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Python Testing Patterns

Seth HobsonCommunityCreated by Seth Hobson

  • Skill
  • Guidelines
  • Software development
  • MIT
  • Low risk

From the author

Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.
— the description by Seth Hobson

AutoGineer summary

Written by AutoGineer from the skill’s own files, not by the author

This skill provides a structured approach to testing Python applications. It covers essential testing concepts including the Arrange-Act-Assert pattern, test isolation, and coverage analysis. The content includes practical examples for unit, integration, and functional testing, alongside advanced techniques such as mocking, parameterization, async testing, and environment manipulation using pytest.

What it does

  • Explains core testing concepts like test types and the AAA structure.
  • Provides patterns for organizing test suites and naming conventions.
  • Demonstrates how to use fixtures for setup and teardown operations.
  • Shows how to mock dependencies and control time in tests.
  • Covers advanced testing scenarios like async code and environment variables.
  • Details how to generate coverage reports and use test markers.

When to use it

  • When writing unit or integration tests for Python code.
  • When setting up test infrastructure or configuring test suites.
  • When implementing test-driven development practices.
  • When needing to mock external services or handle time-dependent logic.
  • When debugging failing tests or improving test coverage.

Advantages

  • Promotes consistent test organization and naming.
  • Provides reusable patterns for common testing challenges.
  • Includes clear examples for complex scenarios like async and environment mocking.
  • Helps maintain test independence and clean state management.

Usage examples

“How do I structure my pytest tests using the AAA pattern?”
The agent explains the Arrange, Act, and Assert phases and provides a code example demonstrating how to set up data, execute the function, and verify the result.
“Show me how to mock a service that has retry logic.”
The agent provides a code example using unittest.mock to simulate transient failures and verify that the service retries the expected number of times.
“How can I test code that depends on the current time?”
The agent demonstrates the use of the freezegun library to freeze time, allowing for predictable assertions in time-dependent logic.
“How do I run tests with coverage reporting?”
The agent provides the necessary commands to install pytest-cov and run tests with coverage, including how to generate HTML reports and set thresholds.

Install

  1. Download the skill as a ZIP:

    https://autogineer.com/agent-skills/wshobson/python-testing-patterns/download
  2. Unzip it into the cross-client skills folder of your project:

    mkdir -p .agents/skills && unzip python-testing-patterns.zip -d .agents/skills

Documentation by Seth Hobson

Python Testing Patterns

Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and test-driven development practices.

When to Use This Skill

  • Writing unit tests for Python code

  • Setting up test suites and test infrastructure

  • Implementing test-driven development (TDD)

  • Creating integration tests for APIs and services

  • Mocking external dependencies and services

  • Testing async code and concurrent operations

  • Setting up continuous testing in CI/CD

  • Implementing property-based testing

  • Testing database operations

  • Debugging failing tests

Core Concepts

1. Test Types
  • Unit Tests: Test individual functions/classes in isolation

  • Integration Tests: Test interaction between components

  • Functional Tests: Test complete features end-to-end

  • Performance Tests: Measure speed and resource usage

2. Test Structure (AAA Pattern)
  • Arrange: Set up test data and preconditions

  • Act: Execute the code under test

  • Assert: Verify the results

3. Test Coverage
  • Measure what code is exercised by tests

  • Identify untested code paths

  • Aim for meaningful coverage, not just high percentages

4. Test Isolation
  • Tests should be independent

  • No shared state between tests

  • Each test should clean up after itself

Quick Start

# test_example.py
def add(a, b):
    return a + b

def test_add():
    """Basic test example."""
    result = add(2, 3)
    assert result == 5

def test_add_negative():
    """Test with negative numbers."""
    assert add(-1, 1) == 0

# Run with: pytest test_example.py

Detailed patterns and worked examples

Detailed pattern documentation lives in references/details.md. Read that file when the navigation tier above is insufficient.

Testing Best Practices

Test Organization
# tests/
#   __init__.py
#   conftest.py           # Shared fixtures
#   test_unit/            # Unit tests
#     test_models.py
#     test_utils.py
#   test_integration/     # Integration tests
#     test_api.py
#     test_database.py
#   test_e2e/            # End-to-end tests
#     test_workflows.py
Test Naming Convention

A common pattern: test_<unit>_<scenario>_<expected_outcome>. Adapt to your team's preferences.

# Pattern: test_<unit>_<scenario>_<expected>
def test_create_user_with_valid_data_returns_user():
    ...

def test_create_user_with_duplicate_email_raises_conflict():
    ...

def test_get_user_with_unknown_id_returns_none():
    ...

