset(m, dirname, app_config, 4) - - datasets = self.get_datasets(m, dirname) - self.assertEqual(datasets[1].num_access, 2) - self.assertEqual(datasets[3].num_access, 1) - self.assertEqual(datasets[4].num_access, 3) - - def test_timelimit(self): - with tempfile.TemporaryDirectory() as dirname: - self.make_temporay_datasets(dirname, 2) - - app_config = AppConfig() - m = MatrixDataCacheManager(max_cached=3, timelimit_s=1) - - adaptor = self.use_dataset(m, dirname, app_config, 0) - adaptor1 = self.use_dataset(m, dirname, app_config, 0) - self.assertTrue(adaptor is adaptor1) - - # wait until the timelimit expires and check that there is a new adaptor - time.sleep(1.1) - adaptor2 = self.use_dataset(m, dirname, app_config, 0) - self.assertTrue(adaptor is not adaptor2) - self.check_datasets(m, dirname, [0]) - - # now load a different dataset and see if dataset 0 gets evicted - time.sleep(1.1) - self.use_dataset(m, dirname, app_config, 1) - self.check_datasets(m, dirname, [1]) - - def test_access_error(self): - with tempfile.TemporaryDirectory() as dirname: - self.make_temporay_datasets(dirname, 1) - - app_config = AppConfig() - m = MatrixDataCacheManager(max_cached=3, timelimit_s=1) - - # use the 0 datasets - self.use_dataset(m, dirname, app_config, 0) - self.check_datasets(m, dirname, [0]) - - # use the 0 datasets, but this time a DatasetAccessError is raised. - # verify that dataset is removed from the cache. - self.use_dataset_with_error(m, dirname, app_config, 0) - self.check_datasets(m, dirname, []) diff --git a/backend/test/test_czi_hosted/unit/data_cxg/__init__.py b/backend/test/test_czi_hosted/unit/data_cxg/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/data_cxg/test_cxg_adaptor.py b/backend/test/test_czi_hosted/unit/data_cxg/test_cxg_adaptor.py deleted file mode 100644 index 8775a1f3..00000000 --- a/backend/test/test_czi_hosted/unit/data_cxg/test_cxg_adaptor.py +++ /dev/null @@ -1,20 +0,0 @@ -import unittest - -from backend.common.utils.data_locator import DataLocator -from backend.czi_hosted.data_cxg.cxg_adaptor import CxgAdaptor -from backend.test.test_czi_hosted.unit import app_config -from backend.test import FIXTURES_ROOT -from backend.test.fixtures.fixtures import pbmc3k_colors - - -class TestCxgAdaptor(unittest.TestCase): - def test_get_colors(self): - data = self.get_data("pbmc3k.cxg") - self.assertDictEqual(data.get_colors(), pbmc3k_colors) - data = self.get_data("pbmc3k_v0.cxg") - self.assertDictEqual(data.get_colors(), dict()) - - def get_data(self, fixture): - data_locator = f"{FIXTURES_ROOT}/{fixture}" - config = app_config(data_locator) - return CxgAdaptor(DataLocator(data_locator), config) diff --git a/backend/test/test_czi_hosted/unit/eb/__init__.py b/backend/test/test_czi_hosted/unit/eb/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/backend/test/test_czi_hosted/unit/eb/test_eb.py b/backend/test/test_czi_hosted/unit/eb/test_eb.py deleted file mode 100644 index 9dba1bc9..00000000 --- a/backend/test/test_czi_hosted/unit/eb/test_eb.py +++ /dev/null @@ -1,82 +0,0 @@ -import os -from unittest.mock import patch - -import requests -import subprocess -import tempfile -import time -import unittest - -from contextlib import contextmanager -from backend.czi_hosted.common.config.app_config import AppConfig -from backend.test import PROJECT_ROOT, FIXTURES_ROOT - - -@contextmanager -def run_eb_app(tempdirname): - ps = subprocess.Popen(["python", "artifact.dir/application.py"], cwd=tempdirname) - server = "http://localhost:5000" - - for _ in range(10): - try: - requests.get(f"{server}/health") - break - except requests.exceptions.ConnectionError: - time.sleep(1) - - try: - yield server - finally: - try: - ps.terminate() - except ProcessLookupError: - pass - - -class Elastic_Beanstalk_Test(unittest.TestCase): - def test_run(self): - tempdir = tempfile.TemporaryDirectory(dir=f"{PROJECT_ROOT}/backend/czi_hosted") - tempdirname = tempdir.name - config = AppConfig() - # test that eb works - config.update_server_config(multi_dataset__dataroot=f"{FIXTURES_ROOT}", app__flask_secret_key="open sesame") - config.complete_config() - config.write_config(f"{tempdirname}/config.yaml") - subprocess.check_call(f"git ls-files . | cpio -pdm {tempdirname}", cwd=f"{PROJECT_ROOT}/backend/czi_hosted/eb", - shell=True) - subprocess.check_call(["make", "build"], cwd=tempdirname) - with run_eb_app(tempdirname) as server: - session = requests.Session() - response = session.get(f"{server}/d/pbmc3k.cxg/api/v0.2/config") - data_config = response.json() - assert data_config["config"]["displayNames"]["dataset"] == "pbmc3k" - - def