---
id: diff-cover
version: "10.5.0"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# diff-cover — Run coverage and linting reports on diffs

License: permissive · Maintenance: active · Popularity: top 1,000 on PyPI

## Install

pip install diff-cover
uv add diff-cover
poetry add diff-cover

## Description

diff-cover |pypi-version| |conda-version| |build-status|
========================================================================================

Automatically find diff lines that need test coverage.
Also finds diff lines that have violations (according to tools such
as pycodestyle, pyflakes, flake8, or pylint).
This is used as a code quality metric during code reviews.

Overview
--------

Diff coverage is the percentage of new or modified
lines that are covered by tests.  This provides a clear
and achievable standard for code review: If you touch a line
of code, that line should be covered.  Code coverage
is *every* developer's responsibility!

The ``diff-cover`` command line tool compares an XML coverage report
with the output of ``git diff``.  It then reports coverage information
for lines in the diff.

Currently, ``diff-cover`` requires that:

- You are using ``git`` for version control.
- Your test runner generates coverage reports in Cobertura, Clover
  or JaCoCo XML format, or LCov format.

Supported XML or LCov coverage reports can be generated with many coverage tools,
including:

- Cobertura__ (Java)
- Clover__ (Java)
- JaCoCo__ (Java)
- coverage.py__ (Python)
-...

## AI interpretation — verify before relying

Compares test coverage and code quality reports against git diffs to measure coverage on only the lines you changed, supporting multiple coverage formats (Cobertura, Clover, JaCoCo, LCov) and quality checkers (pycodestyle, flake8, pylint, ruff).

Verdict: Production-stable tool for enforcing test coverage on code changes during review. Actively maintained, permissive license, low install friction, and no known vulnerabilities. Supports Python 3.10–3.14 and integrates with standard coverage and linting tools.

[View on SkillFed](https://skillfed.io/packages/diff-cover) · [View on PyPI](https://pypi.org/project/diff-cover/)