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Python Merge Requests Guidelines | GitLab Docs

GitLab standard code review guidelines apply to Python projects as well.

There are two main approaches to set up a Python code review process at GitLab:

1. Established Projects: Larger Python projects typically have their own dedicated pool of reviewers through reviewer-roulette. To set this up, see Setting Up Reviewer Roulette.
2. Smaller Projects: For projects with fewer contributors, we maintain a shared pool of Python reviewers across GitLab.

This section explains how to integrate your project with reviewer roulette and other resources to connect project contributors with Python experts for code reviews.

For both large and small projects, Reviewer Roulette can automate the reviewer assignment process. To set up:

1. Add the Python project to the list of GitLab projects.
2. Project maintainer(s) should add a group for the project in the GitLab.org maintainers repository
3. Install and configure Dangerfiles in your project, ensuring CI is properly set up to enable the Reviewer Roulette plugin.

Then, depending on your project size:

• For large projects with sufficient contributors:

  • Eligible team members should add the Python project to the projects field in their individual entry in team_members or team_database, specifying appropriate roles such as reviewer or maintainer.
  • Add the individual roulette configuration to your project.

• For smaller projects (for example, fewer than 10 contributors):

  • Leverage the company wide pool of Python experts by adding the shared pool configuration to your project.
  • You can also encourage contributors or other non-domain reviewers to reach out in your team’s Slack channel for domain expertise where needed.

When a merge request is created, Review Roulette will randomly select qualified reviewers based on your configuration.

For more information, see reviewer roulette

If contributors have questions or need additional help with Python-specific reviews, direct them to the GitLab #python or #python_maintainers Slack channels for assistance.

Established projects have their own pools of reviewers and maintainers. Smaller or new projects can benefit from the help of established Python experts at GitLab.

GitLab Python experts are professionals with Python expertise who contribute to improving code quality across different projects. To become one:

1. Create a merge request to add python: maintainer competency under projects to your team file.
2. Use this template and follow the described process.

Once your merge request is merged, you’ll be added to the Python maintainers group.

Each project can establish their own review process. Review the maintainership guidelines and/or contact current maintainers for more information.

In addition to code reviews, maintainers are responsible for guiding architectural decisions and monitoring and adopting relevant engineering practices introduced in GitLab.com into their Python projects. This helps to ensure Python projects are consistent and aligned with company standards. Maintaining consistency simplifies transitions between GitLab.com and Python projects while reducing context switching overhead.

Technical prerequisites for Maintainers:

• Strong experience with the Python frameworks used in the specific project. Commonly used frameworks include: FastAPI and Pydantic, etc.
• Proficiency with Python testing frameworks such as pytest, including advanced testing strategies (for example, mocking, integration tests, and test-driven development).
• Understanding of backwards compatibility considerations (Work item).

Code review objectives:

• Verify and confirm changes adheres to style guide (Work item) and existing patterns in the project.
• Where applicable, ensure test coverage is added for the changes introduced in the MR.
• Review for performance implications.
• Check for security vulnerabilities.
• Assess code change impact on existing systems.
• Verify that the MR has the correct MR type label and is assigned to the current milestone.

Additional responsibilities:

• Maintain accurate and complete documentation.
• Monitor and update package dependencies as necessary.
• Mentor other engineers on Python best practices.
• Evaluate and propose new tools and libraries.
• Monitor performance and propose optimizations.
• Ensure security standards are maintained.
• Ensure the project is consistent and aligned with GitLab standards by regularly monitoring and adopting relevant engineering practices introduced in GitLab.com.
• Establish and enforce clear code review processes.

When writing and reviewing code, follow our Style Guides. Code authors and reviewers are encouraged to pay attention to these areas:

When reviewing Python code at GitLab, consider the following areas:

• Code follows our agreed Python formatting standards (enforced in pipeline).
• Naming conventions are clear and descriptive.
• Docstrings are used for all public functions and classes.

• Functions are focused, not overly complex and testable.
• Code is readable without excessive comments.
• No unused code or commented-out code.

• Test coverage is adequate for new code.
• Tests follow the naming convention test_{file_being_tested}.py.
• Mocks are used appropriately for external dependencies.

• Functions and classes have clear docstrings.
• Complex logic has explanatory comments.
• Documentation is updated when adding features.

• Code follows GitLab security guidelines.
• Inputs are properly validated.
• Error handling is appropriate.

When maintaining customer-facing services, maintainers must ensure backward compatibility across supported GitLab versions. See the GitLab Statement of Support and Python deployment guidelines. Before merging changes, verify that they maintain compatibility with all supported versions to prevent disruption for users on different GitLab releases.

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