pytest-workflow 1.2.1

A pytest plugin for configuring workflow/pipeline tests using YAML files

pytest-workflow is a pytest plugin that aims to make pipeline/workflow testing easy by using yaml files for the test configuration.

For our complete documentation checkout our readthedocs page.

Installation

Pytest-workflow requires Python 3.5 or higher. It is tested on Python 3.5, 3.6 and 3.7. Python 2 is not supported.

• Make sure your virtual environment is activated.

• Install using pip pip install pytest-workflow

• Create a tests directory in the root of your repository.

• Create your test yaml files in the tests directory.

Pytest-workflow is also available as a conda package on conda-forge. Follow these instructions to set up channels properly in order to use conda-forge. Alternatively, you can set up the channels correctly for use with bioconda. After that conda install pytest-workflow can be used to install pytest-workflow.

Quickstart

Run pytest from an environment with pytest-workflow installed. Pytest will automatically gather files in the tests directory starting with test and ending in .yaml or .yml.

To check the progress of a workflow while it is running you can use tail -f on the stdout or stderr file of the workflow. The locations of these files are reported in the log as soon as a workflow is started.

For debugging pipelines using the --kwd or --keep-workflow-wd flag is recommended. This will keep the workflow directory and logs after the test run so it is possible to check where the pipeline crashed. The -v flag can come in handy as well as it gives a complete overview of succeeded and failed tests.

Below is an example of a YAML file that defines a test:

- name: Touch a file
  command: touch test.file
  files:
    - path: test.file

This will run touch test.file and check afterwards if a file with path: test.file is present. It will also check if the command has exited with exit code 0, which is the only default test that is run. Testing workflows that exit with another exit code is also possible. Several other predefined tests as well as custom tests are possible.

Documentation for more advanced use cases can be found on our readthedocs page.