# Good test names - clear and descriptive
def test_user_creation_with_valid_data():
    """Clear name describes what is being tested."""
    pass

def test_login_fails_with_invalid_password():
    """Name describes expected behavior."""
    pass

def test_api_returns_404_for_missing_resource():
    """Specific about inputs and expected outcomes."""
    pass

# Bad test names - avoid these
def test_1():  # Not descriptive
    pass

def test_user():  # Too vague
    pass

def test_function():  # Doesn't explain what's tested
    pass
Testing Retry Behavior

Verify that retry logic works correctly using mock side effects.

from unittest.mock import Mock

def test_retries_on_transient_error():
    """Test that service retries on transient failures."""
    client = Mock()
    # Fail twice, then succeed
    client.request.side_effect = [
        ConnectionError("Failed"),
        ConnectionError("Failed"),
        {"status": "ok"},
    ]

    service = ServiceWithRetry(client, max_retries=3)
    result = service.fetch()

    assert result == {"status": "ok"}
    assert client.request.call_count == 3

def test_gives_up_after_max_retries():
    """Test that service stops retrying after max attempts."""
    client = Mock()
    client.request.side_effect = ConnectionError("Failed")

    service = ServiceWithRetry(client, max_retries=3)

    with pytest.raises(ConnectionError):
        service.fetch()

    assert client.request.call_count == 3

def test_does_not_retry_on_permanent_error():
    """Test that permanent errors are not retried."""
    client = Mock()
    client.request.side_effect = ValueError("Invalid input")

    service = ServiceWithRetry(client, max_retries=3)

    with pytest.raises(ValueError):
        service.fetch()

    # Only called once - no retry for ValueError
    assert client.request.call_count == 1
Mocking Time with Freezegun

Use freezegun to control time in tests for predictable time-dependent behavior.

from freezegun import freeze_time
from datetime import datetime, timedelta

@freeze_time("2026-01-15 10:00:00")
def test_token_expiry():
    """Test token expires at correct time."""
    token = create_token(expires_in_seconds=3600)
    assert token.expires_at == datetime(2026, 1, 15, 11, 0, 0)

@freeze_time("2026-01-15 10:00:00")
def test_is_expired_returns_false_before_expiry():
    """Test token is not expired when within validity period."""
    token = create_token(expires_in_seconds=3600)
    assert not token.is_expired()

@freeze_time("2026-01-15 12:00:00")
def test_is_expired_returns_true_after_expiry():
    """Test token is expired after validity period."""
    token = Token(expires_at=datetime(2026, 1, 15, 11, 30, 0))
    assert token.is_expired()

def test_with_time_travel():
    """Test behavior across time using freeze_time context."""
    with freeze_time("2026-01-01") as frozen_time:
        item = create_item()
        assert item.created_at == datetime(2026, 1, 1)

        # Move forward in time
        frozen_time.move_to("2026-01-15")
        assert item.age_days == 14
Test Markers
# test_markers.py
import pytest

@pytest.mark.slow
def test_slow_operation():
    """Mark slow tests."""
    import time
    time.sleep(2)


@pytest.mark.integration
def test_database_integration():
    """Mark integration tests."""
    pass


@pytest.mark.skip(reason="Feature not implemented yet")
def test_future_feature():
    """Skip tests temporarily."""
    pass


@pytest.mark.skipif(os.name == "nt", reason="Unix only test")
def test_unix_specific():
    """Conditional skip."""
    pass


@pytest.mark.xfail(reason="Known bug #123")
def test_known_bug():
    """Mark expected failures."""
    assert False


# Run with:
# pytest -m slow          # Run only slow tests
# pytest -m "not slow"    # Skip slow tests
# pytest -m integration   # Run integration tests
Coverage Reporting
# Install coverage
pip install pytest-cov

# Run tests with coverage
pytest --cov=myapp tests/

# Generate HTML report
pytest --cov=myapp --cov-report=html tests/

# Fail if coverage below threshold
pytest --cov=myapp --cov-fail-under=80 tests/

# Show missing lines
pytest --cov=myapp --cov-report=term-missing tests/

For advanced patterns (async testing, monkeypatching, property-based testing, database testing, CI/CD integration, and configuration), see references/advanced-patterns.md

Files

Requirements and compatibility

Works with: Claude Code, Claude apps, OpenAI Codex, GitHub Copilot, Cursor, Gemini CLI, Kiro, OpenCode, Goose, Amp, Roo Code, JetBrains Junie, Factory Droid, Devin (ex-Windsurf), Mistral Vibe, OpenHands, Letta

“Works with” means the tool reads the open Agent Skills format; a skill written for one tool may use features others lack.

Needs: Needs Python

Security

What our scanner noticed· Low risk

  • Instructions that use the network

A static scan is not a guarantee. Skills are third-party content: review a skill before you let an agent use it.

Attribution and licence

Created by
Seth Hobson
Publisher
Seth Hobson (Community)
Source
wshobson/agents · plugins/python-development/skills/python-testing-patterns · commit 4bde316
Licence
MIT License (redistribution allowed)
  • LICENSE (added by AutoGineer from LICENSE)
  • ATTRIBUTION.md (written by AutoGineer)
Synced

AutoGineer is not affiliated with or endorsed by Seth Hobson or Seth Hobson.

Download ZIP

The ZIP holds the skill’s files, its licence files and an ATTRIBUTION.md. Download python-testing-patterns.zip