Mastering Python Skill
mastering-python-skill
Modern Python coaching covering language foundations through advanced production patterns. Use when asked to "write Python code", "explain Python concepts", "set up a Python project", "configure Poetry or PDM", "write pytest tests", "create a FastAPI endpoint", "run uvicorn server", "configure al...
SKILL.md
Full skill instructions
Mastering Python Skill
Production-ready Python patterns with runnable code examples.
Contents
Workflow
Phase 1: Setup
-
Verify Python version
python --version # Require 3.10+, prefer 3.12+ -
Create and activate virtual environment
python -m venv .venv && source .venv/bin/activate -
Install dependencies
poetry install # or: pip install -r requirements.txt
Phase 2: Develop
-
Reference appropriate patterns:
- Types → type-systems.md
- Async → async-programming.md
- APIs → fastapi-patterns.md
- DB → database-access.md
-
Follow project structure from project-structure.md
Phase 3: Validate
-
Run quality checks
ruff check . && ruff format --check . mypy src/ -
Run tests with coverage
pytest -v --cov=src --cov-report=term-missing
Phase 4: Deploy
-
Build and verify package
python -m build && twine check dist/* -
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
| Category | Files | Key Topics |
|---|---|---|
| Foundations | syntax-essentials, type-systems, project-structure, code-quality | Variables, type hints, generics, src layout, ruff, mypy |
| Patterns | async-programming, error-handling, decorators, context-managers, generators | async/await, exceptions, Result type, with statements, yield |
| Testing | pytest-essentials, mocking-strategies, property-testing | Fixtures, parametrize, unittest.mock, Hypothesis |
| Web APIs | fastapi-patterns, pydantic-validation, database-access | Dependencies, middleware, validators, SQLAlchemy async |
| Packaging | poetry-workflow, pyproject-config, docker-deployment | Lock files, PEP 621, multi-stage builds |
| Production | ci-cd-pipelines, monitoring, security | GitHub Actions, OpenTelemetry, OWASP, JWT |
See TOC.md for detailed topic lookup.
Sample CLI Tools
Runnable examples demonstrating production patterns:
| Tool | Demonstrates | Reference |
|---|---|---|
| async_fetcher.py | Async HTTP, rate limiting, error handling | async-programming.md |
| config_loader.py | Pydantic settings, .env files, validation | pydantic-validation.md |
| db_cli.py | SQLAlchemy async CRUD, repository pattern | database-access.md |
| code_validator.py | Run→check→fix with ruff and mypy | code-quality.md |
# 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+