Coverage.py vs. Python vs. UndercoverCI vs. scikit-image Comparison Chart

Coverage.py is a tool for measuring code coverage of Python programs. It monitors your program, noting which parts of the code have been executed, then analyzes the source to identify code that could have been executed but was not. Coverage measurement is typically used to gauge the effectiveness of tests. It can show which parts of your code are being exercised by tests, and which are not. Use coverage run to run your test suite and gather data. However you normally run your test suite, and you can run your test runner under coverage. If your test runner command starts with “python”, just replace the initial “python” with “coverage run”. To limit coverage measurement to code in the current directory, and also find files that weren’t executed at all, add the source argument to your coverage command line. By default, it will measure line (statement) coverage. It can also measure branch coverage. It can tell you what tests ran which lines.

Actionable test coverage for Ruby and GitHub. Checks and insights to help your team ship healthy code while saving time on PR reviews. Stop focusing on getting to 100% test coverage. Reduce pull request defects by telling when the changed code is untested before it's deployed to production. The CI server runs tests and uploads coverage data to UndercoverCI. That's the only required post-install setup step! We scan the PR diff and verify local test coverage for each updated class, method, and block because an absolute percentage check is not enough. Reveal untested methods and blocks, find unused code paths, and improve your test suite. Install UndercoverCI's hosted GitHub App or explore the Ruby gems family. Fully-featured GitHub App code review integration with quick setup for your organization. The UndercoverCI project and related Ruby gems are entirely open-source and free to use locally and in your CI/CD workflows.