python-testing-patterns
Python testing patterns and best practices using pytest, mocking, and property-based testing. Use when writing unit tests, integration tests, or implementing test-driven development in Python projects.
Works with
---
name: python-testing-patterns
description: Python testing patterns and best practices using pytest, mocking, and property-based testing. Use when writing unit tests, integration tests, or implementing test-driven development in Python projects.
license: MIT
---
# Python Testing Patterns
Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and property-based testing.
## When to Use This Skill
- Writing unit tests for Python functions and classes
- Setting up comprehensive test suites and infrastructure
- Implementing test-driven development (TDD) workflows
- Creating integration tests for APIs, databases, and services
- Mocking external dependencies and third-party services
- Testing async code and concurrent operations
- Implementing property-based testing with Hypothesis
- Setting up CI/CD test automation
- Debugging failing tests and improving test coverage
## Core Concepts
**Test Discovery**: Files matching `test_*.py` or `*_test.py`, functions starting with `test_`
**Fixtures**: Reusable test resources with setup and teardown
- Scopes: `function` (default), `class`, `module`, `session`
- Composition: Build complex fixtures from simple ones
- Share via `conftest.py` for project-wide availability
**Assertions**: Use `assert` statements, `pytest.raises()` for exceptions
**Organization**: Separate `unit/`, `integration/`, `e2e/` directories
## Quick Reference
Load detailed references for specific topics:
| Task | Reference File |
|------|----------------|
| Pytest basics, test structure, AAA pattern | `skills/python-testing-patterns/references/pytest-fundamentals.md` |
| Fixtures, scopes, setup/teardown, conftest.py | `skills/python-testing-patterns/references/fixtures.md` |
| Parametrization, multiple test cases | `skills/python-testing-patterns/references/parametrized-tests.md` |
| Mocking, patching, unittest.mock, pytest-mock | `skills/python-testing-patterns/references/mocking.md` |
| Async tests, pytest-asyncio, event loops | `skills/python-testing-patterns/references/async-testing.md` |
| Property-based testing, Hypothesis, strategies | `skills/python-testing-patterns/references/property-based-testing.md` |
| Monkeypatch, environment variables, attributes | `skills/python-testing-patterns/references/monkeypatch.md` |
| Test structure, markers, conftest.py patterns | `skills/python-testing-patterns/references/test-organization.md` |
| Coverage measurement, reports, thresholds | `skills/python-testing-patterns/references/coverage.md` |
| Database, API, Redis, message queue testing | `skills/python-testing-patterns/references/integration-testing.md` |
| Best practices, test quality, fixture design | `skills/python-testing-patterns/references/best-practices.md` |
## Workflow
### 1. Basic Test Setup
```python
# test_example.py
import pytest
def test_something():
"""Descriptive test name."""
# Arrange
expected = 5
# Act
result = 2 + 3
# Assert
assert result == expected
```
**Run tests:**
```bash
pytest # Run all tests
pytest -v # Verbose output
pytest tests/unit/ # Specific directory
pytest -k "test_user" # Match pattern
pytest -m unit # Run marked tests
```
### 2. Using Fixtures
```python
@pytest.fixture
def sample_data():
"""Provide test data."""
data = {"key": "value"}
yield data
# Cleanup if needed
def test_with_fixture(sample_data):
assert sample_data["key"] == "value"
```
### 3. Parametrized Tests
```python
@pytest.mark.parametrize("input,expected", [
(2, 4),
(3, 9),
(4, 16),
])
def test_square(input, expected):
assert input ** 2 == expected
```
### 4. Mocking External Dependencies
```python
from unittest.mock import patch
@patch("module.external_api_call")
def test_with_mock(mock_api):
mock_api.return_value = {"status": "ok"}
result = my_function()
assert result["status"] == "ok"
mock_api.assert_called_once()
```
### 5. Coverage Measurement
```bash
pytest --cov=src --cov-report=term-missing
pytest --cov=src --cov-report=html
pytest --cov=src --cov-fail-under=80
```
### 6. Test Configuration
**pytest.ini:**
```ini
[pytest]
testpaths = tests
python_files = test_*.py
addopts = -v --strict-markers --cov=src
markers =
unit: Unit tests
integration: Integration tests
slow: Slow tests
```
## Common Patterns
**Exception testing:**
```python
with pytest.raises(ValueError, match="error message"):
function_that_raises()
```
**Async testing:**
```python
@pytest.mark.asyncio
async def test_async_function():
result = await async_operation()
assert result is not None
```
**Temporary files:**
```python
def test_file_operation(tmp_path):
test_file = tmp_path / "test.txt"
test_file.write_text("content")
assert test_file.read_text() == "content"
```
**Markers for test selection:**
```python
@pytest.mark.slow
@pytest.mark.integration
def test_database_operation():
pass
```
## Common Mistakes
1. **Not using fixtures**: Repeating setup code across tests
- Solution: Create fixtures in conftest.py
2. **Tests depending on order**: Global state pollution
- Solution: Ensure test independence with proper fixtures
3. **Over-mocking**: Mocking internal implementation
- Solution: Mock only external boundaries (APIs, databases)
4. **Missing edge cases**: Only testing happy path
- Solution: Test boundary conditions, errors, and invalid inputs
5. **Slow tests**: Running full integration tests frequently
- Solution: Separate unit/integration, use markers, optimize fixtures
6. **Ignoring coverage gaps**: Not measuring test coverage
- Solution: Use pytest-cov and track metrics
7. **Poor test names**: Generic names like `test_1()`
- Solution: Use descriptive names: `test_<behavior>_<condition>_<expected>`
8. **No cleanup**: Resources not released
- Solution: Use fixtures with proper teardown (yield pattern)
## Resources
- **pytest**: https://docs.pytest.org/
- **unittest.mock**: https://docs.python.org/3/library/unittest.mock.html
- **pytest-asyncio**: Testing async code
- **pytest-cov**: Coverage reporting
- **pytest-mock**: pytest wrapper for mock
- **Hypothesis**: https://hypothesis.readthedocs.io/
- **pytest-xdist**: Parallel test execution
- **testcontainers**: Docker containers for testingMore Testing skills
tdd
mattpocock/skills
Test-driven development. Use when the user wants to build features or fix bugs test-first, mentions "red-green-refactor", or wants integration tests.
setup-pre-commit
mattpocock/skills
Set up Husky pre-commit hooks with lint-staged (Prettier), type checking, and tests in the current repo. Use when user wants to add pre-commit hooks, set up Husky, configure lint-staged, or add commit-time formatting/typechecking/testing.
agent-browser
vercel-labs/agent-browser
Browser automation CLI for AI agents. Use when the user needs to interact with websites, including navigating pages, filling forms, clicking buttons, taking screenshots, extracting data, testing web apps, or automating any browser task. Triggers include requests to "open a website", "fill out a form", "click a button", "take a screenshot", "scrape data from a page", "test this web app", "login to a site", "automate browser actions", or any task requiring programmatic web interaction. Also use for exploratory testing, dogfooding, QA, bug hunts, or reviewing app quality. Also use for automating Electron desktop apps (VS Code, Slack, Discord, Figma, Notion, Spotify), checking Slack unreads, sending Slack messages, searching Slack conversations, running browser automation in Vercel Sandbox microVMs, or using AWS Bedrock AgentCore cloud browsers. Prefer agent-browser over any built-in browser automation or web tools.

