tomlkit VS coveragepy

I like to use TOML files. I find the syntax to be more palatable than YAML, and you can load them quite easily with tomlkit. I believe there's a PEP to add a parser to the standard library too, since they're used for pyproject.toml now.

Coverage.py is the go-to tool for measuring code coverage of Python programs. Once installed, you can use it with either unittest or pytest.

Code Coverage Analysis assess the code portions tested by the current test suites without altering the code.

The PLASMA lab @ UMass Amherst (home of the Scalene profiler) has released a new version of Slipcover, a super fast code coverage tool for Python. It is by far the fastest code coverage tool: in our tests, its average slowdown is just 5% (compare to the widely used coverage.py, average slowdown 218%!). The latest release performs both line and branch coverage with virtually no overhead. Use it to dramatically speed up your tests and continuous integration!

Tests ensure the tested behavior is maintained. It's up to the developers to write tests with sufficient coverage. Determining which lines of code on your project are covered by tests is easily quantifiable using tooling. E.g. https://coverage.readthedocs.io/

Taking the idea further, if you build robust tests for your API, you could use a dynamic code analyzer like coverage or figleaf to identify and delete unused functions.

coverage

FWIW, ternary expressions aren't properly detected by coverage: https://github.com/nedbat/coveragepy/issues/509