bump version (#518 )

Cluster Occupancy (n dim cube) (#513 )
* create occupancy component * occupancy working * centering, width, flex spacing * add is-number * extend sort to cover string + int * proof of concept sorted occupancy * handle undefined occupancy entry, cleanup * only render occupancy when colorby is cat * cleanup unused vars * cleanup
2026-09-28 04:38:11 +08:00 · 2018-12-17 14:30:34 -05:00 · 2018-12-17 14:19:48 -05:00 · 2018-12-14 16:32:41 -08:00 · 2018-12-14 15:19:21 -08:00 · 2018-12-13 15:15:56 -08:00
35 changed files with 1003 additions and 881 deletions
@@ -1,5 +1,5 @@
 [bumpversion]
-current_version = 0.3.0
+current_version = 0.4.0

 [bumpversion:file:setup.py]
 search = version="{current_version}"
@@ -0,0 +1,5 @@
+bin
+client
+dist
+docs
+server
@@ -11,10 +11,11 @@ install:
  - ./bin/build-client
  - pip install -e .
  - pip install -r server/requirements-dev.txt
+  - docker build .
 script:
  - set -eo pipefail
-  - flake8 server/app/
-  - flake8 server/cli/
+  - flake8 server
+  - black --check
  - npm run --prefix client/ build
  - npm run --prefix client/ test
  - pytest -s server/test
@@ -0,0 +1,10 @@
+FROM ubuntu:bionic
+
+ENV LC_ALL=C.UTF-8
+ENV LANG=C.UTF-8
+
+RUN apt-get update && \
+    apt-get install -y build-essential libxml2-dev python3-dev python3-pip zlib1g-dev && \
+    pip3 install cellxgene
+
+ENTRYPOINT ["cellxgene"]
@@ -8,7 +8,9 @@

 ## getting started

-You'll need **python 3.6** and **Google Chrome**. The web UI is tested on OSX and Windows using Chrome, and the python CLI is tested on OSX and Ubuntu (via WSL/Windows). It should work on other platforms, but if you run into trouble let us know (see [help](#help-and-contact) below).
+You'll need **python 3.6** and **Google Chrome**. (*Warning*: Python 3.7 is **not** supported at this time)
+The web UI is tested on OSX and Windows using Chrome, and the python CLI is tested on OSX and Ubuntu (via WSL/Windows). It should work on other platforms, but if you run into trouble let us know (see [help](#help-and-contact) below).
+

 To install run

@@ -89,6 +91,12 @@ cellxgene prepare --help
 pip install cellxgene[louvain]
 ```

+If the aforementioned optional package installation fails, you can also install these packages directly:
+
+```
+pip install python-igraph louvain>=0.6
+```
+
 ## conda and virtual environments

 If you use conda and want to create a conda environment for `cellxgene` you can use the following commands
@@ -103,13 +111,28 @@ Or you can create a virtual environment by using

 ```
 ENV_NAME=cellxgene
-python3 -m venv ${ENV_NAME}
+python3.6 -m venv ${ENV_NAME}
 source ${ENV_NAME}/bin/activate
 pip install cellxgene
 ```

+## docker
+
+We have included a dockerfile to conveniently run cellxgene from docker. 
+
+1. Build the  image `docker build . -t cellxgene`
+2. Run the container and mount data `docker run -v "$PWD/example-dataset/:/data/" -p 5005:5005 cellxgene launch --host 0.0.0.0 data/pbmc3k.h5ad`
+    * You will need to use --host 0.0.0.0 to have the container listen to incoming requests from the browser
+
+
 ## FAQ

+<details>
+
+<summary> questions about data formatting </summary>
+  
+<hr>
+  
 > Someone sent me a directory of `10X-Genomics` data with a `mtx` file and I've never used `scanpy`, can I use `cellxgene`?

 Yep! This should only take a couple steps. We'll assume your data is in a folder called `data/` and you've successfully installed `cellxgene` with the `louvain` packages as described above. Just run
@@ -126,6 +149,8 @@ cellxgene launch data-processed.h5ad --layout=umap --open

 And your web browser should open with an interactive view of your data.

+<hr>
+
 > In my `prepare` command I received the following error `Warning: louvain module is not installed, no clusters will be calculated. To fix this please install cellxgene with the optional feature louvain enabled`

 Louvain clustering requires additional dependencies that are somewhat complex, so we don't include them by default. For now, you need to specify that you want these packages by using
@@ -134,6 +159,8 @@ Louvain clustering requires additional dependencies that are somewhat complex, s
 pip install cellxgene[louvain]
 ```

+<hr>
+
 > I ran `prepare` and I'm getting results that look unexpected

 You might want to try running one of the preprocessing recipes included with `scanpy` (read more about them [here](https://scanpy.readthedocs.io/en/latest/api/index.html#recipes)). You can specify this with the `--recipe` option, such as
@@ -144,21 +171,13 @@ cellxgene prepare data/ --output=data-processed.h5ad --recipe=zheng17

 It should be easy to run `prepare` then call `cellxgene launch` a few times with different settings to explore different behaviors. We may explore adding other preprocessing options in the future.

+<hr>
+
 > I have extra metadata that I want to add to my dataset

 Currently this is not supported directly, but you should be able to do this manually using `scanpy`. For example, this [notebook](https://github.com/falexwolf/fun-analyses/blob/master/tabula_muris/tabula_muris.ipynb) shows adding the contents of a `csv` file with metadata to an `anndata` object. For now, you could do this manually on your data in the same way and then save out the result before loading into `cellxgene`.

-> I tried to `pip install cellxgene` and got a weird error I don't understand
-
-This may happen, especially as we work out bugs in our installation process! Please create a new [Github issue](https://github.com/chanzuckerberg/cellxgene/issues), explain what you did, and include all the error messages you saw. It'd also be super helpful if you call `pip freeze` and include the full output alongside your issue.
-
-> How are you computing and sorting differential expression results?
-
-Currently we use a [Welch's _t_-test](https://en.wikipedia.org/wiki/Welch%27s_t-test) implementation including the same variance overestimation correction as used in `scanpy`. We sort the `tscore` to identify the top N genes, and then filter to remove any that fall below a cutoff log fold change value, which can help remove spurious test results. The default threshold is `0.01` and can be changed using the option `--diffexp-lfc-cutoff`. We can explore adding support for other test types in the future.
-
-> I'm following the developer instructions and get an error about "missing files and directories” when trying to build the client
-
-This is likely because you do not have node and npm installed, we recommend using [nvm](https://github.com/creationix/nvm) if you're new to using these tools.
+<hr>

 > What part of the anndata objects does cellxgene pull in for visualization?

@@ -166,12 +185,46 @@ This is likely because you do not have node and npm installed, we recommend usin
 - `.X` is used to display expression (histograms, scatterplot & colorscale) and to compute differential expression
 - `.obsm` is used for layout

+<hr>
+
 > When I start cellxgene, I get an error `Unexpected HTTP response 500, INTERNAL SERVER ERROR -- Out of range float values are not JSON compliant` in the web UI, or `Warning: JSON encoding failure - suggest trying --nan-to-num command line option` in the CLI. What can I do?

 At the moment, cellxgene is unable to transmit floating point NaN or Inifinty values to the web UI (due to a limitation on data serialization method in use). We expect to resolve this in a future release, but in the meantime, you can work around this issue by starting cellxgene with the `--nan-to-num` command line option, ie, `cellxgene launch data.h5ad --nan-to-num`.

 This option will convert all NaNs to zero, and all positive/negative infinities to the min/max of the data element within which the value was found (eg, +Infinity within an `obs` annotation will be converted to the maximum finite value in that annotation). This option will increase startup time, so we recommend only using it when the dataset contains NaN/Infinities.

+</details>
+
+<details>
+  
+<summary> questions about installing and building </summary>
+
+<hr>
+
+> I tried to `pip install cellxgene` and got a weird error I don't understand
+
+This may happen, especially as we work out bugs in our installation process! Please create a new [Github issue](https://github.com/chanzuckerberg/cellxgene/issues), explain what you did, and include all the error messages you saw. It'd also be super helpful if you call `pip freeze` and include the full output alongside your issue.
+
+<hr>
+
+> I'm following the developer instructions and get an error about "missing files and directories” when trying to build the client
+
+This is likely because you do not have node and npm installed, we recommend using [nvm](https://github.com/creationix/nvm) if you're new to using these tools.
+
+</details>
+
+<details>
+
+<summary> questions about algorithms </summary>
+
+<hr>
+
+> How are you computing and sorting differential expression results?
+
+Currently we use a [Welch's _t_-test](https://en.wikipedia.org/wiki/Welch%27s_t-test) implementation including the same variance overestimation correction as used in `scanpy`. We sort the `tscore` to identify the top N genes, and then filter to remove any that fall below a cutoff log fold change value, which can help remove spurious test results. The default threshold is `0.01` and can be changed using the option `--diffexp-lfc-cutoff`. We can explore adding support for other test types in the future.
+
+</details>
+
 ## developer guide

 This project has made a few key design choices
@@ -207,7 +260,7 @@ pip install -e .

 You can start the app while developing either by calling `cellxgene` or by calling `python -m server`. We recommend using the `--debug` flag to see more output, which you can include when reporting bugs.

-If you have any questions about developing or contributing, come hang out with us by joining the [CZI Science Slack](https://cziscience.slack.com/messages/CCTA8DF1T) and posting in the `#cellxgene-dev` channel.
+If you have any questions about developing or contributing, come hang out with us by joining the [CZI Science Slack](https://join-cellxgene-users.herokuapp.com/) and posting in the `#cellxgene-dev` channel.

 ## development roadmap

@@ -234,7 +287,7 @@ We are eager to explore integrations with other computational backends such as [

 ## help and contact

-Have questions, suggestions, or comments? You can come hang out with us by joining the [CZI Science Slack](https://cziscience.slack.com/messages/CCTA8DF1T) and posting in the `#cellxgene-users` channel. As mentioned above, please submit any feature requests or bugs as [Github issues](https://github.com/chanzuckerberg/cellxgene/issues). We'd love to hear from you!
+Have questions, suggestions, or comments? You can come hang out with us by joining the [CZI Science Slack](https://join-cellxgene-users.herokuapp.com/) and posting in the `#cellxgene-users` channel. As mentioned above, please submit any feature requests or bugs as [Github issues](https://github.com/chanzuckerberg/cellxgene/issues). We'd love to hear from you!

 ## reuse

@@ -1,6 +1,6 @@
 {
  "name": "cellxgene",
-  "version": "0.3.0",
+  "version": "0.4.0",
  "lockfileVersion": 1,
  "requires": true,
  "dependencies": {
@@ -5202,6 +5202,17 @@
        "randomatic": "^3.0.0",
        "repeat-element": "^1.1.2",
        "repeat-string": "^1.5.2"
+      },
+      "dependencies": {
+        "is-number": {
+          "version": "2.1.0",
+          "resolved": "https://registry.npmjs.org/is-number/-/is-number-2.1.0.tgz",
+          "integrity": "sha1-Afy7s5NGOlSPL0ZszhbezknbkI8=",
+          "dev": true,
+          "requires": {
+            "kind-of": "^3.0.2"
+          }
+        }
      }
    },
    "finalhandler": {
@@ -5401,8 +5412,7 @@
        "ansi-regex": {
          "version": "2.1.1",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "aproba": {
          "version": "1.2.0",
@@ -5423,14 +5433,12 @@
        "balanced-match": {
          "version": "1.0.0",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "brace-expansion": {
          "version": "1.1.11",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "balanced-match": "^1.0.0",
            "concat-map": "0.0.1"
@@ -5445,20 +5453,17 @@
        "code-point-at": {
          "version": "1.1.0",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "concat-map": {
          "version": "0.0.1",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "console-control-strings": {
          "version": "1.1.0",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "core-util-is": {
          "version": "1.0.2",
@@ -5575,8 +5580,7 @@
        "inherits": {
          "version": "2.0.3",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "ini": {
          "version": "1.3.5",
@@ -5588,7 +5592,6 @@
          "version": "1.0.0",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "number-is-nan": "^1.0.0"
          }
@@ -5603,7 +5606,6 @@
          "version": "3.0.4",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "brace-expansion": "^1.1.7"
          }
@@ -5611,14 +5613,12 @@
        "minimist": {
          "version": "0.0.8",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "minipass": {
          "version": "2.2.4",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "safe-buffer": "^5.1.1",
            "yallist": "^3.0.0"
@@ -5637,7 +5637,6 @@
          "version": "0.5.1",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "minimist": "0.0.8"
          }
@@ -5718,8 +5717,7 @@
        "number-is-nan": {
          "version": "1.0.1",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "object-assign": {
          "version": "4.1.1",
@@ -5731,7 +5729,6 @@
          "version": "1.4.0",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "wrappy": "1"
          }
@@ -5817,8 +5814,7 @@
        "safe-buffer": {
          "version": "5.1.1",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "safer-buffer": {
          "version": "2.1.2",
@@ -5854,7 +5850,6 @@
          "version": "1.0.2",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "code-point-at": "^1.0.0",
            "is-fullwidth-code-point": "^1.0.0",
@@ -5874,7 +5869,6 @@
          "version": "3.0.1",
          "bundled": true,
          "dev": true,
-          "optional": true,
          "requires": {
            "ansi-regex": "^2.0.0"
          }
@@ -5918,14 +5912,12 @@
        "wrappy": {
          "version": "1.0.2",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        },
        "yallist": {
          "version": "3.0.2",
          "bundled": true,
-          "dev": true,
-          "optional": true
+          "dev": true
        }
      }
    },
@@ -6776,13 +6768,9 @@
      "dev": true
    },
    "is-number": {
-      "version": "2.1.0",
-      "resolved": "https://registry.npmjs.org/is-number/-/is-number-2.1.0.tgz",
-      "integrity": "sha1-Afy7s5NGOlSPL0ZszhbezknbkI8=",
-      "dev": true,
-      "requires": {
-        "kind-of": "^3.0.2"
-      }
+      "version": "7.0.0",
+      "resolved": "https://registry.npmjs.org/is-number/-/is-number-7.0.0.tgz",
+      "integrity": "sha512-41Cifkg6e8TylSpdtTpeLVMqvSBEVzTttHvERD741+pnZ8ANv0004MRL43QKPDlK9cGvNp6NZWZUBlbGXYxxng=="
    },
    "is-obj": {
      "version": "1.0.1",
@@ -1,6 +1,6 @@
 {
  "name": "cellxgene",
-  "version": "0.3.0",
+  "version": "0.4.0",
  "license": "MIT",
  "description": "cellxgene is a web application for the interactive exploration of single cell sequence data.",
  "repository": "https://github.com/chanzuckerberg/cellxgene",
@@ -37,6 +37,7 @@
    "fuzzysort": "^1.1.4",
    "gl-mat4": "^1.1.4",
    "gl-matrix": "^2.7.1",
+    "is-number": "^7.0.0",
    "key-pressed": "0.0.1",
    "lodash": "^4.17.4",
    "memoize-one": "^4.0.0",
@@ -6,7 +6,7 @@ import { Button, Tooltip } from "@blueprintjs/core";

