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

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+