python-testing
Lets your agent create tests for Python code. It uses tools like pytest to ensure code works as expected, covering different scenarios.
What it does
This tool helps you write tests for your Python code. It uses a technique called TDD (Test-Driven Development) and tools like pytest to ensure your code works as expected.
When to use it
- ✓When writing new Python code.
- ✓When creating a test suite for a project.
- ✓When checking your code's test coverage.
Example of what to ask your AI
“How can I test a function that adds two numbers using TDD?”
Want more? Open the sections below.
How to use
The easiest way: copy the message below and paste it into Claude, ChatGPT, Cursor or any AI. It reads the skill and follows the instructions.
Skill link
Ready-to-paste message
How it works
You write a test that fails first, then write the minimal code to make it pass, and finally refactor the code. Tools like pytest help organize and run these tests.
Installation
Easiest way: copy the skill link and paste it into Claude, ChatGPT or Cursor asking it to follow the instructions.
In the terminal (Claude Code, Codex, Cursor), in your project folder:
npx skills add affaan-m/ECC --skill python-testingOr download just the file:
curl -L https://raw.githubusercontent.com/affaan-m/ECC/main/pi/core/skills/python-testing/SKILL.md -o SKILL.mdTechnical content (original SKILL.md)
Original text by the author, straight from GitHub.
Python Testing Patterns
Comprehensive testing strategies for Python applications using pytest, TDD methodology, and best practices.
When to Activate
- Writing new Python code (follow TDD: red, green, refactor)
- Designing test suites for Python projects
- Reviewing Python test coverage
- Setting up testing infrastructure
Core Testing Philosophy
Test-Driven Development (TDD)
Always follow the TDD cycle:
- RED: Write a failing test for the desired behavior
- GREEN: Write minimal code to make the test pass
- REFACTOR: Improve code while keeping tests green
# Step 1: Write failing test (RED)
def test_add_numbers():
result = add(2, 3)
assert result == 5
# Step 2: Write minimal implementation (GREEN)
def add(a, b):
return a + b
# Step 3: Refactor if needed (REFACTOR)
Coverage Requirements
- Target: 80%+ code coverage
- Critical paths: 100% coverage required
- Use
pytest --covto measure coverage
pytest --cov=mypackage --cov-report=term-missing --cov-report=html
pytest Fundamentals
Basic Test Structure
import pytest
def test_addition():
"""Test basic addition."""
assert 2 + 2 == 4
def test_string_uppercase():
"""Test string uppercasing."""
text = "hello"
assert text.upper() == "HELLO"
def test_list_append():
"""Test list append."""
items = [1, 2, 3]
items.append(4)
assert 4 in items
assert len(items) == 4
Assertions
# Equality
assert result == expected
# Inequality
assert result != unexpected
# Truthiness
assert result # Truthy
assert not result # Falsy
assert result is True # Exactly True
assert result is False # Exactly False
assert result is None # Exactly None
# Membership
assert item in collection
assert item not in collection
# Comparisons
assert result > 0
assert 0 <= result <= 100
# Type checking
assert isinstance(result, str)
# Exception testing (preferred approach)
with pytest.raises(ValueError):
raise ValueError("error message")
# Check exception message
with pytest.raises(ValueError, match="invalid input"):
raise ValueError("invalid input provided")
# Check exception attributes
with pytest.raises(ValueError) as exc_info:
raise ValueError("error message")
assert str(exc_info.value) == "error message"
Fixtures
Basic Fixture Usage
import pytest
@pytest.fixture
def sample_data():
"""Fixture providing sample data."""
return {"name": "Alice", "age": 30}
def test_sample_data(sample_data):
"""Test using the fixture."""
assert sample_data["name"] == "Alice"
assert sample_data["age"] == 30
Fixture with Setup/Teardown
@pytest.fixture
def database():
"""Fixture with setup and teardown."""
# Setup
db = Database(":memory:")
db.create_tables()
db.insert_test_data()
yield db # Provide to test
# Teardown
db.close()
def test_database_query(database):
"""Test database operations."""
result = database.query("SELECT * FROM users")
assert len(result) > 0
Fixture Scopes
# Function scope (default) - runs for each test
@pytest.fixture
def temp_file():
with open("temp.txt", "w") as f:
yield f
os.remove("temp.txt")
# Module scope - runs once per module
@pytest.fixture(scope="module")
def module_db():
db = Database(":memory:")
db.create_tables()
yield db
db.close()
# Session scope - runs once per test session
@pytest.fixture(scope="session")
def shared_resource():
resource = ExpensiveResource()
yield resource
resource.cleanup()
Fixture with Parameters
@pytest.fixture(params=[1, 2, 3])
def number(request):
"""Parameterized fixture."""
return request.param
def test_numbers(number):
"""Test runs 3 times, once for each parameter."""
assert number > 0
Using Multiple Fixtures
@pytest.fixture
def user():
return User(id=1, name="Alice")
@pytest.fixture
def admin():
return User(id=2, name="Admin", role="admin")
def test_user_admin_interaction(user, admin):
"""Test using multiple fixtures."""
assert admin.can_manage(user)
Autouse Fixtures
@pytest.fixture(autouse=True)
def reset_config():
"""Automatically runs before every test."""
Config.reset()
yield
Config.cleanup()
def test_without_fixture_call():
# reset_config runs automatically
…
FAQ
What is TDD?
TDD stands for Test-Driven Development. It's an approach where you write a test before writing the actual code, ensuring the code meets requirements.
What is pytest?
Pytest is a popular tool for writing and running tests in Python. It offers features like fixtures and parametrization to make testing more efficient.
What is code coverage?
Code coverage measures the percentage of your code that is executed by your tests. A common goal is to have at least 80% coverage.
Details
Original description by the author
Python testing strategies using pytest, TDD methodology, fixtures, mocking, parametrization, and coverage requirements. Use when writing pytest tests — fixtures, mocks, parametrization, or coverage.
repo: affaan-m/ECC
Popularity
- GitHub stars
- 280k
- Ranking position
- #104
- License
- MIT
- Updated
- 10/15/2026
Comments
- …
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