 import * as globals from "../../globals";
 import Value from "./value";
-import alphabeticallySortedValues from "./util";
+import sortedCategoryValues from "./util";

@connect(state => ({
  colorAccessor: state.controls.colorAccessor,
@@ -86,9 +86,10 @@ class Category extends React.Component {
    const { categoricalSelectionState, metadataField } = this.props;

    const cat = categoricalSelectionState[metadataField];
-    const optTuples = alphabeticallySortedValues([...cat.categoryIndices]);
+    const optTuples = sortedCategoryValues([...cat.categoryIndices]);
    return _.map(optTuples, (tuple, i) => (
      <Value
+        optTuples={optTuples}
        key={tuple[1]}
        metadataField={metadataField}
        categoryIndex={tuple[1]}
@@ -0,0 +1,73 @@
+// jshint esversion: 6
+import React from "react";
+import _ from "lodash";
+import { connect } from "react-redux";
+import * as d3 from "d3";
+
+@connect()
+class Occupancy extends React.Component {
+  render() {
+    const {
+      occupancy,
+      colorScale,
+      categoricalSelectionState,
+      colorAccessor,
+      schema
+    } = this.props;
+    const width = 100;
+    const height = 11;
+
+    const categories = _.filter(schema.annotations.obs, {
+      name: colorAccessor
+    })[0].categories;
+
+    const x = d3
+      .scaleLinear()
+      /* get all the keys d[1] as an array, then find the sum */
+      .domain([0, d3.sum(Array.from(occupancy, d => d[1]))])
+      .range([0, width]);
+
+    let currentOffset = 0;
+
+    const stacks = categoricalSelectionState[colorAccessor].categoryValues.map(
+      d => {
+        const o = occupancy.get(d);
+
+        const scaledValue = x(o);
+
+        const stackItem = {
+          key: d,
+          value: o || 0,
+          rectWidth: o ? scaledValue : 0,
+          offset: currentOffset,
+          fill: o ? colorScale(categories.indexOf(d)) : "rgb(255,255,255)"
+        };
+        currentOffset += o ? scaledValue : 0;
+        return stackItem;
+      }
+    );
+
+    return (
+      <svg
+        style={{
+          marginRight: 5,
+          width,
+          height
+        }}
+      >
+        {stacks.map(d => (
+          <rect
+            key={d.key}
+            width={d.rectWidth}
+            height={height}
+            x={d.offset}
+            title={d.metadataField}
+            fill={d.fill}
+          />
+        ))}
+      </svg>
+    );
+  }
+}
+
+export default Occupancy;
@@ -3,9 +3,33 @@
 // values is [ [optVal, optIdx], ...]
 // index is range array
 // return sorted index
-export default values =>
-  values.sort((a, b) => {
+
+import isNumber from "is-number";
+import _ from "lodash";
+
+const sortedCategoryValues = values => {
+  /* this sort could be memoized for perf */
+
+  const strings = [];
+  const ints = [];
+
+  _.forEach(values, v => {
+    if (isNumber(v[0])) {
+      ints.push(v);
+    } else {
+      strings.push(v);
+    }
+  });
+
+  strings.sort((a, b) => {
    const textA = String(a[0]).toUpperCase();
    const textB = String(b[0]).toUpperCase();
    return textA < textB ? -1 : textA > textB ? 1 : 0;
  });
+
+  ints.sort((a, b) => +a[0] - +b[0]);
+
+  return ints.concat(strings);
+};
+
+export default sortedCategoryValues;
@@ -2,12 +2,16 @@
 import { connect } from "react-redux";
 import React from "react";
 import _ from "lodash";
+import Occupancy from "./occupancy";
+import { countCategoryValues2D } from "../../util/stateManager/worldUtil";
+import * as globals from "../../globals";

@connect(state => ({
  categoricalSelectionState: state.controls.categoricalSelectionState,
  colorScale: state.controls.colorScale,
  colorAccessor: state.controls.colorAccessor,
-  schema: _.get(state.controls.world, "schema", null)
+  schema: _.get(state.controls.world, "schema", null),
+  world: state.controls.world
 }))
 class CategoryValue extends React.Component {
  toggleOff() {
@@ -36,7 +40,8 @@ class CategoryValue extends React.Component {
      colorAccessor,
      colorScale,
      i,
-      schema
+      schema,
+      world
    } = this.props;

    if (!categoricalSelectionState) return null;
@@ -50,15 +55,24 @@ class CategoryValue extends React.Component {
    ).valueOf();

    /* this is the color scale, so add swatches below */
-    const c = metadataField === colorAccessor;
+    const isColorBy = metadataField === colorAccessor;
    let categories = null;
+    let occupancy = null;

-    if (c && schema) {
+    if (isColorBy && schema) {
      categories = _.filter(schema.annotations.obs, {
        name: colorAccessor
      })[0].categories;
    }

+    if (colorAccessor && !isColorBy) {
+      occupancy = countCategoryValues2D(
+        metadataField,
+        colorAccessor,
+        world.obsAnnotations
+      );
+    }
+
    return (
      <div
        key={i}
@@ -72,7 +86,10 @@ class CategoryValue extends React.Component {
          style={{
            margin: 0,
            padding: 0,
-            userSelect: "none"
+            userSelect: "none",
+            width: globals.leftSidebarWidth - 130,
+            display: "flex",
+            justifyContent: "space-between"
          }}
        >
          <label className="bp3-control bp3-checkbox">
@@ -86,6 +103,18 @@ class CategoryValue extends React.Component {
            <span className="bp3-control-indicator" />
            {displayString}
          </label>
+          <span style={{ flexShrink: 0 }}>
+            {colorAccessor &&
+            !isColorBy &&
+            categoricalSelectionState[colorAccessor] ? (
+              <Occupancy
+                occupancy={occupancy.get(
+                  category.categoryValues[categoryIndex]
+                )}
+                {...this.props}
+              />
+            ) : null}
+          </span>
        </div>
        <span>
          <span>{count}</span>
@@ -95,7 +124,7 @@ class CategoryValue extends React.Component {
              width: 11,
              height: 11,
              backgroundColor:
-                c && categories
+                isColorBy && categories
                  ? colorScale(categories.indexOf(value))
                  : "inherit"
            }}
@@ -0,0 +1 @@
+theme: jekyll-theme-architect
@@ -0,0 +1,37 @@
+# cellxgene
+
+cellxgene is an interactive data explorer for single-cell transcriptomics data designed to handle large datasets (1 million cells or more) and integrate with your favorite analysis tools
+
+## getting started
+
+install the package
+> `> pip install cellxgene`
+
+preprocess the data for use with cellxgene (optional)
+> `> cellxgene --prepare dataset.h5ad -o processed.h5ad`
+
+launch the web app
+> `> cellxgene --launch processed.h5ad`
+
+## features
+
+
+
+### inspiration and collaboration
+
+We've been heavily inspired by several other related single-cell visualization projects:
+* [UCSC Cell Browswer](http://cells.ucsc.edu/)
+* [Cytoscape](http://www.cytoscape.org/)
+* [Xena](https://xena.ucsc.edu/)
+* [ASAP](https://asap.epfl.ch/)
+* [Gene Pattern](http://genepattern-notebook.org/)
+
+We were inspired by Mike Bostock and the [crossfilter](https://github.com/crossfilter) team for the design of our filtering implementation.
+
+We have been working closely with the [`scanpy`](https://github.com/theislab/scanpy) team to integrate with their awesome analysis tools. Special thanks to Alex Wolf, Fabian Theis, and the rest of the team for their help during development and for providing an example dataset.
+
+We are eager to explore integrations with other computational backends such as [`Seurat`](https://github.com/satijalab/seurat) or [`Bioconductor`](https://github.com/Bioconductor)
+
+### help and contact
+
+Have questions, suggestions, or comments? You can come hang out with us by joining the [CZI Science Slack](https://join-cziscience-slack.herokuapp.com/) and posting in the `#cellxgene-users` channel. As mentioned above, please submit any feature requests or bugs as [Github issues](https://github.com/chanzuckerberg/cellxgene/issues). We'd love to hear from you!
@@ -0,0 +1,35 @@
+## Creating PR
+1. Name [username]/branchname 
+    1. Branch name should be all lowercase
+    2. Words separated by “-”
+2. Code should address only one issue ideally, make a separate PR for each task
+3. Description 
+    1. Clear explanation of issues solved
+    2. Describe why and how, when appropriate
+    3. Call out specific areas you want extra attention in review (optional)
+    4. If your PR requires more than one reviewer tag those people in the description or comments and let them know that you specifically require them
+4. Ensure that the PR updates tests and documentation and adds tests where appropriate
+5. Use github’s issue keywords when PR is addressing an issue https://help.github.com/articles/closing-issues-using-keywords/
+6. Tags (add at beginning of title)
+    1. [EASY] - small non-controversial change, easy to review
+    2. [DO NOT MERGE] - PR is in progress, do not merge changes
+
+## Review
+1. Assign at least one reviewer to submitted PRs.   Reviewers should be selected based on expertise in areas affected by the PR (eg, web UI: Colin), and should include Comp Bio and PM as needed.
+2. Reviewers should approve or request changes (not just comment) and put general and line level comments where appropriate
+3. As a PR submitter respond to all comments (eg, comment, commit a change, etc)
+4. External PRs
+    1. For external PRs or PRs not from our core team, core team should assign a reviewer and make initial contact within 1 business day
+    2. Build code on local environment and run smoke tests 
+
+## Required to Merge
+1. Travis CI Build passing
+2. At least one reviewer approved
+    1. Exceptions: 
+        1. Release PRs where version is just bumped should not need review
+        2. Complex PRs which touch multiple parts of the codebase should have reviews from all relevant parties
+3. License and Security checks (SNYK) passing. If their server is down and you didn’t add any new external npm or python packages, merge is OK
+
+## Merging
+1. Use "squash and merge" option when merging
+2. If you resolved conflicts, wait until the build passes to merge
@@ -14,35 +14,40 @@ The release process should result in the following side-effects:
 - Tagged github release
 - Publication to PyPi

-## Process
+## Recipe

 Follow these steps to create a release.

