/coveralls-python

Show coverage stats online via coveralls.io

Primary LanguagePythonMIT LicenseMIT

Coveralls for Python

Test Status:https://img.shields.io/circleci/project/github/TheKevJames/coveralls-python/master.svg?style=flat-square&label=CircleCI https://img.shields.io/github/actions/workflow/status/TheKevJames/coveralls-python/test.yml?branch=master&style=flat-square&label=Github%20Actions https://img.shields.io/coveralls/TheKevJames/coveralls-python/master.svg?style=flat-square&label=Coverage https://img.shields.io/readthedocs/coveralls-python?style=flat-square&label=Docs
Version Info:https://img.shields.io/pypi/v/coveralls.svg?style=flat-square&label=PyPI https://img.shields.io/conda/v/conda-forge/coveralls?style=flat-square&label=Conda https://img.shields.io/docker/v/thekevjames/coveralls?sort=semver&style=flat-square&label=Dockerhub https://img.shields.io/docker/v/thekevjames/coveralls?sort=semver&style=flat-square&label=Quay
Compatibility:https://img.shields.io/pypi/pyversions/coveralls.svg?style=flat-square&label=Python%20Versions https://img.shields.io/pypi/implementation/coveralls.svg?style=flat-square&label=Python%20Implementations
Downloads:https://img.shields.io/pypi/dm/coveralls.svg?style=flat-square&label=PyPI https://img.shields.io/conda/dn/conda-forge/coveralls?style=flat-square&label=Conda https://img.shields.io/docker/pulls/thekevjames/coveralls?style=flat-square&label=Dockerhub

coveralls.io is a service for publishing your coverage stats online. This package provides seamless integration with coverage.py (and thus pytest, nosetests, etc...) in your Python projects:

pip install coveralls
coverage run --source=mypkg -m pytest tests/
coveralls

For more information and usage instructions, see our documentation.

Version Compatibility

As of version 2.0, we have dropped support for end-of-life'd versions of Python and particularly old versions of coverage. Support for non-EOL'd environments is provided on a best-effort basis and will generally be removed once they make maintenance too difficult.

If you're running on an outdated environment with a new enough package manager to support version checks (see the PyPA docs), then installing the latest compatible version should do the trick automatically! If you're even more outdated than that, please pin to coveralls<2.

If you're in an outdated environment and experiencing an issue, you're welcome to open a ticket -- but please mention your environment! I'm willing to backport fixes to the 1.x branch if the need is great enough.