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Development

Environment

For local development, it is required to have Python 3.8 (or a later version) installed.

It is recommended to set up a virtual environment while developing this package to isolate your development environment, however, due to the many varied ways Python can be installed and virtual environments can be set up, this is left up to the developers to do themselves.

One recommended way is with the built-in venv module:

python3 -m venv .venv
source .venv/bin/activate

To improve on the experience, you can use pyenv to have an environment with a pinned Python version, and direnv to automatically activate/deactivate the environment when you enter/exit the project folder.

Dependencies

To install this package and its development dependencies, run make install-dev.

Code checking

To run all our code checking tools together, just run make check-code.

Linting

We use ruff for linting to to analyze the code for potential issues and enforce uniformed code style. See the pyproject.toml for its configuration. To run the linting, just run make lint.

Formatting

We use ruff for automated code formatting. It formats the code to follow uniformed code style and addresses auto-fixable linting issues. See the pyproject.toml for its configuration. To run the formatting, just run make format.

Type checking

We use mypy for type checking. See the mypy.ini for its configuration. To run the type checking, just run make type-check.

Unit tests

We use pytest as a testing framework with many plugins. See the pyproject.toml for both its configuration and the list of installed plugins. To run unit tests execute make unit-tests. To run unit tests with HTML coverage report execute make unit-tests-cov.

Integration tests

We have integration tests which build and run actors using the Python SDK on the Apify Platform. To run these tests, you need to set the APIFY_TEST_USER_API_TOKEN environment variable to the API token of the Apify user you want to use for the tests, and then start them with make integration-tests.

If you want to run the integration tests on a different environment than the main Apify Platform, you need to set the APIFY_INTEGRATION_TESTS_API_URL environment variable to the right URL to the Apify API you want to use.

Documentation

We use the Google docstring format for documenting the code. We document every user-facing class or method, and enforce that using the flake8-docstrings library.

The documentation is then rendered from the docstrings in the code, using pydoc-markdown and some heavy post-processing, and from Markdown documents in the docs folder in the docs branch, and then rendered using Docusaurus and published to GitHub pages.

Release process

Publishing new versions to PyPI happens automatically through GitHub Actions.

On each commit to the master branch, a new beta release is published, taking the version number from pyproject.toml and automatically incrementing the beta version suffix by 1 from the last beta release published to PyPI.

A stable version is published when a new release is created using GitHub Releases, again taking the version number from pyproject.toml. The built package assets are automatically uploaded to the GitHub release.

If there is already a stable version with the same version number as in pyproject.toml published to PyPI, the publish process fails, so don't forget to update the version number before releasing a new version. The release process also fails when the released version is not described in CHANGELOG.md, so don't forget to describe the changes in the new version there.

Beta release checklist

Beta release happens automatically after you merge a pull request or add a direct commit to the master branch. Before you do that check the following:

  • Make sure that in the pyproject.toml a project version is set to the latest non-published version.
  • Describe your changes to the CHANGELOG.md in the section with the latest non-published version.

Production release checklist

Production release happens after the GitHub release is created. Before you do that check the following:

  • Make sure here that the beta release with the latest commit is successfully deployed.
  • Make sure that all the changes that happened from the last production release are described in the CHANGELOG.md (it's okay to skip DX related changes, repo setup etc).
  • When drafting a new GitHub release:
    • Create a new tag in the format of v1.2.3 targeting the master branch.
    • Fill in the release title in the format of 1.2.3.
    • Copy the changes from the CHANGELOG.md and paste them into the release description. Make sure that all changes are properly categorized using headlines (Added, Fixed or Internal changes).
    • Check the "Set as the latest release" option.

Currently, there is no explicit approval process, so when you are done with the checklist, proceed with the release.

Once released, manually bump the version in pyproject.toml (PR example).

Maintanance

Removing Support for an outdated Python version

  • Todo: Fill in once Python 3.8 is deprecated.

Adding support for a new Python version

  1. Firstly, ensure that the package ( apify-sdk-python, apify-client-python, apify-shared-python ) is compatible with the new Python version. Both in our code base and the dependencies we use. Then, release a new version of the package.

  2. Next, build and publish the new versions of Python base Docker images.

  3. Integrate the new Python version into the CI/CD workflows of existing Python projects ( apify-sdk-python, apify-client-python, apify-shared-python, actor-templates ).

    • For inspiration, see the PR apify/apify-sdk-python#124, where support for Python 3.12 was added to the CI/CD of the Apify Python SDK.