 1.  Preparation:
-    - Define the release version number, using [semantic versioning](https://semver.org/)
-    - Write the release title and release notes and add to 
-    [release notes document](https://docs.google.com/document/d/1KnHwkYfhyWO5H8BDcMu7y3ogjvq5Yi4OwpmZ8DB6w0Y/edit)
+    - python3.6 environment, and a cellxgene clone
+    - install required tools: `pip install -r requirements-dev.txt`
+    - Define the release version number, using [semantic versioning](https://semver.org/),
+      and specifying all three digits (eg, 0.3.0)
+    - Write the release title and release notes and add to
+      [release notes document](https://docs.google.com/document/d/1KnHwkYfhyWO5H8BDcMu7y3ogjvq5Yi4OwpmZ8DB6w0Y/edit)
 2.  Create a release branch, eg, `release-version`
 3.  In the release branch:
-    - Run `bumpversion --config-file .bumpversion.cfg [major | minor | patch]`
+    - Run `bumpversion --config-file .bumpversion.cfg [major | minor | patch]`,
+      where you choose major/minor/patch depending on which part of the version
+      is being bumped (eg, 0.2.9->0.3 is minor).
    - Clean up existing environment using `bin/clean`
    - Build the JS asserts using `bin/build-client`
 4.  Commit and push the new branch
 5.  Create a PR for the release.
    - [optional] As needed, conduct PR review.
 6.  Merge to master
-7.  Create Github release using the version number and release notes 
-([instructions](https://help.github.com/articles/creating-releases/)).
+7.  Create Github release using the version number and release notes
+    ([instructions](https://help.github.com/articles/creating-releases/)).
    - Draft new release
    - Type version name matching release version number from (1)
    - Select `master` as release branch (ensure you merged the release PR)
    - Type title `Release {version num}`
    - [optional] Check pre-release if this release is not ready for production
    - Publish Release
-8.  Publish to pypi by performing the following steps (assumes you have `setuptools` and `twine` installed and that you 
-have registered for pypi and have write access to the cellxgene pypi package)
-    - Build the distribution by calling
-    `python setup.py sdist`
+8.  Publish to pypi by performing the following steps (assumes you have `setuptools`
+    and `twine` installed, that you have registered for pypi, and that you have
+    write access to the cellxgene pypi package):
+    - Build the distribution by calling `python setup.py sdist`
      inside the top-level directory
    - [optional] Upload the package to test pypi
      `twine upload --repository-url https://test.pypi.org/legacy/ dist/*`
@@ -2,11 +2,14 @@
 if __package__ is None:
    import sys
    from pathlib import Path
+
    PKG_PATH = Path(__file__).parent
    sys.path.insert(0, str(PKG_PATH.parent))
-    import server
+    import server # noqa F401
+
    __package__ = PKG_PATH.name

 # Main thing
-from .cli.cli import cli
+from .cli.cli import cli # noqa F402
+
 cli()
@@ -14,16 +14,14 @@ REACTIVE_LIMIT = 1_000_000

 app = Flask(__name__, static_folder="web/static")
 app.json_encoder = Float32JSONEncoder
-cache = Cache(app, config={"CACHE_TYPE": "simple", "CACHE_DEFAULT_TIMEOUT": 860000})
+cache = Cache(app, config={"CACHE_TYPE": "simple", "CACHE_DEFAULT_TIMEOUT": 860_000})
 Compress(app)
 CORS(app)

 # Config
 SECRET_KEY = os.environ.get("CXG_SECRET_KEY", default="SparkleAndShine")

-app.config.update(
-    SECRET_KEY=SECRET_KEY,
-)
+app.config.update(SECRET_KEY=SECRET_KEY)

 # Application Data
 data = None
@@ -36,7 +34,13 @@ docs.append(resources.get_swagger_doc())
 app.register_blueprint(webapp.bp)
 app.register_blueprint(resources.blueprint)
 app.register_blueprint(
-    get_swagger_blueprint(docs, "/api/swagger", produces=["application/json"], title="cellxgene rest api",
-                          description="An API connecting ExpressionMatrix2 clustering algorithm to cellxgene"))
+    get_swagger_blueprint(
+        docs,
+        "/api/swagger",
+        produces=["application/json"],
+        title="cellxgene rest api",
+        description="An API connecting ExpressionMatrix2 clustering algorithm to cellxgene",
+    )
+)

 app.add_url_rule("/", endpoint="index")
@@ -11,7 +11,6 @@ Sort order for methods


 class CXGDriver(metaclass=ABCMeta):
-
    def __init__(self, data, args):
        self.data = self._load_data(data)
        self.layout_method = args["layout"]
@@ -24,11 +23,8 @@ class CXGDriver(metaclass=ABCMeta):
    def features(self):
        features = {
            "cluster": {"available": False},
-            "layout": {
-                "obs": {"available": False},
-                "var": {"available": False},
-            },
-            "diffexp": {"available": False}
+            "layout": {"obs": {"available": False}, "var": {"available": False}},
+            "diffexp": {"available": False},
        }
        # TODO - Interactive limit should be generated from the actual available methods see GH issue #94
        if self.layout_method:
@@ -2,9 +2,7 @@ from http import HTTPStatus
 import pkg_resources
 import warnings

-from flask import (
-    Blueprint, current_app, jsonify, make_response, request
-)
+from flask import Blueprint, current_app, jsonify, make_response, request
 from flask_restful_swagger_2 import Api, swagger, Resource
 from werkzeug.datastructures import ImmutableMultiDict

@@ -23,83 +21,78 @@ Sort order for routes


 class SchemaAPI(Resource):
-    @swagger.doc({
-        "summary": "get schema for dataframe and annotations",
-        "tags": ["initialize"],
-        "parameters": [],
-        "responses": {
-            "200": {
-                "description": "schema",
-                "examples": {
-                    "application/json": {
-                        "schema": {
-                            "dataframe": {
-                                "nObs": 383,
-                                "nVar": 19944,
-                                "type": "float32"
-                            },
-                            "annotations": {
-                                "obs": [
-                                    {"name": "name", "type": "string"},
-                                    {"name": "tissue_type", "type": "string"},
-                                    {"name": "num_reads", "type": "int32"},
-                                    {"name": "sample_name", "type": "string"},
-                                    {
-                                        "name": "clusters",
-                                        "type": "categorical",
-                                        "categories": [99, 1, "unknown cluster"]
-                                    },
-                                    {"name": "QScore", "type": "float32"}
-                                ],
-                                "var": [
-                                    {"name": "name", "type": "string"},
-                                    {"name": "gene", "type": "string"}
-                                ]
+    @swagger.doc(
+        {
+            "summary": "get schema for dataframe and annotations",
+            "tags": ["initialize"],
+            "parameters": [],
+            "responses": {
+                "200": {
+                    "description": "schema",
+                    "examples": {
+                        "application/json": {
+                            "schema": {
+                                "dataframe": {"nObs": 383, "nVar": 19944, "type": "float32"},
+                                "annotations": {
+                                    "obs": [
+                                        {"name": "name", "type": "string"},
+                                        {"name": "tissue_type", "type": "string"},
+                                        {"name": "num_reads", "type": "int32"},
+                                        {"name": "sample_name", "type": "string"},
+                                        {
+                                            "name": "clusters",
+                                            "type": "categorical",
+                                            "categories": [99, 1, "unknown cluster"],
+                                        },
+                                        {"name": "QScore", "type": "float32"},
+                                    ],
+                                    "var": [{"name": "name", "type": "string"}, {"name": "gene", "type": "string"}],
+                                },
                            }
                        }
-                    }
+                    },
                }
-            }
+            },
        }
-
-    })
+    )
    def get(self):
        return make_response(jsonify({"schema": current_app.data.schema}), HTTPStatus.OK)


 class ConfigAPI(Resource):
-    @swagger.doc({
-        "summary": "Configuration information to assist in front-end adaptation"
-                   " to underlying engine, available functionality, interactive time limits, etc",
-        "tags": ["initialize"],
-        "parameters": [],
-        "responses": {
-            "200": {
-                "description": "schema",
-                "examples": {
-                    "application/json": {
-                        "config": {
-                            "features": [
-                                {"method": "POST", "path": "/cluster/", "available": False},
-                                {
-                                    "method": "POST",
-                                    "path": "/layout/obs",
-                                    "available": True,
-                                    "interactiveLimit": 10000
+    @swagger.doc(
+        {
+            "summary": "Configuration information to assist in front-end adaptation"
+            " to underlying engine, available functionality, interactive time limits, etc",
+            "tags": ["initialize"],
+            "parameters": [],
+            "responses": {
+                "200": {
+                    "description": "schema",
+                    "examples": {
+                        "application/json": {
+                            "config": {
+                                "features": [
+                                    {"method": "POST", "path": "/cluster/", "available": False},
+                                    {
+                                        "method": "POST",
+                                        "path": "/layout/obs",
+                                        "available": True,
+                                        "interactiveLimit": 10000,
+                                    },
+                                    {"method": "POST", "path": "/layout/var", "available": False},
+                                ],
+                                "displayNames": {
+                                    "engine": "ScanPy version 1.33",
+                                    "dataset": "/home/joe/mouse/blorth.csv",
                                },
-                                {"method": "POST", "path": "/layout/var", "available": False}
-
-                            ],
-                            "displayNames": {
-                                "engine": "ScanPy version 1.33",
-                                "dataset": "/home/joe/mouse/blorth.csv"
-                            },
+                            }
                        }
-                    }
+                    },
                }
-            }
+            },
        }
-    })
+    )
    def get(self):
        config = {
            "config": {
@@ -111,50 +104,48 @@ class ConfigAPI(Resource):
                ],
                "displayNames": {
                    "engine": f"cellxgene Scanpy engine version {pkg_resources.get_distribution('cellxgene').version}",
-                    "dataset": current_app.config["DATASET_TITLE"]
+                    "dataset": current_app.config["DATASET_TITLE"],
                },
-                "parameters": {
-                    "max_category_items": current_app.data.max_category_items
-                }
+                "parameters": {"max_category_items": current_app.data.max_category_items},
            }
        }
        return make_response(jsonify(config), HTTPStatus.OK)


 class AnnotationsObsAPI(Resource):
-    @swagger.doc({
-        "summary": "Fetch annotations (metadata) for all observations.",
-        "tags": ["annotations"],
-        "parameters": [{
-            "in": "query",
-            "name": "annotation-name",
-            "type": "string",
-            "description": "list of 1 or more annotation names"
-        }],
-        "responses": {
-            "200": {
-                "description": "annotations",
-                "examples": {
-                    "application/json": {
-                        "names": [
-                            "tissue_type", "sex", "num_reads", "clusters"
-                        ],
-                        "data": [
-                            [0, "lung", "F", 39844, 99],
-                            [1, "heart", "M", 83, 1],
-                            [49, "spleen", None, 2, "unknown cluster"],
-
-                        ]
-                    }
-
+    @swagger.doc(
+        {
+            "summary": "Fetch annotations (metadata) for all observations.",
+            "tags": ["annotations"],
+            "parameters": [
+                {
+                    "in": "query",
+                    "name": "annotation-name",
+                    "type": "string",
+                    "description": "list of 1 or more annotation names",
                }
+            ],
+            "responses": {
+                "200": {
+                    "description": "annotations",
+                    "examples": {
+                        "application/json": {
+                            "names": ["tissue_type", "sex", "num_reads", "clusters"],
+                            "data": [
+                                [0, "lung", "F", 39844, 99],
+                                [1, "heart", "M", 83, 1],
+                                [49, "spleen", None, 2, "unknown cluster"],
+                            ],
+                        }
+                    },
+                },
+                "400": {
+                    "description": "one or more of the annotation-name identifiers were not associated with an "
+                    "annotation name"
+                },
            },
-            "400": {
-                "description": "one or more of the annotation-name identifiers were not associated with an "
-                               "annotation name"
-            }
        }
-    })
+    )
    def get(self):
        fields = request.args.getlist("annotation-name", None)
        try:
@@ -168,47 +159,40 @@ class AnnotationsObsAPI(Resource):
            warnings.warn(JSON_NaN_to_num_warning_msg)
            return make_response(str(e), HTTPStatus.INTERNAL_SERVER_ERROR)

-    @swagger.doc({
-        "summary": "Fetch annotations (metadata) for filtered subset of observations.",
-        "tags": ["annotations"],
-        "parameters": [
-            {
-                "in": "query",
-                "name": "annotation-name",
-                "type": "string",
-                "description": "list of 1 or more annotation names"
+    @swagger.doc(
+        {
+            "summary": "Fetch annotations (metadata) for filtered subset of observations.",
+            "tags": ["annotations"],
+            "parameters": [
+                {
+                    "in": "query",
+                    "name": "annotation-name",
+                    "type": "string",
+                    "description": "list of 1 or more annotation names",
+                },
+                {"name": "filter", "description": "Complex Filter", "in": "body", "schema": FilterModel},
+            ],
+            "responses": {
+                "200": {
+                    "description": "annotations",
+                    "examples": {
+                        "application/json": {
+                            "names": ["tissue_type", "sex", "num_reads", "clusters"],
+                            "data": [
+                                [0, "lung", "F", 39844, 99],
+                                [1, "heart", "M", 83, 1],
+                                [49, "spleen", None, 2, "unknown cluster"],
+                            ],
+                        }
+                    },
+                },
+                "400": {
+                    "description": "malformed filter or one or more of the annotation-name identifiers were"
+                    "not associated with an annotation name"
+                },
            },
-            {
-                "name": "filter",
-                "description": "Complex Filter",
-                "in": "body",
-                "schema": FilterModel
-            }
-        ],
-        "responses": {
-            "200": {
-                "description": "annotations",
-                "examples": {
-                    "application/json": {
-                        "names": [
-                            "tissue_type", "sex", "num_reads", "clusters"
-                        ],
-                        "data": [
-                            [0, "lung", "F", 39844, 99],
-                            [1, "heart", "M", 83, 1],
-                            [49, "spleen", None, 2, "unknown cluster"],
-
-                        ]
-                    }
-
-                }
-            },
-            "400": {
-                "description": "malformed filter or one or more of the annotation-name identifiers were"
-                               "not associated with an annotation name"
-            }
        }
-    })
+    )
    def put(self):
        fields = request.args.getlist("annotation-name", None)
        try:
@@ -226,38 +210,35 @@ class AnnotationsObsAPI(Resource):


 class AnnotationsVarAPI(Resource):
-    @swagger.doc({
-        "summary": "Fetch annotations (metadata) for all variables.",
-        "tags": ["annotations"],
-        "parameters": [{
-            "in": "query",
-            "name": "annotation-name",
-            "type": "string",
-            "description": "list of 1 or more annotation names"
-        }],
-        "responses": {
-            "200": {
-                "description": "annotations",
-                "examples": {
-                    "application/json": {
-                        "names": [
-                            "name", "category"
-                        ],
-                        "data": [
-                            [0, "ATAD3C", 1],
-                            [1, "RER1", None],
-                            [49, "S100B", 6]
-                        ]
-                    }
-
+    @swagger.doc(
+        {
+            "summary": "Fetch annotations (metadata) for all variables.",
+            "tags": ["annotations"],
+            "parameters": [
+                {
+                    "in": "query",
+                    "name": "annotation-name",
+                    "type": "string",
+                    "description": "list of 1 or more annotation names",
                }
+            ],
+            "responses": {
+                "200": {
+                    "description": "annotations",
+                    "examples": {
+                        "application/json": {
+                            "names": ["name", "category"],
+                            "data": [[0, "ATAD3C", 1], [1, "RER1", None], [49, "S100B", 6]],
+                        }
+                    },
+                },
+                "400": {
+                    "description": "one or more of the annotation-name identifiers were not associated with an"
+                    " annotation name"
+                },
            },
-            "400": {
-                "description": "one or more of the annotation-name identifiers were not associated with an"
-                               " annotation name"
-            }
        }
-    })
+    )
    def get(self):
        fields = request.args.getlist("annotation-name", None)
        try:
@@ -271,45 +252,36 @@ class AnnotationsVarAPI(Resource):
            warnings.warn(JSON_NaN_to_num_warning_msg)
            return make_response(str(e), HTTPStatus.INTERNAL_SERVER_ERROR)

