Python Project Creator
Critical Corrections
Use 'uv' instead of 'pip'
- •✗ Don't: pip install, pip freeze
- •✓ Do: uv pip install, uv pip freeze (uv is faster and more modern)
Always use pytest, never unittest
- •✗ Don't: unittest framework
- •✓ Do: pytest for all testing needs
Overview
This skill creates well-structured Python projects with best practices for dependency management, testing, and code organization. It sets up virtual environments, installs dependencies, and configures common development tools.
Project Creation Workflow
1. Understand Requirements
Ask the user about:
- •Project name and purpose
- •Type: CLI tool, web app, library, data science project
- •Dependencies: Required packages
- •Testing: Testing framework preference (pytest, unittest)
2. Create Project Structure
Standard Python project structure:
code
project-name/ ├── src/ │ └── project_name/ │ ├── __init__.py │ └── main.py ├── tests/ │ ├── __init__.py │ └── test_main.py ├── .gitignore ├── README.md ├── requirements.txt └── setup.py (optional, for libraries)
3. Virtual Environment Setup
Create and activate virtual environment:
bash
# Create virtual environment python3 -m venv venv # Activate (instructions for user) # macOS/Linux: source venv/bin/activate # Windows: venv\Scripts\activate
4. Install Dependencies
Install packages using uv:
bash
uv pip install <package-name> uv pip freeze > requirements.txt
For development dependencies:
bash
uv pip install pytest black flake8 mypy
5. Initialize Git
bash
git init git add . git commit -m "Initial commit: project setup"
Project Types
CLI Application
- •Use
argparseorclickfor command-line arguments - •Include
main.pywith proper entry point - •Add
if __name__ == "__main__":guard
Web Application
- •Flask: Lightweight, good for small APIs
- •FastAPI: Modern, async, auto-documentation
- •Django: Full-featured, batteries included
Library/Package
- •Include
setup.pyfor packaging - •Follow semantic versioning
- •Add comprehensive docstrings
Data Science
- •Include
notebooks/directory for Jupyter notebooks - •Add
data/directory (with .gitignore) - •Common packages: pandas, numpy, matplotlib, scikit-learn
Testing Setup
pytest (Required)
Always use pytest for testing:
bash
uv pip install pytest pytest-cov
Example test file:
python
# tests/test_main.py
import pytest
from src.project_name.main import my_function
def test_my_function():
assert my_function(2, 3) == 5
Run tests:
bash
pytest pytest --cov=src # with coverage
Code Quality Tools
Black (Code Formatter)
bash
uv pip install black black src/ tests/
Flake8 (Linter)
bash
uv pip install flake8 flake8 src/ tests/
mypy (Type Checker)
bash
uv pip install mypy mypy src/
Common Patterns
Entry Point Pattern
python
# src/project_name/main.py
def main():
"""Main application entry point."""
print("Hello, World!")
if __name__ == "__main__":
main()
Configuration Pattern
python
# src/project_name/config.py
import os
from pathlib import Path
# Project root directory
PROJECT_ROOT = Path(__file__).parent.parent.parent
# Load environment variables
DEBUG = os.getenv("DEBUG", "False") == "True"
Error Handling Pattern
python
class ProjectError(Exception):
"""Base exception for this project."""
pass
class ConfigError(ProjectError):
"""Configuration-related errors."""
pass
.gitignore Template
code
# Virtual environment venv/ env/ .venv/ # Python __pycache__/ *.py[cod] *$py.class *.so .Python *.egg-info/ dist/ build/ # IDE .vscode/ .idea/ *.swp *.swo # Environment .env .env.local # Testing .pytest_cache/ .coverage htmlcov/ # OS .DS_Store Thumbs.db
Best Practices
Dependency Management
- •Pin exact versions in production:
package==1.2.3 - •Use ranges for libraries:
package>=1.2,<2.0 - •Separate dev dependencies from production
- •Keep requirements.txt minimal
Project Structure
- •Use
src/layout to avoid import issues - •Keep tests separate from source code
- •One module per file, clear naming
- •Flat is better than nested (within reason)
Documentation
- •Write clear README.md with setup instructions
- •Add docstrings to all public functions/classes
- •Include usage examples in README
- •Document environment variables
Version Control
- •Initialize git from the start
- •Write meaningful commit messages
- •Create .gitignore before first commit
- •Never commit secrets or credentials
Quick Start Examples
Minimal CLI Tool
bash
mkdir my-cli-tool && cd my-cli-tool python3 -m venv venv source venv/bin/activate uv pip install click # Create main.py, tests, etc.
FastAPI Web Service
bash
mkdir my-api && cd my-api python3 -m venv venv source venv/bin/activate uv pip install fastapi uvicorn # Create app structure
Data Science Project
bash
mkdir my-analysis && cd my-analysis python3 -m venv venv source venv/bin/activate uv pip install pandas numpy matplotlib jupyter # Create notebooks/, data/, src/
Resources
This skill includes examples in the bundled directories:
scripts/
- •
example.py- Template Python script with best practices
references/
- •
api_reference.md- Common library documentation references
assets/
- •Project templates and boilerplate code