python-pytest-creator

name	python-pytest-creator
description	Generate comprehensive pytest test files for Python using the test-generator-framework Use when this capability is needed.
metadata	{"author":"darellchua2"}

What I do

I implement a complete Python pytest test generation workflow by extending the test-generator-framework:

1. Analyze Python Codebase: Scan Python application to identify functions, classes, and modules
2. Detect Python Testing Setup: Identify pytest version and Poetry availability
3. Generate Python-Specific Scenarios: Create comprehensive test scenarios covering:
   • Happy paths, edge cases, and error handling
   • Python-specific patterns (decorators, context managers, async functions)
4. Delegate to Framework: Use test-generator-framework for core test generation workflow
5. Ensure Executability: Verify tests run with poetry run pytest or pytest

When to use me

Use this workflow when:

• You need to create comprehensive pytest test files for a Python application
• You want to ensure all edge cases and error conditions are covered
• You need tests that integrate with Poetry environments
• You prefer a systematic approach to test generation with user confirmation
• You want to ensure tests run correctly with your project's pytest version

Framework: This skill extends test-generator-framework for core test generation workflow, adding Python-specific functionality.

Prerequisites

• Python project with Poetry (pyproject.toml) or pip (requirements.txt)
• Pytest installed and configured in project
• Python source code to test
• Appropriate file permissions to create test files

Note: Poetry is optional. If Poetry is installed and pyproject.toml exists, tests will use poetry run pytest. Otherwise, tests will use pytest directly.

Steps

Step 1: Analyze Python Codebase

• Use glob patterns to find Python files: **/*.py
• Exclude test files: **/test_*.py, **/*_test.py, **/tests/**/*.py
• Read each Python file to identify:
  • Functions: def function_name(parameters):
  • Classes: class ClassName:
  • Methods: def method_name(self, parameters):
  • Async functions: async def async_function():
  • Decorators: @decorator_name
  • Context managers: with context_manager():
• Identify import statements to understand dependencies

Step 2: Detect Python Testing Setup

• Check for pyproject.toml or requirements.txt
• Determine pytest version and plugins
• Check for Poetry installation: poetry --version

Step 3: Generate Python-Specific Test Scenarios

Function Scenarios (Python-specific)

• Happy Path: Normal inputs with expected outputs
• Edge Cases: Empty strings, empty lists, None, 0, -1
• Error Cases: Invalid types, out of range values, missing parameters
• Python Features: Decorators, type hints, default arguments, *args/**kwargs

Class Scenarios

• Initialization: __init__ with valid/invalid parameters
• Method Behavior: Public/private method testing
• Special Methods: __str__, __repr__, __eq__, __hash__
• Class Methods: @classmethod, @staticmethod
• Property: Properties defined with @property
• Context Managers: __enter__ and __exit__ methods

Async Function Scenarios

• Awaitable Results: Normal async execution
• Concurrency: Multiple async calls with asyncio.gather()
• Error Handling: Async exceptions with pytest.raises()
• Timeout: Tests that should timeout

Step 4: Delegate to Test Generator Framework

Note: Core test generation workflow is provided by test-generator-framework. This skill focuses only on Python-specific aspects.

Refer to test-generator-framework for:

• Generic test file creation structure
• Framework detection and command determination
• User confirmation workflow
• Executability verification

Python-specific test file templates below extend the framework structure.

