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 runs tests against pull requests submitted to the jupyter/docker-stacks repository.

We use the pytest module to run tests on the image. and pytest.ini in the tests folder define the environment in which tests are run. More info on pytest can be found here.

The actual image-specific test files are located in folders like tests/<somestack>/ (e.g., tests/docker-stacks-foundation/, tests/minimal-notebook/, etc.).


If your test is located in tests/<somestack>/, it will be run against the jupyter/<somestack> image and against all the [images inherited from this image](

Many tests make use of global pytest fixtures defined in the file.

Unit tests#

You can add a unit test if you want to run a Python script in one of our images. You should create a tests/<somestack>/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 can see an TensorFlow package example here.

Contributing New Tests#

Please follow the process below to add new tests:

  1. Add your test code to one of the modules in the tests/<somestack>/ 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:

    make build/<somestack>
    make test/<somestack>
  3. Submit 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.