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Add comprehensive skills and documentation for various technologies
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# pytest
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## Description
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Python testing with pytest including fixtures, parametrization, and mocking.
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## When to Use
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- Writing Python tests
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- Test fixtures and setup
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- Mocking dependencies
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---
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## Core Patterns
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### Basic Tests
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```python
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import pytest
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def test_addition():
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assert 1 + 1 == 2
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def test_exception():
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with pytest.raises(ValueError, match="Invalid"):
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raise ValueError("Invalid input")
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```
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### Fixtures
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```python
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@pytest.fixture
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def user():
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return User(id=1, name="Test")
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@pytest.fixture
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def db_session():
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session = create_session()
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yield session
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session.close()
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def test_with_fixtures(user, db_session):
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db_session.add(user)
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assert user.id is not None
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```
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### Parametrization
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```python
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@pytest.mark.parametrize("input,expected", [
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("hello", "HELLO"),
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("world", "WORLD"),
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("", ""),
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])
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def test_uppercase(input, expected):
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assert input.upper() == expected
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```
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### Mocking
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```python
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from unittest.mock import Mock, patch
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def test_with_mock():
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service = Mock()
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service.get_user.return_value = {"id": 1}
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result = service.get_user(1)
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assert result["id"] == 1
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@patch('module.external_api')
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def test_with_patch(mock_api):
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mock_api.fetch.return_value = {"data": []}
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# Test code that uses external_api
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```
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## Best Practices
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1. Use fixtures for test setup
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2. Parametrize for multiple test cases
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3. Mock external dependencies
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4. Use descriptive test names
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5. Keep tests independent
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## Common Pitfalls
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- **Shared state**: Use fresh fixtures
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- **Over-mocking**: Only mock boundaries
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- **Slow tests**: Use markers for slow tests
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