Step 5: Create Test Files (Python-specific)

"""
Test suite for <module_name>.py
Generated by python-pytest-creator skill
"""

import pytest
from <module_path> import <function_name>, <ClassName>

@pytest.fixture
def sample_instance():
    """Create a sample instance for testing"""
    return ClassName(param1, param2)

def test_function_name_happy_path(sample_instance):
    """Test that function_name works with valid inputs"""
    result = function_name(valid_input)
    assert result == expected_output

def test_function_name_edge_case_empty():
    """Test that function_name handles empty input"""
    result = function_name("")
    assert result is None

def test_function_name_error_invalid_type():
    """Test that function_name raises ValueError for invalid type"""
    with pytest.raises(ValueError):
        function_name(invalid_input)

@pytest.mark.parametrize("input,expected", [
    (1, "one"),
    (2, "two"),
])
def test_function_name_parametrized(input, expected):
    """Test function_name with multiple inputs"""
    result = function_name(input)
    assert result == expected

class TestClassName:
    """Test suite for ClassName"""
    
     ():
        
        instance = ClassName(param1, param2)
         instance.attribute == expected_value
    
     ():
        
        result = sample_instance.method_name(param)
         result == expected_result


  ():
    
    result =  async_function(valid_input)
     result[] == 

Step 6: Verify Executability

Refer to test-generator-framework for core executability verification.

Step 7: Display Summary

✅ Python test files created successfully!

**Test Files Created:**
- tests/test_<module_name>.py (<number> tests)

**Total Tests Generated:** <number>
**Test Framework:** Pytest

**Python-Specific Categories:**
- Decorator tests: <number>
- Context manager tests: <number>
- Special method tests: <number>
- Async function tests: <number>

To run tests:

# If Poetry is installed:
poetry run pytest tests/test_<module_name>.py -v
poetry run pytest --cov=<module_name> tests/

# Otherwise:
pytest tests/test_<module_name>.py -v
pytest --cov=<module_name> tests/

Python-Specific Scenario Generation

Python-specific patterns to focus on:

Decorator Testing

• Decorator Execution: Decorator modifies function behavior correctly
• Decorator Chaining: Multiple decorators apply correctly
• Decorator Arguments: Decorator with parameters works
• Class Decorators: Decorator classes properly

Context Manager Testing

• __enter__: Returns context manager correctly
• __exit__: Cleans up resources properly
• Exception Handling: Exceptions in context are handled
• Nested Context: Multiple context managers work together

Special Method Testing

• __str__: String representation is correct
• __repr__: Developer representation is correct
• __eq__: Equality comparison works
• __hash__: Hash allows use in sets/dicts
• __len__: Length function returns correct value
• __getitem__: Item access works
• __setitem__: Item assignment works

Property Testing

• Getter: Property returns correct value
• Setter: Property sets value correctly
• Deleter: Property deletion works
• Cached Properties: Cached behavior is correct

Best Practices

Refer to test-generator-framework for general best practices.

Python-specific best practices:

• Pytest Features: Use fixtures, parametrization, marks
• Async Testing: Use pytest-asyncio for async functions
• Type Hints: Include type hints for better test coverage
• Mocking: Use pytest-mock or unittest.mock appropriately

Common Issues

Refer to test-generator-framework for general issues.

Python-specific issues:

Poetry Not Installed

Issue: poetry run pytest command not found

Solution: Use pytest directly instead:

pytest tests/

pytest-asyncio Not Installed

Issue: Async tests fail or don't run

Solution: Install pytest-asyncio:

poetry add --group dev pytest-asyncio
# or
pip install pytest-asyncio

Module Not Found

Issue: Import errors for modules to test

Solution: Add source to PYTHONPATH:

export PYTHONPATH="${PYTHONPATH}:$(pwd)"

Troubleshooting Checklist

Refer to test-generator-framework for general checklist.

Python-specific additions: Before generating tests:

• Python files exist and are syntactically correct
• pyproject.toml or requirements.txt exists
• Pytest is installed
• Poetry is installed (if using Poetry)

Related Commands

# Poetry commands
poetry run pytest -v
poetry run pytest --cov=<module> tests/
poetry install --group dev pytest-asyncio

# Direct pytest commands
pytest -v
pytest tests/test_module.py -v
pytest --cov=<module> tests/
pytest -k "test_name"

# Python commands
python -m pytest
export PYTHONPATH="${PYTHONPATH}:$(pwd)"

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