What are the best practices for setting coverage thresholds in CI?
An example of an AI chatbot conversation about Python coverage thresholds in CI/CD pipelines.
What are the best practices for setting coverage thresholds in CI?
Setting coverage thresholds in CI is crucial for maintaining code quality. Best practices include starting with a baseline of 70-80% coverage, gradually increasing it, and ensuring critical code paths are well-tested.
How do I enforce these thresholds in my CI pipeline?
You can enforce coverage thresholds by integrating tools like Coverage.py with your CI/CD pipeline. Configure your CI tool to fail the build if coverage falls below your set threshold.
What tools can help me measure code coverage?
Popular tools for measuring code coverage in Python include Coverage.py, pytest-cov, and Codecov. Each offers different features for reporting and integration.
Can I set different thresholds for different branches?
Yes, many CI tools allow you to set different coverage thresholds for different branches. This is useful for managing feature branches versus the main branch.
What should I do if my coverage is below the threshold?
If your coverage is below the threshold, review the uncovered code, write additional tests, and consider refactoring to improve testability.
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