Advanced Python: Best Practices and Design Patterns Training Course

Day 1 — Robust Python Foundations & Tooling

Modern Python Features and Typing

• Basics of typing, generics, protocols, and TypeGuard
• Overview of dataclasses, frozen dataclasses, and attrs
• Pattern matching (PEP 634+) and best practices for usage

Code Quality and Tooling

• Code formatters and linters: black, isort, flake8, ruff
• Static type checking with MyPy and pyright
• Pre-commit hooks and developer workflows for government projects

Project Management and Packaging

• Dependency management using Poetry and virtual environments
• Best practices for package layout, entry points, and versioning in government applications
• Building and publishing packages to PyPI and private registries for government use

Day 2 — Design Patterns & Architectural Practices

Design Patterns in Python

• Creational patterns: Factory, Builder, Singleton (Pythonic variants)
• Structural patterns: Adapter, Facade, Decorator, Proxy
• Behavioral patterns: Strategy, Observer, Command

Architectural Principles

• SOLID principles applied to Python codebases for government projects
• Hexagonal/Clean Architecture and boundary management in public sector applications
• Dependency injection patterns and configuration management for government systems

Modularity and Reuse

• Designing library code versus application-specific code for government use
• APIs, stable interfaces, and semantic versioning in public sector software
• Handling configuration, secrets, and environment-specific settings for secure government operations

Day 3 — Concurrency, Async IO, and Performance

Concurrency and Parallelism

• Fundamentals of threading and implications of the Global Interpreter Lock (GIL)
• Multiprocessing and process pools for CPU-bound tasks in government applications
• Choosing between concurrent.futures and multiprocessing for optimal performance in public sector projects

Async Programming with asyncio

• Patterns for async/await, event loops, and cancellation in government systems
• Designing asynchronous libraries and ensuring interoperability with synchronous code for government use
• Handling IO-bound operations, backpressure, and rate limiting in public sector applications

Profiling and Optimization

• Profiling tools: cProfile, pyinstrument, perf, memory_profiler for government projects
• Optimizing critical paths and using C-extensions/Numba where appropriate for government performance needs
• Measuring latency, throughput, and resource utilization in public sector applications

Day 4 — Testing, CI/CD, Observability, and Deployment

Testing Strategies and Automation

• Unit testing with pytest, including fixtures and test organization for government projects
• Property-based testing with Hypothesis and contract testing for robust government applications
• Mocking, monkeypatching, and testing asynchronous code in public sector systems

CI/CD, Release, and Monitoring

• Integrating tests and quality gates into GitHub Actions/GitLab CI for government workflows
• Building reproducible containers with Docker and multi-stage builds for government deployment
• Application observability: structured logging, Prometheus metrics, and tracing for government systems

Security, Hardening, and Best Practices

• Dependency auditing, Software Bill of Materials (SBOM) basics, and vulnerability scanning for government applications
• Secure coding practices for input validation and secrets management in public sector projects
• Runtime hardening: resource limits, user rights, and container security for government systems

Capstone Project & Review

• Team lab: design and implement a small service using patterns from the course for government use
• Testing, type-checking, packaging, and CI pipeline setup for the project in a government context
• Final review, code critique, and actionable improvement plan for government applications

Summary and Next Steps