mirror of
https://github.com/chanzuckerberg/cellxgene.git
synced 2026-09-20 03:18:12 +08:00
5ec66c5b0e
* Improved fix for matrix cache handling. During the MatrixDataCacheItem acquire function there was a time when the write lock was released and the read lock was taken. During that time, the dataset could have been deleted, later result in the MatrixDataCacheManageri data adaptor returning None. The solution is to demote the writer lock to a reader lock instead of unlocking and relocking. Also, when a the cache needs to delete an entry, the delete is done outside the MatrixDataCacheManager lock. This operation only requires the write lock for the MatrixDataCacheItem. Fixes #1255
77 lines
1.5 KiB
Python
77 lines
1.5 KiB
Python
import yaml
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default_config = """
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# cellxgene configuration
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server:
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verbose: false
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debug: false
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host: "127.0.0.1"
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port : null
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scripts : []
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open_browser: false
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about_legal_tos: null
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about_legal_privacy: null
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force_https: false
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presentation:
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max_categories: 1000
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multi_dataset:
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dataroot: null
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# The index page when in multi-dataset mode:
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# false or null: this returns a 404 code
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# true: loads a test index page, which links to the datasets that are available in the dataroot
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# string/URL: redirect to this URL: flask.redirect(config.multi_dataset__index)
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index: false
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# A list of allowed matrix types. If an empty list, then all matrix types are allowed
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allowed_matrix_types: []
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matrix_cache:
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# The maximum number of datasets that may be opened at one time. The least recently used dataset
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# is evicted from the cache first.
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max_datasets: 5
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single_dataset:
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datapath: null
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obs_names: null
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var_names: null
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about: null
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title: null
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user_annotations:
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enable: true
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type: local_file_csv
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local_file_csv:
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directory: null
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file: null
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ontology:
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enable: false
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obo_location: null
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embeddings:
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names : []
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enable_reembedding: false
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diffexp:
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enable: true
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lfc_cutoff: 0.01
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adaptor:
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cxg_adaptor:
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tiledb_ctx:
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sm.tile_cache_size: 8589934592
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sm.num_reader_threads: 32
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vfs.s3.region: us-east-1
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anndata_adaptor:
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backed: false
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"""
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def get_default_config():
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return yaml.load(default_config, Loader=yaml.Loader)
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