mastering-python-skill

Mastering Python Skill

Production-ready Python patterns with runnable code examples.

Contents

• Workflow
• Reference Files
• Sample CLI Tools
• When NOT to Use
• Full Table of Contents

Workflow

Phase 1: Setup

1. Verify Python version

   python --version  # Require 3.10+, prefer 3.12+
   

2. Create and activate virtual environment

   python -m venv .venv && source .venv/bin/activate
   

3. Install dependencies

   poetry install  # or: pip install -r requirements.txt
   

Phase 2: Develop

4. Reference appropriate patterns:

   • Types → type-systems.md
   • Async → async-programming.md
   • APIs → fastapi-patterns.md
   • DB → database-access.md

5. Follow project structure from project-structure.md

Phase 3: Validate

6. Run quality checks

   ruff check . && ruff format --check .
   mypy src/
   

7. Run tests with coverage

   pytest -v --cov=src --cov-report=term-missing
   

Phase 4: Deploy

8. Build and verify package

   python -m build && twine check dist/*
   

9. Deploy per docker-deployment.md or ci-cd-pipelines.md

Pre-Completion Checklist:

- [ ] All tests pass
- [ ] mypy reports no errors
- [ ] ruff check clean
- [ ] Coverage ≥80%
- [ ] No security warnings in dependencies

Reference Files

See TOC.md for detailed topic lookup.

Sample CLI Tools

Runnable examples demonstrating production patterns:

# Test examples
python sample-cli/async_fetcher.py https://httpbin.org/get
python sample-cli/config_loader.py --show-env
python sample-cli/db_cli.py init --sample-data && python sample-cli/db_cli.py list
python sample-cli/code_validator.py src/

When NOT to Use

• Non-Python languages: Use language-specific skills
• ML/AI model internals: Use PyTorch/TensorFlow skills
• Cloud infrastructure: Use AWS/GCP skills for infra (this covers code)
• Legacy Python 2: Focus is Python 3.10+