-    @swagger.doc({
-        "summary": "Fetch annotations (metadata) for filtered subset of variables.",
-        "tags": ["annotations"],
-        "parameters": [
-            {
-                "in": "query",
-                "name": "annotation-name",
-                "type": "string",
-                "description": "list of 1 or more annotation names"
+    @swagger.doc(
+        {
+            "summary": "Fetch annotations (metadata) for filtered subset of variables.",
+            "tags": ["annotations"],
+            "parameters": [
+                {
+                    "in": "query",
+                    "name": "annotation-name",
+                    "type": "string",
+                    "description": "list of 1 or more annotation names",
+                },
+                {"name": "filter", "description": "Complex Filter", "in": "body", "schema": FilterModel},
+            ],
+            "responses": {
+                "200": {
+                    "description": "annotations",
+                    "examples": {
+                        "application/json": {
+                            "names": ["name", "category"],
+                            "data": [[0, "ATAD3C", 1], [1, "RER1", None], [49, "S100B", 6]],
+                        }
+                    },
+                },
+                "400": {
+                    "description": "malformed filter or one or more of the annotation-name identifiers were"
+                    "not associated with an annotation name"
+                },
            },
-            {
-                "name": "filter",
-                "description": "Complex Filter",
-                "in": "body",
-                "schema": FilterModel
-            }
-        ],
-        "responses": {
-            "200": {
-                "description": "annotations",
-                "examples": {
-                    "application/json": {
-                        "names": [
-                            "name", "category"
-                        ],
-                        "data": [
-                            [0, "ATAD3C", 1],
-                            [1, "RER1", None],
-                            [49, "S100B", 6]
-                        ]
-                    }
-                }
-            },
-            "400": {
-                "description": "malformed filter or one or more of the annotation-name identifiers were"
-                               "not associated with an annotation name"
-            }
        }
-    })
+    )
    def put(self):
        fields = request.args.getlist("annotation-name", None)
        try:
@@ -327,57 +299,39 @@ class AnnotationsVarAPI(Resource):


 class DataObsAPI(Resource):
-    @swagger.doc({
-        "summary": "Get data (expression values) from the dataframe.",
-        "tags": ["data"],
-        "parameters": [
-            {
-                "in": "query",
-                "name": "filter",
-                "type": "string",
-                "description": "axis:key:value"
-            },
-            {
-                "in": "query",
-                "name": "accept-type",
-                "type": "string",
-                "description": "MIME type"
-            },
-        ],
-        "responses": {
-            "200": {
-                "description": "expression",
-                "examples": {
-                    "application/json": {
-                        "var": [0, 20000],
-                        "obs": [
-                            [1, 39483, 3902, 203, 0, 0, 28]
-                        ]
-                    }
-                }
-            },
-            "400": {
-                "description": "Malformed filter"
-            },
-            "406": {
-                "description": "Unacceptable MIME type"
+    @swagger.doc(
+        {
+            "summary": "Get data (expression values) from the dataframe.",
+            "tags": ["data"],
+            "parameters": [
+                {"in": "query", "name": "filter", "type": "string", "description": "axis:key:value"},
+                {"in": "query", "name": "accept-type", "type": "string", "description": "MIME type"},
+            ],
+            "responses": {
+                "200": {
+                    "description": "expression",
+                    "examples": {"application/json": {"var": [0, 20000], "obs": [[1, 39483, 3902, 203, 0, 0, 28]]}},
+                },
+                "400": {"description": "Malformed filter"},
+                "406": {"description": "Unacceptable MIME type"},
            },
        }
-    })
+    )
    def get(self):
        accept_type = request.args.get("accept-type", None)
        # request.args is immutable
        args = request.args.copy()
        args.pop("accept-type", None)
        try:
-            filter_ = parse_filter(ImmutableMultiDict(args), current_app.data.schema['annotations'])
+            filter_ = parse_filter(ImmutableMultiDict(args), current_app.data.schema["annotations"])
        except QueryStringError as e:
            return make_response(e.message, HTTPStatus.BAD_REQUEST)
        # TODO support CSV
        try:
            # TODO store mime_type when more than one is supported
-            get_mime_type(acceptable_types=["application/json"], query_param=accept_type,
-                          header=request.accept_mimetypes)
+            get_mime_type(
+                acceptable_types=["application/json"], query_param=accept_type, header=request.accept_mimetypes
+            )
        except MimeTypeError as e:
            return make_response(e.message, HTTPStatus.NOT_ACCEPTABLE)
        try:
@@ -389,37 +343,21 @@ class DataObsAPI(Resource):
            warnings.warn(JSON_NaN_to_num_warning_msg)
            return make_response(str(e), HTTPStatus.INTERNAL_SERVER_ERROR)

-    @swagger.doc({
-        "summary": "Get data (expression values) from the dataframe.",
-        "tags": ["data"],
-        "parameters": [
-            {
-                'name': 'filter',
-                'description': 'Complex Filter',
-                'in': 'body',
-                'schema': FilterModel
-            }
-        ],
-        "responses": {
-            "200": {
-                "description": "expression",
-                "examples": {
-                    "application/json": {
-                        "var": [0, 20000],
-                        "obs": [
-                            [1, 39483, 3902, 203, 0, 0, 28]
-                        ]
-                    }
-                }
-            },
-            "400": {
-                "description": "Malformed filter"
-            },
-            "406": {
-                "description": "Unacceptable MIME type"
+    @swagger.doc(
+        {
+            "summary": "Get data (expression values) from the dataframe.",
+            "tags": ["data"],
+            "parameters": [{"name": "filter", "description": "Complex Filter", "in": "body", "schema": FilterModel}],
+            "responses": {
+                "200": {
+                    "description": "expression",
+                    "examples": {"application/json": {"var": [0, 20000], "obs": [[1, 39483, 3902, 203, 0, 0, 28]]}},
+                },
+                "400": {"description": "Malformed filter"},
+                "406": {"description": "Unacceptable MIME type"},
            },
        }
-    })
+    )
    def put(self):
        if not request.accept_mimetypes.best_match(["application/json", "text/csv"]):
            return make_response(f"Unsupported MIME type '{request.accept_mimetypes}'", HTTPStatus.NOT_ACCEPTABLE)
@@ -428,8 +366,9 @@ class DataObsAPI(Resource):
        except MimeTypeError as e:
            return make_response(e.message, HTTPStatus.NOT_ACCEPTABLE)
        try:
-            return make_response((jsonify(current_app.data.data_frame(request.get_json()["filter"], axis=Axis.OBS))),
-                                 HTTPStatus.OK)
+            return make_response(
+                (jsonify(current_app.data.data_frame(request.get_json()["filter"], axis=Axis.OBS))), HTTPStatus.OK
+            )
        except FilterError as e:
            return make_response(e.message, HTTPStatus.BAD_REQUEST)
        except ValueError as e:
@@ -439,55 +378,37 @@ class DataObsAPI(Resource):


 class DataVarAPI(Resource):
-    @swagger.doc({
-        "summary": "Get data (expression values) from the dataframe.",
-        "tags": ["data"],
-        "parameters": [
-            {
-                "in": "query",
-                "name": "filter",
-                "type": "string",
-                "description": "axis:key:value"
-            },
-            {
-                "in": "query",
-                "name": "accept-type",
-                "type": "string",
-                "description": "MIME type"
-            },
-        ],
-        "responses": {
-            "200": {
-                "description": "expression",
-                "examples": {
-                    "application/json": {
-                        "obs": [0, 20000],
-                        "var": [
-                            [1, 39483, 3902, 203, 0, 0, 28]
-                        ]
-                    }
-                }
-            },
-            "400": {
-                "description": "Malformed filter"
-            },
-            "406": {
-                "description": "Unacceptable MIME type"
+    @swagger.doc(
+        {
+            "summary": "Get data (expression values) from the dataframe.",
+            "tags": ["data"],
+            "parameters": [
+                {"in": "query", "name": "filter", "type": "string", "description": "axis:key:value"},
+                {"in": "query", "name": "accept-type", "type": "string", "description": "MIME type"},
+            ],
+            "responses": {
+                "200": {
+                    "description": "expression",
+                    "examples": {"application/json": {"obs": [0, 20000], "var": [[1, 39483, 3902, 203, 0, 0, 28]]}},
+                },
+                "400": {"description": "Malformed filter"},
+                "406": {"description": "Unacceptable MIME type"},
            },
        }
-    })
+    )
    def get(self):
        accept_type = request.args.get("accept-type", None)
        # request.args is immutable
        args = request.args.copy()
        args.pop("accept-type", None)
        try:
-            filter_ = parse_filter(ImmutableMultiDict(args), current_app.data.schema['annotations'])
+            filter_ = parse_filter(ImmutableMultiDict(args), current_app.data.schema["annotations"])
        except QueryStringError as e:
            return make_response(e.message, HTTPStatus.BAD_REQUEST)
        try:
-            get_mime_type(acceptable_types=["application/json"], query_param=accept_type,
-                          header=request.accept_mimetypes)
+            get_mime_type(
+                acceptable_types=["application/json"], query_param=accept_type, header=request.accept_mimetypes
+            )
        except MimeTypeError as e:
            return make_response(e.message, HTTPStatus.NOT_ACCEPTABLE)
        try:
@@ -499,37 +420,21 @@ class DataVarAPI(Resource):
            warnings.warn(JSON_NaN_to_num_warning_msg)
            return make_response(str(e), HTTPStatus.INTERNAL_SERVER_ERROR)

-    @swagger.doc({
-        "summary": "Get data (expression values) from the dataframe.",
-        "tags": ["data"],
-        "parameters": [
-            {
-                'name': 'filter',
-                'description': 'Complex Filter',
-                'in': 'body',
-                'schema': FilterModel
-            }
-        ],
-        "responses": {
-            "200": {
-                "description": "expression",
-                "examples": {
-                    "application/json": {
-                        "obs": [0, 20000],
-                        "var": [
-                            [1, 39483, 3902, 203, 0, 0, 28]
-                        ]
-                    }
-                }
-            },
-            "400": {
-                "description": "Malformed filter"
-            },
-            "406": {
-                "description": "Unacceptable MIME type"
+    @swagger.doc(
+        {
+            "summary": "Get data (expression values) from the dataframe.",
+            "tags": ["data"],
+            "parameters": [{"name": "filter", "description": "Complex Filter", "in": "body", "schema": FilterModel}],
+            "responses": {
+                "200": {
+                    "description": "expression",
+                    "examples": {"application/json": {"obs": [0, 20000], "var": [[1, 39483, 3902, 203, 0, 0, 28]]}},
+                },
+                "400": {"description": "Malformed filter"},
+                "406": {"description": "Unacceptable MIME type"},
            },
        }
-    })
+    )
    def put(self):
        if not request.accept_mimetypes.best_match(["application/json", "text/csv"]):
            return make_response(f"Unsupported MIME type '{request.accept_mimetypes}'", HTTPStatus.NOT_ACCEPTABLE)
@@ -539,8 +444,9 @@ class DataVarAPI(Resource):
        except MimeTypeError as e:
            return make_response(e.message, HTTPStatus.NOT_ACCEPTABLE)
        try:
-            return make_response((jsonify(current_app.data.data_frame(request.get_json()["filter"], axis=Axis.VAR))),
-                                 HTTPStatus.OK)
+            return make_response(
+                (jsonify(current_app.data.data_frame(request.get_json()["filter"], axis=Axis.VAR))), HTTPStatus.OK
+            )
        except FilterError as e:
            return make_response(e.message, HTTPStatus.BAD_REQUEST)
        except ValueError as e:
@@ -550,67 +456,64 @@ class DataVarAPI(Resource):