test_config(self): - check_config_script = os.path.join(PROJECT_ROOT, "backend", "czi_hosted", "eb", "check_config.py") - with tempfile.TemporaryDirectory() as tempdir: - configfile = os.path.join(tempdir, "config.yaml") - app_config = AppConfig() - app_config.update_server_config(multi_dataset__dataroot=f"{FIXTURES_ROOT}") - app_config.write_config(configfile) - - command = ["python", check_config_script, configfile] - - # test failure mode (flask_secret_key not set) - env = os.environ.copy() - env.pop("CXG_SECRET_KEY", None) - with self.assertRaises(subprocess.CalledProcessError) as exception_context: - subprocess.check_output(command, env=env) - output = str(exception_context.exception.stdout, "utf-8") - self.assertTrue( - output.startswith( - "Error: Invalid type for attribute: app__flask_secret_key, expected type str, got NoneType" - ) - ) - self.assertEqual(exception_context.exception.returncode, 1) - - # test passing case - env = os.environ.copy() - env["CXG_SECRET_KEY"] = "secret" - output = subprocess.check_output(command, env=env) - output = str(output, "utf-8") - self.assertTrue(output.startswith("PASS")) diff --git a/client/__tests__/e2e/e2e.test.js b/client/__tests__/e2e/e2e.test.js index bd3e852a..d8a4b5e9 100644 --- a/client/__tests__/e2e/e2e.test.js +++ b/client/__tests__/e2e/e2e.test.js @@ -16,7 +16,6 @@ import { getTestId, goToPage, waitByID, - clickOnUntil, } from "./puppeteerUtils"; import { @@ -26,8 +25,6 @@ import { getAllCategoriesAndCounts, getCellSetCount, selectCategory, - login, - logout, } from "./cellxgeneActions"; const data = datasets[DATASET]; @@ -351,34 +348,4 @@ test("lasso moves after pan", async () => { expect(panCount).toBe(initialCount); }); - -const describeIfCalledByMakeFileTarget = - process.env.CXG_AUTH_TYPE?.toLowerCase() === "test" - ? describe - : describe.skip; - -describeIfCalledByMakeFileTarget("auth buttons", () => { - test("login then logout", async () => { - await goToPage(appUrlBase); - await clickOnUntil("log-in", async () => { - await page.waitForNavigation({ waitUntil: "networkidle0" }); - await waitByID("user-info"); - }); - await logout(); - }); -}); - -const conditionalDescribe = - process.env.TEST_AUTH_INTEGRATION === "true" ? describe : describe.skip; - -conditionalDescribe("AuthN Integration", () => { - it("logs in", async () => { - await login(); - }); - - it("logs out", async () => { - await login(); - await logout(); - }); -}); /* eslint-enable no-await-in-loop -- await in loop is needed to emulate sequential user actions */ diff --git a/setup.cfg b/setup.cfg index 5841d387..7913312c 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,4 +1,4 @@ [flake8] max-line-length = 120 ignore = E203, W503 -exclude = backend/common/fbs/NetEncoding/,.git,__pycache__,venv,backend/czi_hosted/venv,old,build,dist,backend/czi_hosted/eb/artifact.dir/ +exclude = backend/common/fbs/NetEncoding/,.git,__pycache__,venv,old,build,dist diff --git a/setup_hosted.py b/setup_hosted.py deleted file mode 100644 index d09b5eb5..00000000 --- a/setup_hosted.py +++ /dev/null @@ -1,43 +0,0 @@ -from setuptools import setup, find_packages - -with open("README.md", "rb") as fh: - long_description = fh.read().decode() - -with open("backend/czi_hosted/requirements.txt") as fh: - requirements = fh.read().splitlines() - -with open("backend/czi_hosted/requirements-prepare.txt") as fh: - requirements_prepare = fh.read().splitlines() - -setup( - name="cellxgene", - version="0.16.0", - packages=find_packages(), - url="https://github.com/chanzuckerberg/cellxgene", - license="MIT", - author="Chan Zuckerberg Initiative", - author_email="cellxgene@chanzuckerberg.com", - description="Web application for exploration of large scale scRNA-seq datasets", - long_description=long_description, - long_description_content_type="text/markdown", - install_requires=requirements, - include_package_data=True, - zip_safe=False, - classifiers=[ - "Framework :: Flask", - "Intended Audience :: Science/Research", - "License :: OSI Approved :: MIT License", - "Natural Language :: English", - "Operating System :: POSIX", - "Operating System :: Unix", - "Operating System :: MacOS :: MacOS X", - "Programming Language :: JavaScript", - "Programming Language :: Python :: 3", - "Programming Language :: Python :: 3.6", - "Programming Language :: Python :: 3.7", - "Programming Language :: Python :: 3 :: Only", - "Topic :: Scientific/Engineering :: Bio-Informatics", - ], - entry_points={"console_scripts": ["cellxgene = backend.czi_hosted.cli.cli:cli"]}, - extras_require=dict(prepare=requirements_prepare), -)

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