pytest-workflow is a workflow-system agnostic testing framework that aims to make pipeline/workflow testing easy by using YAML files for the test configuration. Whether you write your pipelines in WDL, snakemake, nextflow, bash or any other workflow framework, pytest-workflow makes testing easy. pytest-workflow is build on top of the pytest test framework.
For our complete documentation and examples checkout our readthedocs page.
Pytest-workflow requires Python 3.7 or higher. It is tested on Python 3.7, 3.8, 3.9, 3.10 and 3.11.
- Make sure your virtual environment is activated.
- Install using pip
pip install pytest-workflow
- Create a
testsdirectory in the root of your repository.
- Create your test yaml files in the
Pytest-workflow is also available as a conda package on conda-forge. Follow
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
install pytest-workflow can be used to install pytest-workflow.
pytest from an environment with pytest-workflow installed.
Pytest will automatically gather files in the
tests directory starting with
test and ending in
To check the progress of a workflow while it is running you can use
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
--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.
- name: moo file # The name of the workflow (required) command: bash moo_workflow.sh # The command to execute the workflow (required) files: # A list of files to check (optional) - path: "moo.txt" # File path. (Required for each file) contains: # A list of strings that should be in the file (optional) - "moo" must_not_contain: # A list of strings that should NOT be in the file (optional) - "Cock a doodle doo" md5sum: e583af1f8b00b53cda87ae9ead880224 # Md5sum of the file (optional) encoding: UTF-8 # Encoding for the text file (optional). Defaults to system locale. - name: simple echo # A second workflow. Notice the starting `-` which means command: "echo moo" # that workflow items are in a list. You can add as much workflows as you want files: - path: "moo.txt" should_exist: false # Whether a file should be there or not. (optional, if not given defaults to true) stdout: # Options for testing stdout (optional) contains: # List of strings which should be in stdout (optional) - "moo" must_not_contain: # List of strings that should NOT be in stout (optional) - "Cock a doodle doo" encoding: ASCII # Encoding for stdout (optional). Defaults to system locale. - name: mission impossible # Also failing workflows can be tested tags: # A list of tags that can be used to select which test - should fail # is run with pytest using the `--tag` flag. command: bash impossible.sh exit_code: 2 # What the exit code should be (optional, if not given defaults to 0) files: - path: "fail.log" # Multiple files can be tested for each workflow - path: "TomCruise.txt.gz" # Gzipped files can also be searched, provided their extension is '.gz' contains: - "starring" stderr: # Options for testing stderr (optional) contains: # A list of strings which should be in stderr (optional) - "BSOD error, please contact the IT crowd" must_not_contain: # A list of strings which should NOT be in stderr (optional) - "Mission accomplished!" encoding: UTF-16 # Encoding for stderr (optional). Defaults to system locale. - name: regex tests command: echo Hello, world stdout: contains_regex: # A list of regex patterns that should be in stdout (optional) - 'Hello.*' # Note the single quotes, these are required for complex regexes - 'Hello .*' # This will fail, since there is a comma after Hello, not a space must_not_contain_regex: # A list of regex patterns that should not be in stdout (optional) - '^He.*' # This will fail, since the regex matches Hello, world - '^Hello .*' # Complex regexes will break yaml if double quotes are used
For more information on how Python parses regular expressions, see the Python documentation.
Documentation for more advanced use cases including the custom tests can be found on our readthedocs page.