python-testing

What I do

I help with three pytest workflows:

1. Write tests — generate focused, well-documented tests following project conventions
2. Check coverage — detect untested lines per file or folder
3. Bootstrap setup — install dev dependencies and apply recommended pytest configuration

Supporting files in this skill:

• assets/pytest.ini.template — ready-to-copy pytest configuration
• scripts/analyze_coverage.sh [path] — coverage analysis helper (whole src or specific folder/module)
  • Run from repo root as: ./.claude/skills/python-testing/scripts/analyze_coverage.sh [path]
  • Or use repo-root-safe path: "$(git rev-parse --show-toplevel)/.claude/skills/python-testing/scripts/analyze_coverage.sh" [path]

When to use me

Use when you want to:

• Write new tests for a module or feature
• Review and improve existing test quality
• Check coverage for a specific file, folder, or the whole project
• Bootstrap pytest for a new project (deps + config)

Example usage

"Write tests for the slugify function in src/utils/text.py" "Check coverage for src/services/payment.py" "Set up pytest for this project with coverage and async support"

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Conventions

Naming

• Files: test_<module_or_feature>.py
• Functions: test_<unit>__<behavior>__<condition>
• Mark every AI-generated test with @pytest.mark.ai

Docstring (required on every test)

Three-part format:

Purpose: What this test verifies.
Why this matters: Business or technical consequence if it breaks.
Setup summary: What's arranged and what's asserted.

Structure

• AAA pattern: Arrange – Act – Assert
• No conditionals or loops in test body (use parametrization)
• One responsibility per test

Fixtures

• Centralize in <domain>_fixtures.py
• Register via pytest_plugins = ["tests.fixtures"] in conftest.py
• Return typed objects; modify only what changes per test

Mocking

• Use mocker fixture (pytest-mock)
• Mock at the import boundary of the code under test
• Use spec=True for type safety

Coverage

• Target ≥ 80% for AI-authored tests
• ./.claude/skills/python-testing/scripts/analyze_coverage.sh — full src coverage
• ./.claude/skills/python-testing/scripts/analyze_coverage.sh src/services — coverage for a specific folder
• ./.claude/skills/python-testing/scripts/analyze_coverage.sh src/utils/text.py — coverage for a single file

Test scope & quality

• Test every public function and method you touched
• Cover happy paths plus negative scenarios, validation failures, and async edge cases
• Keep tests deterministic and isolated (clean up temp data, reset mocks)
• Mock only external dependencies using pytest-mock's mocker or hand-rolled fixtures
• Document why each test matters using the required docstring template

Test cases to include

• Happy path scenarios that reflect realistic inputs
• Edge cases such as empty inputs, boundary values, and timeout paths
• Error handling or exception flows (raise and capture specific exceptions)
• Dependency failures (e.g., network timeouts, missing files) while staying fast
• Concurrency and async behavior when applicable (use pytest.mark.asyncio or trio)

Test quality checklist

• Tested all public functions and methods touched by the change
• Covered happy path scenarios plus edge cases and negative flows
• Added or updated tests for error handling and exception cases
• Mocked external dependencies appropriately and kept mocks scoped
• Ensured all tests are deterministic and repeatable
• Kept tests focused (one assertion per behavior) and avoided loops/conditionals
• Documented each test with the three-part docstring
• Verified coverage with scripts/analyze_coverage.sh when changes affect multiple modules

Setup (new project)

1. Install dev dependencies:
   • uv: uv add --dev pytest pytest-cov pytest-asyncio pytest-mock
   • pip: pip install pytest pytest-cov pytest-asyncio pytest-mock
2. Copy assets/pytest.ini.template → pytest.ini at the project root
3. Add tests/ directory with an empty __init__.py and conftest.py