AgentSkillsCN

python-test-runner

使用 pytest 运行 Python 测试，并对测试结果进行分析。当用户请求运行测试、检查测试覆盖率，或验证 Python 代码的功能时，可选用此服务。

SKILL.md
--- frontmatter
name: python-test-runner
description: Run Python tests with pytest and analyze results. Use when the user asks to run tests, check test coverage, or verify Python code functionality.

Python Test Runner

Run Python tests using pytest with comprehensive output and analysis.

When to Use This Skill

Use this skill when you need to:

  • •Run unit tests for Python code
  • •Verify code functionality after changes
  • •Check test coverage
  • •Identify failing tests and their causes
  • •Run specific test files or test cases

Test Execution Process

1. Check for Test Files

First, identify test files in the project:

bash
# Look for test files
Get-ChildItem -Recurse -Filter "test_*.py"
Get-ChildItem -Recurse -Filter "*_test.py"

2. Run Tests with Pytest

Execute tests with verbose output:

bash
# Run all tests
pytest -v

# Run specific test file
pytest path/to/test_file.py -v

# Run specific test function
pytest path/to/test_file.py::test_function_name -v

# Run with coverage report
pytest --cov=. --cov-report=term-missing -v

3. Analyze Test Results

Review the output for:

  • •Passed tests - Verify expected functionality works
  • •Failed tests - Identify what broke and why
  • •Error details - Read tracebacks and assertion messages
  • •Coverage gaps - Identify untested code paths

Common Test Patterns

Running Tests After Code Changes

bash
# Run tests related to changed files
pytest -v path/to/modified_module/

# Run tests with immediate failure stopping
pytest -x -v

Debugging Failed Tests

bash
# Show local variables on failure
pytest -v --showlocals

# Enter debugger on failure
pytest -v --pdb

Test Selection

bash
# Run tests by keyword
pytest -v -k "test_user"

# Run tests by marker
pytest -v -m "slow"

Best Practices

  1. •Always activate virtual environment before running tests
  2. •Review test output carefully - don't just check pass/fail
  3. •Run tests after any code modification to catch regressions
  4. •Use coverage reports to identify untested code
  5. •Fix failing tests immediately - don't let them accumulate

Example Workflow

python
# 1. User makes code changes
# 2. You run: pytest -v
# 3. Analyze results and report to user
# 4. If tests fail, help debug by:
#    - Reading the traceback
#    - Identifying the problem
#    - Suggesting fixes

Integration with Development

This skill integrates well with:

  • •Code refactoring workflows
  • •Bug fixing processes
  • •Feature development
  • •Code review procedures