 class DiffExpObsAPI(Resource):
-    @swagger.doc({
-        "summary": "Generate differential expression (DE) statistics for two specified subsets of data, "
-                   "as indicated by the two provided observation complex filters",
-        "tags": ["diffexp"],
-        # TODO sort out params
-        # "parameters": [
-        #     # {
-        #     #     "in": "body",
-        #     #     "name": "mode",
-        #     #     "type": "string",
-        #     #     "required": True,
-        #     #     "description": "topN or varFilter"
-        #     # },
-        #     {
-        #         "in": "query",
-        #         "name": "count",
-        #         "type": "int32",
-        #         "description": "TopN mode: how many vars to return"
-        #     },
-        #     {
-        #         "in": "body",
-        #         "name": "varFilter",
-        #         "schema": FilterModel,
-        #         "description": "varFilter: Complex filter, only var for which vars to return"
-        #     },
-        #     {
-        #         "in": "body",
-        #         "name": "set1",
-        #         "schema": FilterModel,
-        #         "required": True,
-        #         "description": "Complex filter, only obs - observations in set1"
-        #     },
-        #     {
-        #         "in": "body",
-        #         "name": "set2",
-        #         "schema": FilterModel,
-        #         "description": "Complex filter, only obs - observations in set2. If not included, inverse of set1."
-        #     },
-        # ],
-        "responses": {
-            "200": {
-                "description": "Statistics are encoded as an array of arrays, with fields ordered as: "
-                               "varIndex, logfoldchange,  pVal, pValAdj",
-                "examples": {
-                    "application/json": [
-                        [328, -2.569489, 2.655706e-63, 3.642036e-57],
-                        [1250, -2.569489, 2.655706e-63, 3.642036e-57],
-                    ]
-                }
+    @swagger.doc(
+        {
+            "summary": "Generate differential expression (DE) statistics for two specified subsets of data, "
+            "as indicated by the two provided observation complex filters",
+            "tags": ["diffexp"],
+            # TODO sort out params
+            # "parameters": [
+            #     # {
+            #     #     "in": "body",
+            #     #     "name": "mode",
+            #     #     "type": "string",
+            #     #     "required": True,
+            #     #     "description": "topN or varFilter"
+            #     # },
+            #     {
+            #         "in": "query",
+            #         "name": "count",
+            #         "type": "int32",
+            #         "description": "TopN mode: how many vars to return"
+            #     },
+            #     {
+            #         "in": "body",
+            #         "name": "varFilter",
+            #         "schema": FilterModel,
+            #         "description": "varFilter: Complex filter, only var for which vars to return"
+            #     },
+            #     {
+            #         "in": "body",
+            #         "name": "set1",
+            #         "schema": FilterModel,
+            #         "required": True,
+            #         "description": "Complex filter, only obs - observations in set1"
+            #     },
+            #     {
+            #         "in": "body",
+            #         "name": "set2",
+            #         "schema": FilterModel,
+            #         "description": "Complex filter, only obs - observations in set2.
+            # If not included, inverse of set1."
+            #     },
+            # ],
+            "responses": {
+                "200": {
+                    "description": "Statistics are encoded as an array of arrays, with fields ordered as: "
+                    "varIndex, logfoldchange,  pVal, pValAdj",
+                    "examples": {
+                        "application/json": [
+                            [328, -2.569_489, 2.655_706e-63, 3.642_036e-57],
+                            [1250, -2.569_489, 2.655_706e-63, 3.642_036e-57],
+                        ]
+                    },
+                },
+                "400": {"description": "malformed filter"},
+                "403": {"description": "non-interactive request"},
+                "501": {"description": "diffexp is not implemented"},
            },
-            "400": {
-                "description": "malformed filter"
-            },
-            "403": {
-                "description": "non-interactive request"
-            },
-            "501": {
-                "description": "diffexp is not implemented"
-            }
        }
-    })
+    )
    def post(self):
        args = request.get_json()
        # confirm mode is present and legal
@@ -645,8 +548,9 @@ class DiffExpObsAPI(Resource):
        # mode=topN
        count = args.get("count", None)
        try:
-            diffexp = current_app.data.diffexp_topN(set1_filter, set2_filter, count,
-                                                    current_app.data.features["diffexp"]["interactiveLimit"])
+            diffexp = current_app.data.diffexp_topN(
+                set1_filter, set2_filter, count, current_app.data.features["diffexp"]["interactiveLimit"]
+            )
        except (ValueError, FilterError) as e:
            return make_response(e.message, HTTPStatus.BAD_REQUEST)
        except InteractiveError:
@@ -660,30 +564,27 @@ class DiffExpObsAPI(Resource):


 class LayoutObsAPI(Resource):
-    @swagger.doc({
-        "summary": "Get the default layout for all observations.",
-        "tags": ["layout"],
-        "parameters": [],
-        "responses": {
-            "200": {
-                "description": "layout",
-                "examples": {
-                    "application/json": {
-                        "layout": {
-                            "ndims": 2,
-                            "coordinates": [
-                                [0, 0.284483, 0.983744],
-                                [1, 0.038844, 0.739444]
-                            ]
+    @swagger.doc(
+        {
+            "summary": "Get the default layout for all observations.",
+            "tags": ["layout"],
+            "parameters": [],
+            "responses": {
+                "200": {
+                    "description": "layout",
+                    "examples": {
+                        "application/json": {
+                            "layout": {
+                                "ndims": 2,
+                                "coordinates": [[0, 0.284_483, 0.983_744], [1, 0.038_844, 0.739_444]],
+                            }
                        }
-                    }
-                }
+                    },
+                },
+                "400": {"description": "Data preparation error"},
            },
-            "400": {
-                "description": "Data preparation error"
-            }
        }
-    })
+    )
    def get(self):
        try:
            layout = current_app.data.layout({})
@@ -1,4 +1,3 @@
-
 import numpy as np
 from scipy import sparse, stats

@@ -64,19 +63,19 @@ def diffexp_ttest(adata, maskA, maskB, top_n=8, diffexp_lfc_cutoff=0.01):
    sum_vn = vnA + vnB

    # degrees of freedom for Welch's t-test
-    with np.errstate(divide='ignore', invalid='ignore'):
-        dof = sum_vn**2 / (vnA**2 / (nA - 1) + vnB**2 / (nB - 1))
+    with np.errstate(divide="ignore", invalid="ignore"):
+        dof = sum_vn ** 2 / (vnA ** 2 / (nA - 1) + vnB ** 2 / (nB - 1))
    dof[np.isnan(dof)] = 1

    # Welch's t-test score calculation
-    with np.errstate(divide='ignore', invalid='ignore'):
+    with np.errstate(divide="ignore", invalid="ignore"):
        tscores = (meanA - meanB) / np.sqrt(sum_vn)
    tscores[np.isnan(tscores)] = 0

    # p-value
    pvals = stats.t.sf(np.abs(tscores), dof) * 2
    pvals_adj = pvals * adata._X.shape[1]
-    pvals_adj[pvals_adj > 1] = 1        # cap adjusted p-value at 1
+    pvals_adj[pvals_adj > 1] = 1  # cap adjusted p-value at 1

    # logfoldchanges: log2(meanA / meanB)
    logfoldchanges = np.log2(np.abs((meanA + 1e-9) / (meanB + 1e-9)))
@@ -106,8 +105,5 @@ def diffexp_ttest(adata, maskA, maskB, top_n=8, diffexp_lfc_cutoff=0.01):
    pvals_adj_top_n = pvals_adj[sort_order]

    # varIndex, logfoldchange, pval, pval_adj
-    result = [[sort_order[i],
-               logfoldchanges_top_n[i],
-               pvals_top_n[i],
-               pvals_adj_top_n[i]] for i in range(top_n)]
+    result = [[sort_order[i], logfoldchanges_top_n[i], pvals_top_n[i], pvals_adj_top_n[i]] for i in range(top_n)]
    return result
@@ -22,7 +22,6 @@ Sort order for methods


 class ScanpyEngine(CXGDriver):
-
    def __init__(self, data, args):
        super().__init__(data, args)
        self._alias_annotation_names(Axis.OBS, args["obs_names"])
@@ -36,7 +35,7 @@ class ScanpyEngine(CXGDriver):
        self._create_schema()

        # TODO: temporary work-arounds
-        if args['nan_to_num']:
+        if args["nan_to_num"]:
            self._IEEE754_special_values_workaround()

    def _alias_annotation_names(self, axis, name):
@@ -61,8 +60,9 @@ class ScanpyEngine(CXGDriver):
            if name not in df_axis.columns:
                raise KeyError(f"Annotation name {name}, specified in --{ax_name}-name does not exist.")
            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.")
+                raise KeyError(
+                    f"Values in -{ax_name}-name must be unique. " "Please prepare data to contain unique values."
+                )
            # reset index to simple range; alias user-specified annotation to "name"
            df_axis.reset_index(drop=True, inplace=True)
            df_axis.rename(inplace=True, columns={name: "name"})
@@ -89,15 +89,8 @@ class ScanpyEngine(CXGDriver):

    def _create_schema(self):
        self.schema = {
-            "dataframe": {
-                "nObs": self.cell_count,
-                "nVar": self.gene_count,
-                "type": str(self.data.X.dtype)
-            },
-            "annotations": {
-                "obs": [],
-                "var": []
-            }
+            "dataframe": {"nObs": self.cell_count, "nVar": self.gene_count, "type": str(self.data.X.dtype)},
+            "annotations": {"obs": [], "var": []},
        }
        for ax in Axis:
            curr_axis = getattr(self.data, str(ax))
@@ -129,32 +122,35 @@ class ScanpyEngine(CXGDriver):
        try:
            result = sc.read(data, cache=True)
        except ValueError:
-            raise ScanpyFileError("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.")
+            raise ScanpyFileError(
+                "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 Exception as e:
-            raise ScanpyFileError(f"Error while loading file: {e}, File must be in the .h5ad format, please check "
-                                  f"that your input and try again.")
+            raise ScanpyFileError(
+                f"Error while loading file: {e}, File must be in the .h5ad format, please check "
+                f"that your input and try again."
+            )
        return result

    def _validate_data_types(self):
        if self.data.X.dtype != "float32":
-            warnings.warn(f"Scanpy data matrix is in {self.data.X.dtype} format not float32. "
-                          f"Precision may be truncated.")
+            warnings.warn(
+                f"Scanpy 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",
-                                }
+                downcast_map = {"int64": "int32", "uint32": "int32", "uint64": "int32", "float64": "float32"}
                if datatype in downcast_map:
-                    warnings.warn(f"Scanpy annotation {ax}:{ann} is in unsupported format: {datatype}. "
-                                  f"Data will be downcast to {downcast_map[datatype]}.")
+                    warnings.warn(
+                        f"Scanpy 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.max_category_items:
@@ -162,7 +158,8 @@ class ScanpyEngine(CXGDriver):
                            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")
+                            f"annotations with more than 500 categories in the UI"
+                        )

    def _validate_data_calculations(self):
        layout_key = f"X_{self.layout_method}"
@@ -174,7 +171,8 @@ class ScanpyEngine(CXGDriver):
                f" layout may have been computed. The requested layout must be pre-calculated and saved "
                f"back in the h5ad file. You can run "
                f"`cellxgene prepare --layout {self.layout_method} <datafile>` "
-                f"to solve this problem. ")
+                f"to solve this problem. "
+            )

    def _IEEE754_special_values_workaround(self):
        """
@@ -196,7 +194,7 @@ class ScanpyEngine(CXGDriver):
            curr_axis = getattr(self.data, str(ax))
            for ann in curr_axis:
                dtype = curr_axis[ann].dtype
-                if dtype.kind == 'f':
+                if dtype.kind == "f":
                    finite_idx = np.isfinite(curr_axis[ann])
                    if not finite_idx.all():
                        curr_axis.loc[np.isnan(curr_axis[ann]), ann] = 0
@@ -233,8 +231,7 @@ class ScanpyEngine(CXGDriver):

        if non_finite_X_found:
            warnings.warn(
-                "Dataframe X contains floating point NaN or Infinities. "
-                "These will be converted to finite values."
+                "Dataframe X contains floating point NaN or Infinities. " "These will be converted to finite values."
            )

    def filter_dataframe(self, filter):
@@ -256,7 +253,7 @@ class ScanpyEngine(CXGDriver):

    @staticmethod
    def _annotation_filter_to_mask(filter, d_axis, count):
-        mask = np.ones((count, ), dtype=bool)
+        mask = np.ones((count,), dtype=bool)
        for v in filter:
            if d_axis[v["name"]].dtype.name in ["boolean", "category", "object"]:
                key_idx = np.in1d(getattr(d_axis, v["name"]), v["values"])
@@ -274,24 +271,23 @@ class ScanpyEngine(CXGDriver):

    @staticmethod
    def _index_filter_to_mask(filter, count):
-        mask = np.zeros((count, ), dtype=bool)
+        mask = np.zeros((count,), dtype=bool)
        for i in filter:
            if type(i) == list:
-                mask[i[0]:i[1]] = True
+                mask[i[0] : i[1]] = True
            else:
                mask[i] = True
        return mask

