Metadata-Version: 2.1
Name: pytest-wdl
Version: 0.1.2.dev0
Summary: Fixtures for pytest for running WDL workflows using Cromwell.
Home-page: UNKNOWN
License: UNKNOWN
Platform: UNKNOWN
Description-Content-Type: text/markdown
Requires-Dist: pytest
Requires-Dist: delegator.py
Provides-Extra: all
Requires-Dist: pysam ; extra == 'all'
Requires-Dist: tqdm ; extra == 'all'
Provides-Extra: bam
Requires-Dist: pysam ; extra == 'bam'
Provides-Extra: progress
Requires-Dist: tqdm ; extra == 'progress'

# pytest-wdl

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This package is a plugin for the [pytest](https://docs.pytest.org/en/latest/) unit testing framework that enables testing of workflows written in [Workflow Description Language](https://github.com/openwdl).

## Dependencies

* Python 3.6+
* Java 1.8+
* [Cromwell](https://github.com/broadinstitute/cromwell/releases/tag/38) JAR file
* [Docker](https://www.docker.com/get-started) daemon (if your WDL tasks depend on Docker images)

Other python dependencies are installed when you install the library.

## Installation

### Install from PyPI

```commandline
$ pip install pytest-wdl
```

### Install from source

You can to clone the repository and install:

```
$ make install
```

Or use pip to install from github:

```commandline
$ pip install git+https://github.com/elilillyco/pytest-wdl.git
```

### Install optional dependencies

Some optional features of pytest-wdl have additional dependencies that are loaded on-demand. For example, to enable comparison of expected and actual BAM file outputs of a workflow, the [pysam](https://pysam.readthedocs.io/) library is required.

The following data types require an "extras" installation:

- bam

To install the dependencies for a data type that has extra dependencies:

```
$ pip install pytest-wdl[<data_type>]
```

To do this locally, you can clone the repo and run:

```commandline
$ pip install -e .[<data_type>]
```

To install pytest-wdl and **all** extras dependencies:

```
$ pip install pytest-wdl[all]
```

## Usage

The pytest-wdl plugin provides a set of fixtures for use with pytest. Here is a quick example:

```python
# test_variant_caller.py
def test_variant_caller(workflow_data, workflow_runner):
    inputs = workflow_data.get_dict("bam", "bai")
    inputs["index"] = {
        "fasta": workflow_data["index_fa"],
        "organism": "human"
    }
    expected = workflow_data.get_dict("vcf")
    workflow_runner(
        "variant_caller/variant_caller.wdl",
        "call_variants",
        inputs,
        expected
    )
```

This test will execute a workflow (such as the following one) with the specified inputs, and will compare the outputs to the specified expected outputs.

```wdl
# variant_caller.wdl
version 1.0

struct Index {
  File fasta
  String organism
}

workflow call_variants {
  input {
    File bam
    File bai
    Index index
  }
  ...
  output {
    File vcf = variant_caller.vcf
  }
}
```

Input and output data are defined in a `test_data.json` file in the same directory as your test script:

```json
{
  "bam": {
    "url": "http://example.com/my.bam"
  },
  "bai": {
    "url": "http://example.com/my.bam.bai"
  },
  "index_fa": {
    "name": "chr22.fasta"
  },
  "vcf": {
    "url": "http://example.com/expected.vcf.gz",
    "type": "vcf",
    "allowed_diff_lines": 2
  }
}
```

For details, [read the docs](https://pytest-wdl.readthedocs.io).

## Development

To develop pytest-wdl, clone the repository and install all the dependencies:

```commandline
$ git clone https://github.com/EliLillyCo/pytest-wdl.git
$ pip install -r requirements.txt
```

To run the full build and unit tests, run:

```commandline
$ make
```


