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testland/mutmut-mutation

Configures mutmut for Python mutation testing - `pip install mutmut`, runs via `mutmut run`, browses results via `mutmut browse` or `mutmut results`, applies surviving mutants to disk via `mutmut apply {id}`, suppresses with `# pragma: no mutate` annotations. Configures via `setup.cfg` / `pyproject.toml` with `source_paths` + per-test selection. Use for Python codebases needing mutation-quality verification of pytest / unittest suites.

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SKILL.md

name:
mutmut-mutation
description:
Configures mutmut for Python mutation testing - `pip install mutmut`, runs via `mutmut run`, browses results via `mutmut browse` or `mutmut results`, applies surviving mutants to disk via `mutmut apply {id}`, suppresses with `# pragma: no mutate` annotations. Configures via `setup.cfg` / `pyproject.toml` with `source_paths` + per-test selection. Use for Python codebases needing mutation-quality verification of pytest / unittest suites.

mutmut-mutation

Overview

Per mutmut-docs:

"Mutmut is a mutation testing system for Python, with a strong focus on ease of use." (mutmut-docs)

Key features per mutmut-docs:

  • "Found mutants can be applied on disk with a simple command making it very easy to work with the results"
  • "Remembers work that has been done, so you can work incrementally"
  • "Knows which tests to execute, speeding up mutation testing"
  • "Interactive terminal based UI"
  • "Parallel and fast execution"

When to use

  • A Python codebase has a pytest / unittest suite with high coverage and the team wants to verify the assertions.
  • A specific module needs mutation-quality verification before shipping a release.
  • The team is debating "should we add another test?" - surviving mutants tell you where.

How to use

  1. pip install mutmut and confirm the pytest / unittest suite is green before mutating.
  2. Scope the run in setup.cfg or pyproject.toml (source_paths + test selection) so only project source is mutated.
  3. Run mutmut run - the first run is slow; state is cached so later runs are incremental.
  4. Read the score with mutmut results; open survivors interactively with mutmut browse.
  5. For each survivor, write a test that kills it; verify with mutmut apply <id>, re-run that test, then revert.
  6. Reserve # pragma: no mutate for genuinely unreachable lines only.
  7. Wire a weekly full run plus PR-scoped runs into CI, uploading mutmut results as an artifact.

Step 1 - Install + first run

Per mutmut-docs:

pip install mutmut
mutmut run

mutmut run "automatically detects test folders ('tests' or 'test') and locates source code" (mutmut-docs).

The first run is slow (full suite per mutant); subsequent runs use the cached state.

Step 2 - Configure

Per mutmut-docs, settings go in setup.cfg or pyproject.toml:

[mutmut]
source_paths=src/
pytest_add_cli_args_test_selection=tests/

Or in pyproject.toml:

[tool.mutmut]
source_paths = ["src/"]
pytest_add_cli_args_test_selection = "tests/"

Common config:

SettingUse
source_pathsWhich files to mutate.
pytest_add_cli_args_test_selectionWhich tests to run per mutant.
runnerpytest (default) or python -m unittest.
tests_dirOverride auto-detected test directory.
do_not_mutateRegex of files / lines to skip.

Step 3 - Browse results

Per mutmut-docs, "Results are explored via mutmut browse, where mutants can be retested or written to disk using mutmut apply <mutant>."

mutmut browse        # interactive TUI
mutmut results       # summary table
mutmut show <id>     # show specific mutant diff

Output:

Total: 142
Killed: 119 (83.8%)
Survived: 23 (16.2%)
Timeout: 0
Suspicious: 0

Step 4 - Mutators

Per mutmut-docs, common mutations include:

"Integer literals are changed by adding 1. So 0 becomes 1, 5 becomes 6, etc."

< becomes <=

break converts to continue and vice versa

Other mutators: arithmetic (+-), comparison flipping, constant replacement, statement removal.

Step 5 - Suppress with pragmas

Per mutmut-docs:

Use code comments to skip specific areas:

  • # pragma: no mutate (single line)
  • # pragma: no mutate block (indentation blocks)
  • # pragma: no mutate start/end (arbitrary ranges)
def divide(a, b):
    if b == 0:                  # pragma: no mutate
        raise ZeroDivisionError("intentional unreachable")
    return a / b

Use sparingly - each pragma is a confession that a line isn't mutation-tested. Reviewable in PRs.

Step 6 - Apply a survivor

Once a surviving mutant is identified, write a test that catches it. To verify the test catches this specific mutation:

mutmut apply <mutant-id>     # writes the mutant to disk
pytest tests/affected_test.py # the new test should fail
git checkout src/             # revert the mutant

This proves the test catches the specific bug class.

Step 7 - CI integration

- name: Mutation testing
  if: github.event_name == 'schedule'   # weekly
  run: |
    pip install -e '.[dev]'
    pip install mutmut
    mutmut run --max-children 4
- name: Surface results
  if: always()
  run: mutmut results > mutation-summary.txt
- uses: actions/upload-artifact@v4
  if: always()
  with:
    name: mutation-results
    path: mutation-summary.txt

For PRs, mutmut doesn't have native incremental mode; use source_paths to scope to changed files via a wrapper script:

CHANGED=$(git diff --name-only origin/main...HEAD | grep '^src/')
mutmut run --paths-to-mutate "$CHANGED"

Worked example

A team wants to verify the pytest suite for src/discounts.py before a release.

  1. Scope the run in setup.cfg:
    [mutmut]
    source_paths=src/discounts.py
    pytest_add_cli_args_test_selection=tests/test_discounts.py
  2. mutmut run, then mutmut results:
    Total: 142
    Killed: 119 (83.8%)
    Survived: 23 (16.2%)
  3. mutmut browse shows a survivor: the boundary if total > 100: mutated to if total >= 100: - the suite never exercises total == 100.
  4. Add a test for the no-discount path at total == 100, then confirm it catches the mutant:
    mutmut apply <id>                 # id from the browse listing
    pytest tests/test_discounts.py    # now fails on the mutated line
    git checkout src/                 # revert the mutant
  5. Re-running mutmut run shows the mutant killed and the score up by one mutant.

Pitfalls and limitations

Anti-patterns (pragma escape hatches, full-mutation-per-PR, third-party source_paths, unrealistic gates) and mutmut's limitations (slow runs, no native PR diff scoping, equivalent mutants) are catalogued in references/mutmut-pitfalls.md.

References

  • md - mutmut overview: ease of use, incremental work, intelligent test selection, parallel execution, configuration via setup.cfg / pyproject.toml, mutator examples (integer literals, comparison flipping, break/continue).
  • stryker-mutation, stryker-net-mutation, pitest-mutation, mull-mutation - per-language siblings.

SKILL.md

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