    @staticmethod
    def _axis_filter_to_mask(filter, d_axis, count):
-        mask = np.ones((count, ), dtype=bool)
+        mask = np.ones((count,), dtype=bool)
        if "index" in filter:
            mask = np.logical_and(mask, ScanpyEngine._index_filter_to_mask(filter["index"], count))
        if "annotation_value" in filter:
-            mask = np.logical_and(mask,
-                                  ScanpyEngine._annotation_filter_to_mask(filter["annotation_value"],
-                                                                          d_axis,
-                                                                          count))
+            mask = np.logical_and(
+                mask, ScanpyEngine._annotation_filter_to_mask(filter["annotation_value"], d_axis, count)
+            )
        return mask

    def _filter_to_mask(self, filter, use_slices=True):
@@ -321,8 +317,9 @@ class ScanpyEngine(CXGDriver):

        https://docs.scipy.org/doc/scipy/reference/sparse.html
        """
-        prefer_row_access = sparse.isspmatrix_csr(data._X) or sparse.isspmatrix_lil(data._X) \
-            or sparse.isspmatrix_bsr(data._X)
+        prefer_row_access = (
+            sparse.isspmatrix_csr(data._X) or sparse.isspmatrix_lil(data._X) or sparse.isspmatrix_bsr(data._X)
+        )
        if prefer_row_access:
            # Row-major slicing
            if obs_selector is not None:
@@ -355,18 +352,12 @@ class ScanpyEngine(CXGDriver):
            obs = self.data.obs[obs_selector]
            if not fields:
                fields = obs.columns.tolist()
-            result = {
-                "names": fields,
-                "data": DataFrame(obs[fields]).to_records(index=True).tolist()
-            }
+            result = {"names": fields, "data": DataFrame(obs[fields]).to_records(index=True).tolist()}
        else:
            var = self.data.var[var_selector]
            if not fields:
                fields = var.columns.tolist()
-            result = {
-                "names": fields,
-                "data": DataFrame(var[fields]).to_records(index=True).tolist()
-            }
+            result = {"names": fields, "data": DataFrame(var[fields]).to_records(index=True).tolist()}
        return result

    def data_frame(self, filter, axis):
@@ -391,12 +382,12 @@ class ScanpyEngine(CXGDriver):
        if axis == Axis.OBS:
            result = {
                "var": var_index_sliced.tolist(),
-                "obs": DataFrame(_X, index=obs_index_sliced).to_records(index=True).tolist()
+                "obs": DataFrame(_X, index=obs_index_sliced).to_records(index=True).tolist(),
            }
        else:
            result = {
                "obs": obs_index_sliced.tolist(),
-                "var": DataFrame(_X.T, index=var_index_sliced).to_records(index=True).tolist()
+                "var": DataFrame(_X.T, index=var_index_sliced).to_records(index=True).tolist(),
            }
        return result

@@ -435,11 +426,11 @@ class ScanpyEngine(CXGDriver):
        try:
            df_layout = df.obsm[f"X_{self.layout_method}"]
        except ValueError as e:
-            raise PrepareError(f"Layout has not been calculated using {self.layout_method}, "
-                               f"please prepare your datafile and relaunch cellxgene") from e
-        normalized_layout = DataFrame((df_layout - df_layout.min()) / (df_layout.max() - df_layout.min()),
-                                      index=df.obs.index)
-        return {
-            "ndims": normalized_layout.shape[1],
-            "coordinates": normalized_layout.to_records(index=True).tolist()
-        }
+            raise PrepareError(
+                f"Layout has not been calculated using {self.layout_method}, "
+                f"please prepare your datafile and relaunch cellxgene"
+            ) from e
+        normalized_layout = DataFrame(
+            (df_layout - df_layout.min()) / (df_layout.max() - df_layout.min()), index=df.obs.index
+        )
+        return {"ndims": normalized_layout.shape[1], "coordinates": normalized_layout.to_records(index=True).tolist()}
@@ -7,7 +7,6 @@ from server.app.util.constants import Axis


 class QueryStringError(Exception):
-
    def __init__(self, key, message):
        self.key = key
        self.message = message
@@ -5,24 +5,13 @@ class AnnotationModel(Schema):
    type = "object"
    description = "Filter by annotation key: value"
    properties = {
-        "name": {
-            "type": "string"
-        },
+        "name": {"type": "string"},
        # TODO update to OpenAPI v3.0 when a library is available that supports it
        # Unfortunately 2.0 doesn't have a way to have a schema that accepts multiple types
        # Overloading the type key with a list seems to work ok and makes it to the page
-        "values": {
-            "type": "array",
-            "items": {
-                "type": ["float32", "string", "int32", "bool"]
-            }
-        },
-        "min": {
-            "type": ["int32", "float32"],
-        },
-        "max": {
-            "type": ["int32", "float32"],
-        }
+        "values": {"type": "array", "items": {"type": ["float32", "string", "int32", "bool"]}},
+        "min": {"type": ["int32", "float32"]},
+        "max": {"type": ["int32", "float32"]},
    }
    required = ["name"]

@@ -30,36 +19,16 @@ class AnnotationModel(Schema):
 class IndexModel(Schema):
    type = "object"
    description = "Filter by index of observation/variable ex. [0, 5, 15]"
-    properties = {
-        "index": {
-            "type": "array",
-            "items": {
-                "format": "int32",
-                "type": "integer"
-            }
-
-        }
-    }
+    properties = {"index": {"type": "array", "items": {"format": "int32", "type": "integer"}}}


 class AxisModel(Schema):
    type = "object"
    description = "Axis of data -- obs or var"
-    properties = {
-        "index": IndexModel,
-        "annotation_value": AnnotationModel.array()
-    }
+    properties = {"index": IndexModel, "annotation_value": AnnotationModel.array()}


 class FilterModel(Schema):
    type = "object"
    description = "Complex filter"
-    properties = {
-        "filter": {
-            "type": "object",
-            "properties": {
-                "obs": AxisModel,
-                "var": AxisModel
-            }
-        }
-    }
+    properties = {"filter": {"type": "object", "properties": {"obs": AxisModel, "var": AxisModel}}}
@@ -15,7 +15,7 @@ class Float32JSONEncoder(json.JSONEncoder):
        if it runs into non-finite floating point values which are unsupported by
        standard JSON.
        """
-        kwargs['allow_nan'] = False
+        kwargs["allow_nan"] = False
        super().__init__(*args, **kwargs)

    def default(self, obj):
@@ -30,8 +30,9 @@ def custom_format_warning(msg, *args, **kwargs):
    return f"[cellxgene] Warning: {msg} \n"


-def get_mime_type(default="application/json", acceptable_types=["application/json", "text/csv"], query_param=None,
-                  header=None):
+def get_mime_type(
+    default="application/json", acceptable_types=["application/json", "text/csv"], query_param=None, header=None
+):
    mime_type = default
    if query_param:
        if query_param in acceptable_types:
@@ -1,7 +1,5 @@
 import os
-from flask import (
-    Blueprint, render_template, send_from_directory, current_app
-)
+from flask import Blueprint, render_template, send_from_directory, current_app


 bp = Blueprint("webapp", __name__, template_folder="templates")
@@ -5,7 +5,7 @@ from .prepare import prepare


@click.group(name="cellxgene", context_settings=dict(max_content_width=85))
-@click.version_option(version="0.3.0", prog_name="cellxgene", message="[%(prog)s] Version %(version)s")
+@click.version_option(version="0.4.0", prog_name="cellxgene", message="[%(prog)s] Version %(version)s")
 def cli():
    pass

@@ -13,30 +13,76 @@ from server.app.util.utils import custom_format_warning

@click.command()
@click.argument("data", metavar="<data file>", type=click.Path(exists=True, file_okay=True, dir_okay=False))
-@click.option("--layout", "-l", type=click.Choice(["umap", "tsne"]), default="umap", show_default=True,
-              help="Method for layout.")
-@click.option("--diffexp", "-d", type=click.Choice(["ttest"]), default="ttest", show_default=True,
-              help="Method for differential expression.")
+@click.option(
+    "--layout", "-l", type=click.Choice(["umap", "tsne"]), default="umap", show_default=True, help="Method for layout."
+)
+@click.option(
+    "--diffexp",
+    "-d",
+    type=click.Choice(["ttest"]),
+    default="ttest",
+    show_default=True,
+    help="Method for differential expression.",
+)
@click.option("--title", "-t", help="Title to display (if omitted will use file name).", metavar="")
-@click.option("--verbose", "-v", is_flag=True, default=False, show_default=True,
-              help="Provide verbose output, including warnings and all server requests.")
-@click.option("--debug", "-d", is_flag=True, default=False, show_default=True,
-              help="Run in debug mode.")
-@click.option("--open", "-o", "open_browser", is_flag=True, default=False, show_default=True,
-              help="Open the web browser after launch.")
+@click.option(
+    "--verbose",
+    "-v",
+    is_flag=True,
+    default=False,
+    show_default=True,
+    help="Provide verbose output, including warnings and all server requests.",
+)
+@click.option("--debug", "-d", is_flag=True, default=False, show_default=True, help="Run in debug mode.")
+@click.option(
+    "--open",
+    "-o",
+    "open_browser",
+    is_flag=True,
+    default=False,
+    show_default=True,
+    help="Open the web browser after launch.",
+)
@click.option("--port", "-p", help="Port to run server on.", metavar="", default=5005, show_default=True)
@click.option("--obs-names", default=None, metavar="", help="Name of annotation field to use for observations.")
@click.option("--var-names", default=None, metavar="", help="Name of annotation to use for variables.")
@click.option("--host", default="127.0.0.1", help="Host IP address")
-@click.option("--max-category-items", default=100, metavar="", show_default=True,
-              help="Limits the number of categorical annotation items displayed.")
-@click.option("--diffexp-lfc-cutoff", default=0.01, show_default=True,
-              help="Relative expression cutoff used when selecting top N differentially expressed genes")
-@click.option("--nan-to-num", is_flag=True, default=False, show_default=True,
-              help="Replace all floating point NaN with zero, and infinities with finite numbers")
-def launch(data, layout, diffexp, title, verbose, debug, obs_names, var_names,
-           open_browser, port, host, max_category_items, diffexp_lfc_cutoff,
-           nan_to_num):
+@click.option(
+    "--max-category-items",
+    default=100,
+    metavar="",
+    show_default=True,
+    help="Limits the number of categorical annotation items displayed.",
+)
+@click.option(
+    "--diffexp-lfc-cutoff",
+    default=0.01,
+    show_default=True,
+    help="Relative expression cutoff used when selecting top N differentially expressed genes",
+)
+@click.option(
+    "--nan-to-num",
+    is_flag=True,
+    default=False,
+    show_default=True,
+    help="Replace all floating point NaN with zero, and infinities with finite numbers",
+)
+def launch(
+    data,
+    layout,
+    diffexp,
+    title,
+    verbose,
+    debug,
+    obs_names,
+    var_names,
+    open_browser,
+    port,
+    host,
+    max_category_items,
+    diffexp_lfc_cutoff,
+    nan_to_num,
+):
    """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
@@ -76,10 +122,7 @@ def launch(data, layout, diffexp, title, verbose, debug, obs_names, var_names,
    # Import Flask app
    from server.app.app import app

-    app.config.update(
-        DATASET_TITLE=title,
-        CXG_API_BASE=api_base
-    )
+    app.config.update(DATASET_TITLE=title, CXG_API_BASE=api_base)

    if not verbose:
        log = logging.getLogger("werkzeug")
@@ -90,7 +133,8 @@ def launch(data, layout, diffexp, title, verbose, debug, obs_names, var_names,
    # Fix for anaconda python. matplotlib typically expects python to be installed as a framework TKAgg is usually
    # available and fixes this issue. See https://matplotlib.org/faq/virtualenv_faq.html
    import matplotlib as mpl
-    mpl.use('TkAgg')
+
+    mpl.use("TkAgg")
    from server.app.scanpy_engine.scanpy_engine import ScanpyEngine

    args = {
@@ -100,7 +144,7 @@ def launch(data, layout, diffexp, title, verbose, debug, obs_names, var_names,
        "diffexp_lfc_cutoff": diffexp_lfc_cutoff,
        "obs_names": obs_names,
        "var_names": var_names,
-        "nan_to_num": nan_to_num
+        "nan_to_num": nan_to_num,
    }

    try:
@@ -117,7 +161,7 @@ def launch(data, layout, diffexp, title, verbose, debug, obs_names, var_names,
    click.echo("[cellxgene] Type CTRL-C at any time to exit.")

    if not verbose:
-        f = open(devnull, 'w')
+        f = open(devnull, "w")
        sys.stdout = f

    app.run(host=host, debug=debug, port=port, threaded=True)
@@ -7,22 +7,48 @@ from scipy.sparse.csc import csc_matrix

@click.command()
@click.argument("data", nargs=1, metavar="<dataset: file or path to data>", required=True)
-@click.option("--layout", "-l", default=["umap", "tsne"], multiple=True, type=click.Choice(["umap", "tsne"]),
-              help="Layout algorithm", show_default=True)
-@click.option("--recipe", "-r", default="none", type=click.Choice(["none", "seurat", "zheng17"]),
-              help="Preprocessing to run.", show_default=True)
+@click.option(
+    "--layout",
+    "-l",
+    default=["umap", "tsne"],
+    multiple=True,
+    type=click.Choice(["umap", "tsne"]),
+    help="Layout algorithm",
+    show_default=True,
+)
+@click.option(
+    "--recipe",
+    "-r",
+    default="none",
+    type=click.Choice(["none", "seurat", "zheng17"]),
+    help="Preprocessing to run.",
+    show_default=True,
+)
@click.option("--output", "-o", default="", help="Save a new file to filename.", metavar="<filename>")
@click.option("--plotting", "-p", default=False, is_flag=True, help="Whether to generate plots.", show_default=True)
@click.option("--sparse", default=False, is_flag=True, help="Whether to 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="<name>")
@click.option("--set-var-names", default="", help="Named field to set as index for var.", metavar="<name>")
-@click.option("--make-obs-names-unique", default=True, is_flag=True,
-              help="Ensure obs index is unique.", show_default=True)
-@click.option("--make-var-names-unique", default=True, is_flag=True,
-              help="Ensure var index is unique.", show_default=True)
-def prepare(data, layout, recipe, output, plotting, sparse, overwrite,
-            set_obs_names, set_var_names, make_obs_names_unique, make_var_names_unique):
+@click.option(
+    "--make-obs-names-unique", default=True, is_flag=True, help="Ensure obs index is unique.", show_default=True
+)
+@click.option(
+    "--make-var-names-unique", default=True, is_flag=True, help="Ensure var index is unique.", show_default=True
+)
+def prepare(
+    data,
+    layout,
+    recipe,
+    output,
+    plotting,
+    sparse,
+    overwrite,
+    set_obs_names,
+    set_var_names,
+    make_obs_names_unique,
+    make_var_names_unique,
+):
    """Preprocesses data for use with cellxgene.

