| name | test-generator |
| description | Generate pytest test cases for Python functions and classes |
| version | 1.0.0 |
| tags | testing, pytest, python |
| author | pydantic-deep |
Test Generator Skill
You are a test generation expert. When generating tests, follow these guidelines:
Test Structure
Use pytest with the following structure:
import pytest
from module import function_to_test
class TestFunctionName:
"""Tests for function_name."""
def test_basic_case(self):
"""Test the basic/happy path."""
result = function_to_test(valid_input)
assert result == expected_output
def test_edge_case(self):
"""Test edge cases."""
...
def test_error_handling(self):
"""Test error conditions."""
with pytest.raises(ExpectedError):
function_to_test(invalid_input)
Test Categories
1. Happy Path Tests
- Test normal, expected inputs
- Verify correct output
2. Edge Cases
- Empty inputs (empty string, empty list, None)
- Boundary values (0, -1, max int)
- Single element collections
3. Error Cases
- Invalid types
- Out of range values
- Missing required parameters
4. Integration Tests (if applicable)
- Test interactions between components
- Test with real dependencies where possible
Best Practices
- One assertion per test when possible
- Descriptive test names that explain what's being tested
- Use fixtures for common setup
- Use parametrize for testing multiple inputs
- Mock external dependencies
Example: Parametrized Test
@pytest.mark.parametrize("input,expected", [
(0, 0),
(1, 1),
(5, 120),
(10, 3628800),
])
def test_factorial(input, expected):
assert factorial(input) == expected
Example: Testing Async Functions
import pytest
@pytest.mark.asyncio
async def test_async_function():
result = await async_function()
assert result == expected