Evaluate and Enhance Our CI Pipeline
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Is our CI pipeline complete?
While our current Continuous Integration (CI) pipeline is robust and performing well, I think there's always room for us to step back and evaluate if there's more we could do. Currently, the pre-commit workflow follows this sketch:
repos:
...
hooks:
- id: mypy
...
hooks:
- id: yapf
...
hooks:
- id: black
...
hooks:
- id: flake8
...
hooks:
- id: isort
language_version: python3.9 # Replace with your Python version
...
hooks:
- id: pytest
...
- id: config_validation
name: Config Validation
entry: python -m automata.cli.scripts.run_config_validation
language: system
types: [python]
And we have corresponding GitHub Actions to ensure these pre-commits are satisfied.
While we're covering many bases, it's worth considering if there are other tools or checks we could benefit from. Here are some possibilities I've considered:
- Code Coverage Checks: Consider adding a tool like coverage or codecov to measure the extent to which our codebase is covered by our tests. This would help us ensure we're thoroughly testing our code and identify any areas that might need more testing.
- Security Checks: A tool like bandit or safety could help us catch any potential security vulnerabilities in our codebase.
- Docstring Checks: We could use a tool like pydocstyle to check the quality and consistency of our docstrings.
- Dependency Checks: We could add a tool like pipdeptree or safety to check for any dependency conflicts or security vulnerabilities in our dependencies.
Of course, these are just ideas, and the benefits should outweigh the added complexity for each tool we consider adding. I'm open to hearing everyone's thoughts on these suggestions or if there are other tools you think would be beneficial.