    This tool runs a series of scanpy routines for preparing a dataset
@@ -35,6 +61,7 @@ def prepare(data, layout, recipe, output, plotting, sparse, overwrite,
    # collect slow imports here to make CLI startup more responsive
    click.echo("[cellxgene] Starting CLI...")
    import matplotlib
+
    matplotlib.use("Agg")
    import scanpy.api as sc

@@ -49,8 +76,10 @@ def prepare(data, layout, recipe, output, plotting, sparse, overwrite,
    output = expanduser(output)

    if not output:
-        click.echo("Warning: No file will be saved, to save the results of cellxgene prepare include "
-                   "--output <filename> to save output to a new file")
+        click.echo(
+            "Warning: No file will be saved, to save the results of cellxgene prepare include "
+            "--output <filename> 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")

@@ -119,9 +148,11 @@ def prepare(data, layout, recipe, output, plotting, sparse, overwrite,
        try:
            sc.tl.louvain(adata)
        except ModuleNotFoundError:
-            click.echo("\nWarning: louvain module is not installed, no clusters will be calculated. "
-                       "To fix this please install cellxgene with the optional feature louvain enabled: "
-                       "`pip install cellxgene[louvain]`")
+            click.echo(
+                "\nWarning: louvain module is not installed, no clusters will be calculated. "
+                "To fix this please install cellxgene with the optional feature louvain enabled: "
+                "`pip install cellxgene[louvain]`"
+            )

    def run_layout(adata):
        if len(unique(adata.obs["louvain"].values)) < 10:
@@ -142,11 +173,11 @@ def prepare(data, layout, recipe, output, plotting, sparse, overwrite,
    def show_step(item):
        names = {
            "make_sparse": "Ensuring sparsity",
-            "run_recipe": f"Running preprocessing recipe \"{recipe}\"",
+            "run_recipe": f'Running preprocessing recipe "{recipe}"',
            "run_pca": "Running PCA",
            "run_neighbors": "Calculating neighbors",
            "run_louvain": "Calculating clusters",
-            "run_layout": "Computing layout"
+            "run_layout": "Computing layout",
        }
        if item is not None:
            return names[item.__name__]
@@ -1,5 +1,6 @@
+black
+bumpversion>=0.5
 pytest>=3.6.3
 requests>=2.18.4
 twine>=1.12.1
-bumpversion>=0.5
 -r requirements.txt
@@ -11,4 +11,4 @@ numpy>=1.14.5
 pandas>=0.23.1
 scanpy>=1.3.2
 scipy>=1.1.0
-scikit-learn>=0.20.1
+scikit-learn>=0.19.1,!=0.20.0
@@ -9,15 +9,7 @@ LOCAL_URL = "http://127.0.0.1:5005/"
 VERSION = "v0.2"
 URL_BASE = f"{LOCAL_URL}api/{VERSION}/"

-BAD_FILTER = {
-            "filter": {
-                "obs": {
-                    "annotation_value": [
-                        {"name": "xyz"},
-                    ],
-                }
-            }
-        }
+BAD_FILTER = {"filter": {"obs": {"annotation_value": [{"name": "xyz"}]}}}


 class EndPoints(unittest.TestCase):
@@ -133,7 +125,7 @@ class EndPoints(unittest.TestCase):
                        {"name": "louvain", "values": ["NK cells", "CD8 T cells"]},
                        {"name": "n_counts", "min": 3000},
                    ],
-                    "index": [1, 99, [1000, 2000]]
+                    "index": [1, 99, [1000, 2000]],
                }
            }
        }
@@ -154,7 +146,7 @@ class EndPoints(unittest.TestCase):
                        {"name": "louvain", "values": ["NK cells", "CD8 T cells"]},
                        {"name": "n_counts", "min": 3000},
                    ],
-                    "index": [1, 99, [1000, 2000]]
+                    "index": [1, 99, [1000, 2000]],
                }
            }
        }
@@ -170,23 +162,9 @@ class EndPoints(unittest.TestCase):
        url = f"{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": 7
+            "set1": {"filter": {"obs": {"annotation_value": [{"name": "louvain", "values": ["NK cells"]}]}}},
+            "set2": {"filter": {"obs": {"annotation_value": [{"name": "louvain", "values": ["CD8 T cells"]}]}}},
+            "count": 7,
        }
        result = self.session.post(url, json=params)
        self.assertEqual(result.status_code, HTTPStatus.OK)
@@ -199,20 +177,8 @@ class EndPoints(unittest.TestCase):
        params = {
            "mode": "topN",
            "count": 10,
-            "set1": {
-                "filter": {
-                    "obs": {
-                        "index": [[0, 500]]
-                    }
-                }
-            },
-            "set2": {
-                "filter": {
-                    "obs": {
-                        "index": [[500, 1000]]
-                    }
-                }
-            }
+            "set1": {"filter": {"obs": {"index": [[0, 500]]}}},
+            "set2": {"filter": {"obs": {"index": [[500, 1000]]}}},
        }
        result = self.session.post(url, json=params)
        self.assertEqual(result.status_code, HTTPStatus.OK)
@@ -249,15 +215,7 @@ class EndPoints(unittest.TestCase):
    def test_put_annotations_var(self):
        endpoint = "annotations/var"
        url = f"{URL_BASE}{endpoint}"
-        var_filter = {
-            "filter": {
-                "var": {
-                    "annotation_value": [
-                        {"name": "name", "values": ["ATAD3C", "RER1"]},
-                    ]
-                }
-            }
-        }
+        var_filter = {"filter": {"var": {"annotation_value": [{"name": "name", "values": ["ATAD3C", "RER1"]}]}}}
        result = self.session.put(url, json=var_filter)
        self.assertEqual(result.status_code, HTTPStatus.OK)
        result_data = result.json()
@@ -268,15 +226,7 @@ class EndPoints(unittest.TestCase):
        endpoint = "annotations/var"
        query = "annotation-name=n_cells"
        url = f"{URL_BASE}{endpoint}?{query}"
-        var_filter = {
-            "filter": {
-                "var": {
-                    "annotation_value": [
-                        {"name": "name", "values": ["ATAD3C", "RER1"]},
-                    ]
-                }
-            }
-        }
+        var_filter = {"filter": {"var": {"annotation_value": [{"name": "name", "values": ["ATAD3C", "RER1"]}]}}}
        result = self.session.put(url, json=var_filter)
        self.assertEqual(result.status_code, HTTPStatus.OK)
        result_data = result.json()
@@ -335,7 +285,7 @@ class EndPoints(unittest.TestCase):
                            {"name": "louvain", "values": ["NK cells", "CD8 T cells"]},
                            {"name": "n_counts", "min": 3000},
                        ],
-                        "index": [1, 99, [1000, 2000]]
+                        "index": [1, 99, [1000, 2000]],
                    }
                }
            }
@@ -349,15 +299,7 @@ class EndPoints(unittest.TestCase):
            endpoint = f"data/{axis}"
            url = f"{URL_BASE}{endpoint}"
            header = {"Accept": "application/json"}
-            var_filter = {
-                "filter": {
-                    "var": {
-                        "annotation_value": [
-                            {"name": "name", "values": ["RER1"]},
-                        ]
-                    }
-                }
-            }
+            var_filter = {"filter": {"var": {"annotation_value": [{"name": "name", "values": ["RER1"]}]}}}
            result = self.session.put(url, headers=header, json=var_filter)
            self.assertEqual(result.status_code, HTTPStatus.OK)
            result_data = result.json()
@@ -371,16 +313,44 @@ class EndPoints(unittest.TestCase):
    def test_cache(self):
        endpoint = "annotations/var"
        url = f"{URL_BASE}{endpoint}"
-        f1 = {"filter": {"var": {"annotation_value": [{"name": "name",
-                                                       "values": ["HLA-DRB1", "HLA-DQA1", "HLA-DQB1", "HLA-DPA1",
-                                                                  "HLA-DPB1", "MS4A1", "IL32", "CCL5", "CD79B",
-                                                                  "CD79A"]}]}}}
+        f1 = {
+            "filter": {
+                "var": {
+                    "annotation_value": [
+                        {
+                            "name": "name",
+                            "values": [
+                                "HLA-DRB1",
+                                "HLA-DQA1",
+                                "HLA-DQB1",
+                                "HLA-DPA1",
+                                "HLA-DPB1",
+                                "MS4A1",
+                                "IL32",
+                                "CCL5",
+                                "CD79B",
+                                "CD79A",
+                            ],
+                        }
+                    ]
+                }
+            }
+        }
        result = self.session.put(url, json=f1)
        self.assertEqual(result.status_code, HTTPStatus.OK)
        result_data1 = result.json()
-        f2 = {"filter": {"var": {"annotation_value": [{"name": "name",
-                                                       "values": ["FGFBP2", "GZMA", "LTB", "PRF1", "CTSW", "GZMH",
-                                                                  "CCL5", "CCL4", "CST7", "NKG7"]}]}}}
+        f2 = {
+            "filter": {
+                "var": {
+                    "annotation_value": [
+                        {
+                            "name": "name",
+                            "values": ["FGFBP2", "GZMA", "LTB", "PRF1", "CTSW", "GZMH", "CCL5", "CCL4", "CST7", "NKG7"],
+                        }
+                    ]
+                }
+            }
+        }
        result = self.session.put(url, json=f2)
        self.assertEqual(result.status_code, HTTPStatus.OK)
        result_data2 = result.json()
@@ -393,9 +363,18 @@ class EndPoints(unittest.TestCase):
        result = self.session.put(url, json=f1)
        self.assertEqual(result.status_code, HTTPStatus.OK)
        result_data1 = result.json()
-        f2 = {"filter": {"var": {"annotation_value": [{"name": "name",
-                                                       "values": ["FGFBP2", "GZMA", "LTB", "PRF1", "CTSW", "GZMH",
-                                                                  "CCL5", "CCL4", "CST7", "NKG7"]}]}}}
+        f2 = {
+            "filter": {
+                "var": {
+                    "annotation_value": [
+                        {
+                            "name": "name",
+                            "values": ["FGFBP2", "GZMA", "LTB", "PRF1", "CTSW", "GZMH", "CCL5", "CCL4", "CST7", "NKG7"],
+                        }
+                    ]
+                }
+            }
+        }
        result = self.session.put(url, json=f2)
        self.assertEqual(result.status_code, HTTPStatus.OK)
        result_data2 = result.json()
@@ -54,13 +54,17 @@ class UtilTest(unittest.TestCase):

    def test_complex_filter(self):
        filter_dict = ImmutableMultiDict(
-            [("obs:louvain", "NK cells"), ("obs:louvain", "CD8 T cells"), ("obs:n_counts", "3000,*")])
+            [("obs:louvain", "NK cells"), ("obs:louvain", "CD8 T cells"), ("obs:n_counts", "3000,*")]
+        )
        filter_ = parse_filter(filter_dict, self.schema)
        self.assertIn("obs", filter_)
-        self.assertEqual(filter_["obs"]["annotation_value"], [{"name": "louvain",
-                                                               "values": ["NK cells", "CD8 T cells"]},
-                                                              {"name": "n_counts",
-                                                               "max": None, "min": 3000.0}])
+        self.assertEqual(
+            filter_["obs"]["annotation_value"],
+            [
+                {"name": "louvain", "values": ["NK cells", "CD8 T cells"]},
+                {"name": "n_counts", "max": None, "min": 3000.0},
+            ],
+        )

    def test_bad_filter(self):
        bad_annotation_type = ImmutableMultiDict([("obs:tissue", "lung")])
@@ -71,9 +75,7 @@ class UtilTest(unittest.TestCase):
            parse_filter(bad_axis, self.schema)

