# Image Tests We greatly appreciate pull requests that extend the automated tests that vet the basic functionality of the Docker images. ## How the Tests Work A [GitHub Action workflow](https://github.com/jupyter/docker-stacks/blob/main/.github/workflows/docker.yml) runs tests against pull requests submitted to the `jupyter/docker-stacks` repository. We use `pytest` module to run tests on the image. `conftest.py` and `pytest.ini` in the `tests` folder define the environment in which tests are run. More info on `pytest` can be found [here](https://docs.pytest.org/en/latest/contents.html). The actual image-specific test files are located in folders like `tests//` (e.g., `tests/docker-stacks-foundation/`, `tests/minimal-notebook/`, etc.). ```{note} If your test is located in `tests//`, it will be run against `jupyter/` image and against all the [images inherited from this image](https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#image-relationships. ``` Many tests make use of global [pytest fixtures](https://docs.pytest.org/en/latest/reference/fixtures.html) defined in the [conftest.py](https://github.com/jupyter/docker-stacks/blob/main/tests/conftest.py) file. ## Unit tests If you want to run a python script in one of our images, you could add a unit test. You can do this by creating a `tests//units/` directory, if it doesn't already exist and put your file there. Files in this folder will be executed in the container when tests are run. You could see an [example for the TensorFlow package here](https://github.com/jupyter/docker-stacks/blob/HEAD/tests/tensorflow-notebook/units/unit_tensorflow.py). ## Contributing New Tests Please follow the process below to add new tests: 1. Add your test code to one of the modules in `tests//` directory or create a new module. 2. Build one or more images you intend to test and run the tests locally. If you use `make`, call: ```bash make build/ make test/ ``` 3. [Submit a pull request](https://github.com/PointCloudLibrary/pcl/wiki/A-step-by-step-guide-on-preparing-and-submitting-a-pull-request) (PR) with your changes. 4. Watch for GitHub to report a build success or failure for your PR on GitHub. 5. Discuss changes with the maintainers and address any issues running the tests on GitHub.