DEV Community

keploy
keploy

Posted on

2

Understanding python coverage with practically

Image description

Python Coverage refers to measuring which parts of your Python code are being executed during testing. It is a critical tool for ensuring comprehensive test coverage, helping developers understand which lines of code are tested and which are not. Here’s a deeper dive into how to use Python Coverage effectively:
Getting Started with Python Coverage

  1. Installation You can install the coverage module using pip: bash Copy code pip install coverage
  2. Running Tests with Coverage To measure code coverage, you run your tests through the coverage tool. Here’s a basic example: bash Copy code coverage run -m unittest discover This command runs all tests discovered by unittest while tracking code coverage.
  3. Generating Coverage Report After running tests, you can generate a coverage report. Coverage provides different report formats, including terminal output, HTML, and XML. Here’s how to generate a simple text report: bash Copy code coverage report For a more detailed HTML report, use: bash Copy code coverage html This will create an htmlcov directory with the coverage report. You can open index.html in a browser to view the report.
  4. Configuring Coverage You can configure coverage settings in a .coveragerc file. Here’s an example configuration: ini Copy code [run] branch = True source = my_package

[report]
show_missing = True
• branch: Ensures branch coverage is measured.
• source: Specifies the source code directories.
• show_missing: Displays lines that were not executed.

  1. Advanced Usage • Excluding Files: To exclude files or directories from coverage, use the omit option in the .coveragerc file: ini Copy code [run] omit = /tests/ /migrations/ • Combining Coverage Data: To merge coverage data from multiple runs, use: bash Copy code coverage combine • Checking Coverage Thresholds: Set minimum coverage thresholds to enforce code quality: bash Copy code coverage report --fail-under=80 This command will fail the build if the coverage is below 80%. Example Usage Here’s a complete example of running tests with coverage and generating a report: bash Copy code # Install coverage pip install coverage

Run tests with coverage

coverage run -m unittest discover

Generate a terminal report

coverage report

Generate an HTML report

coverage html
Conclusion
Python Coverage is a powerful tool for ensuring your tests cover all parts of your codebase. By integrating it into your development workflow, you can improve code quality, catch bugs early, and maintain high test coverage standards. Happy coding!

Heroku

Amplify your impact where it matters most — building exceptional apps.

Leave the infrastructure headaches to us, while you focus on pushing boundaries, realizing your vision, and making a lasting impression on your users.

Get Started

Top comments (0)

nextjs tutorial video

Youtube Tutorial Series 📺

So you built a Next.js app, but you need a clear view of the entire operation flow to be able to identify performance bottlenecks before you launch. But how do you get started? Get the essentials on tracing for Next.js from @nikolovlazar in this video series 👀

Watch the Youtube series

👋 Kindness is contagious

Dive into this thoughtful article, cherished within the supportive DEV Community. Coders of every background are encouraged to share and grow our collective expertise.

A genuine "thank you" can brighten someone’s day—drop your appreciation in the comments below!

On DEV, sharing knowledge smooths our journey and strengthens our community bonds. Found value here? A quick thank you to the author makes a big difference.

Okay