    def test_boolean_filter(self):
-        schema = {
-            "obs": [{"name": "bool_filter", "type": "boolean"}]
-        }
+        schema = {"obs": [{"name": "bool_filter", "type": "boolean"}]}
        filter_dict = ImmutableMultiDict([("obs:bool_filter", "false")])
        filter_ = parse_filter(filter_dict, schema)
        self.assertIn("obs", filter_)
@@ -3,7 +3,6 @@ from os import path
 import pytest
 import time
 import unittest
-import argparse

 import numpy as np
 from pandas import Series
@@ -13,9 +12,15 @@ from server.app.scanpy_engine.scanpy_engine import ScanpyEngine

 class UtilTest(unittest.TestCase):
    def setUp(self):
-        args = {'layout': 'umap', 'diffexp': 'ttest', 'max_category_items': 100,
-                'obs_names': None, 'var_names': None, 'diffexp_lfc_cutoff': 0.01,
-                'nan_to_num': True}
+        args = {
+            "layout": "umap",
+            "diffexp": "ttest",
+            "max_category_items": 100,
+            "obs_names": None,
+            "var_names": None,
+            "diffexp_lfc_cutoff": 0.01,
+            "nan_to_num": True,
+        }

        self.data = ScanpyEngine("example-dataset/pbmc3k.h5ad", args)
        self.data._create_schema()
@@ -23,8 +28,8 @@ class UtilTest(unittest.TestCase):
    def test_init(self):
        self.assertEqual(self.data.cell_count, 2638)
        self.assertEqual(self.data.gene_count, 1838)
-        epsilon = 0.000005
-        self.assertTrue(self.data.data.X[0, 0] - -0.17146951 < epsilon)
+        epsilon = 0.000_005
+        self.assertTrue(self.data.data.X[0, 0] - -0.171_469_51 < epsilon)

    def test_mandatory_annotations(self):
        self.assertIn("name", self.data.data.obs)
@@ -39,69 +44,36 @@ class UtilTest(unittest.TestCase):
            self.data._validate_data_types()

    def test_filter_idx(self):
-        filter_ = {
-            "filter": {
-                "var": {
-                    "index": [1, 99, [200, 300]]
-                },
-                "obs": {
-                    "index": [1, 99, [1000, 2000]]
-                }
-            }
-        }
+        filter_ = {"filter": {"var": {"index": [1, 99, [200, 300]]}, "obs": {"index": [1, 99, [1000, 2000]]}}}
        data = self.data.filter_dataframe(filter_["filter"])
        self.assertEqual(data.shape, (1002, 102))

    def test_filter_annotation(self):
        filter_ = {
-            "filter": {
-                "obs": {
-                    "annotation_value": [
-                        {"name": "louvain", "values": ["NK cells", "CD8 T cells"]},
-                    ]
-                }
-            }
+            "filter": {"obs": {"annotation_value": [{"name": "louvain", "values": ["NK cells", "CD8 T cells"]}]}}
        }
        data = self.data.filter_dataframe(filter_["filter"])
        self.assertEqual(data.shape, (470, 1838))
-        filter_ = {
-            "filter": {
-                "obs": {
-                    "annotation_value": [
-                        {"name": "n_counts", "min": 3000},
-                    ]
-                }
-            }
-        }
+        filter_ = {"filter": {"obs": {"annotation_value": [{"name": "n_counts", "min": 3000}]}}}
        data = self.data.filter_dataframe(filter_["filter"])
        self.assertEqual(data.shape, (497, 1838))

    def test_filter_annotation_no_uns(self):
-        filter_ = {
-            "filter": {
-                "var": {
-                    "annotation_value": [
-                        {"name": "name", "values": ["RER1"]},
-                    ]
-                }
-            }
-        }
+        filter_ = {"filter": {"var": {"annotation_value": [{"name": "name", "values": ["RER1"]}]}}}
        data = self.data.filter_dataframe(filter_["filter"])
        self.assertEqual(data.shape[1], 1)

    def test_filter_complex(self):
        filter_ = {
            "filter": {
-                "var": {
-                    "index": [1, 99, [200, 300]]
-                },
+                "var": {"index": [1, 99, [200, 300]]},
                "obs": {
                    "annotation_value": [
                        {"name": "louvain", "values": ["NK cells", "CD8 T cells"]},
                        {"name": "n_counts", "min": 3000},
                    ],
-                    "index": [1, 99, [1000, 2000]]
-                }
+                    "index": [1, 99, [1000, 2000]],
+                },
            }
        }
        data = self.data.filter_dataframe(filter_["filter"])
@@ -117,13 +89,14 @@ class UtilTest(unittest.TestCase):
            self.assertEqual(self.data.schema, schema)

    def test_schema_produces_error(self):
-        self.data.data.obs["time"] = Series(list([time.time() for i in range(self.data.cell_count)]),
-                                            dtype="datetime64[ns]")
+        self.data.data.obs["time"] = 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_config(self):
-        self.assertEqual(self.data.features["layout"]["obs"], {'available': True, 'interactiveLimit': 50000})
+        self.assertEqual(self.data.features["layout"]["obs"], {"available": True, "interactiveLimit": 50000})

    def test_layout(self):
        layout = self.data.layout(None)
@@ -153,16 +126,8 @@ class UtilTest(unittest.TestCase):
    def test_filtered_annotation(self):
        filter_ = {
            "filter": {
-                "obs": {
-                    "annotation_value": [
-                        {"name": "n_counts", "min": 3000},
-                    ]
-                },
-                "var": {
-                    "annotation_value": [
-                        {"name": "name", "values": ["ATAD3C", "RER1"]},
-                    ]
-                }
+                "obs": {"annotation_value": [{"name": "n_counts", "min": 3000}]},
+                "var": {"annotation_value": [{"name": "name", "values": ["ATAD3C", "RER1"]}]},
            }
        }
        annotations = self.data.annotation(filter_["filter"], "obs")
@@ -173,33 +138,13 @@ class UtilTest(unittest.TestCase):
        self.assertEqual(len(annotations["data"]), 2)

    def test_filtered_layout(self):
-        filter_ = {
-            "filter": {
-                "obs": {
-                    "annotation_value": [
-                        {"name": "n_counts", "min": 3000},
-                    ]
-                }
-            }
-        }
+        filter_ = {"filter": {"obs": {"annotation_value": [{"name": "n_counts", "min": 3000}]}}}
        layout = self.data.layout(filter_["filter"])
        self.assertEqual(len(layout["coordinates"]), 497)

    def test_diffexp_topN(self):
-        f1 = {
-            "filter": {
-                "obs": {
-                    "index": [[0, 500]]
-                }
-            }
-        }
-        f2 = {
-            "filter": {
-                "obs": {
-                    "index": [[500, 1000]]
-                }
-            }
-        }
+        f1 = {"filter": {"obs": {"index": [[0, 500]]}}}
+        f2 = {"filter": {"obs": {"index": [[500, 1000]]}}}
        result = self.data.diffexp_topN(f1["filter"], f2["filter"])
        self.assertEqual(len(result), 10)
        result = self.data.diffexp_topN(f1["filter"], f2["filter"], 20)
@@ -214,15 +159,7 @@ class UtilTest(unittest.TestCase):
        self.assertEqual(len(data_frame_var["obs"]), 2638)

    def test_filtered_data_frame(self):
-        filter_ = {
-            "filter": {
-                "obs": {
-                    "annotation_value": [
-                        {"name": "n_counts", "min": 3000},
-                    ]
-                }
-            }
-        }
+        filter_ = {"filter": {"obs": {"annotation_value": [{"name": "n_counts", "min": 3000}]}}}
        data_frame_obs = self.data.data_frame(filter_["filter"], "obs")
        self.assertEqual(len(data_frame_obs["var"]), 1838)
        self.assertEqual(len(data_frame_obs["obs"]), 497)
@@ -236,15 +173,7 @@ class UtilTest(unittest.TestCase):

    def test_data_single_gene(self):
        for axis in ["obs", "var"]:
-            filter_ = {
-                "filter": {
-                    "var": {
-                        "annotation_value": [
-                            {"name": "name", "values": ["RER1"]},
-                        ]
-                    }
-                }
-            }
+            filter_ = {"filter": {"var": {"annotation_value": [{"name": "name", "values": ["RER1"]}]}}}
            data_frame_var = self.data.data_frame(filter_["filter"], axis)
            if axis == "obs":
                self.assertEqual(type(data_frame_var["var"][0]), int)
@@ -253,5 +182,5 @@ class UtilTest(unittest.TestCase):
                self.assertEqual(type(data_frame_var["obs"][0]), int)
                self.assertIsInstance(data_frame_var["var"][0], (list, tuple))

-    if __name__ == '__main__':
+    if __name__ == "__main__":
        unittest.main()
@@ -1,2 +1,3 @@
 [flake8]
 max-line-length = 120
+ignore = E203
@@ -1,4 +1,13 @@
 from setuptools import setup, find_packages
+import sys
+
+if sys.version_info[0:2] != (3, 6):
+    raise ImportError(
+        "cellxgene currently only supports python 3.6. Python 3.7 is known to fail; we will look at supporting "
+        "versions other than 3.6 in the future."
+        "See https://github.com/chanzuckerberg/cellxgene#conda-and-virtual-environments "
+        "for more help with installation."
+    )

 with open("README.md", "rb") as fh:
    long_description = fh.read().decode()
@@ -8,7 +17,7 @@ with open("server/requirements.txt") as fh:

 setup(
    name="cellxgene",
-    version="0.3.0",
+    version="0.4.0",
    packages=find_packages(),
    url="https://github.com/chanzuckerberg/cellxgene",
    license="MIT",
@@ -16,19 +25,24 @@ setup(
    author_email="cweaver@chanzuckerberg.com",
    description="Web application for exploration of large scale scRNA-seq datasets",
    long_description=long_description,
-    long_description_content_type='text/markdown',
+    long_description_content_type="text/markdown",
    install_requires=requirements,
    include_package_data=True,
    zip_safe=False,
-    classifiers=(
-        "Programming Language :: Python :: 3",
+    classifiers=[
+        "Framework :: Flask",
+        "Intended Audience :: Science/Research",
        "License :: OSI Approved :: MIT License",
-    ),
-    entry_points={
-        "console_scripts":
-            ["cellxgene = server.cli.cli:cli"]
-    },
-    extras_require=dict(
-        louvain=['python-igraph', 'louvain>=0.6'],
-    ),
+        "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 :: Only",
+        "Topic :: Scientific/Engineering :: Bio-Informatics",
+    ],
+    entry_points={"console_scripts": ["cellxgene = server.cli.cli:cli"]},
+    extras_require=dict(louvain=["python-igraph", "louvain>=0.6"]),
 )
Author	SHA1	Message	Date
Colin Megill	a297ea30e2	bump version (#518 )	2018-12-17 14:30:34 -05:00
Colin Megill	0ef6c36f4c	Cluster Occupancy (n dim cube) (#513 ) * create occupancy component * occupancy working * centering, width, flex spacing * add is-number * extend sort to cover string + int * proof of concept sorted occupancy * handle undefined occupancy entry, cleanup * only render occupancy when colorby is cat * cleanup unused vars * cleanup	2018-12-17 14:19:48 -05:00
Justin Kiggins	aaa60bc303	new signup url (#516 )	2018-12-14 16:32:41 -08:00
fionagriffin	7d40d89fd8	Update index.md (#507 ) Added content from readme	2018-12-14 15:19:21 -08:00
Charlotte Weaver	46ad346df1	Clarify that we do not support python 3.7 (#512 ) * Update setup.py * Readme: no python 3.7 * specify 3.6 in venv * clarify 3.7 error we will support it eventually	2018-12-13 15:15:56 -08:00
Charlotte Weaver	83154577e4	Black -- formatter for python (#508 ) * Add black * use black to format code * Black version	2018-12-12 09:44:47 -08:00
Charlotte Weaver	a847951658	Update slack link (#506 )	2018-12-11 10:20:22 -08:00
Charlotte Weaver	24af6efbcb	Add Docker file (#505 ) * Add docker support * Add readme * minor fixes	2018-12-11 10:18:10 -08:00
Colin Megill	126cac833a	Rename README.md to index.md	2018-12-11 12:09:16 -05:00
Colin Megill	fc272dc42e	github pages test	2018-12-11 12:05:14 -05:00
Colin Megill	d3a0d66139	Set theme jekyll-theme-architect	2018-12-10 18:16:40 -05:00
Charlotte Weaver	9604231a2a	Add alternative to install [louvain] extra requires (#500 ) * louvain install by hand * reworded	2018-12-10 14:46:55 -08:00
Jeremy Freeman	6ea3b7f3cf	use collapsable details to improve FAQ formatting (#503 )	2018-12-07 21:07:57 +01:00
Charlotte Weaver	0d0a32f272	Added PR guidelines (#492 ) * Added PR guidelines Added document to cover guidelines for creating, reviewing and merging PRs. * fixed typo * another typo * grammar * Remove 5's title The subheading is clearer as a top-level	2018-12-06 13:43:10 -08:00
Bruce Martin	48e0ea542b	clarifications to release recipe (#499 ) * clarifications to release recipe * fix spelling errors	2018-12-05 16:58:53 -08:00