Course Outline
Day 1 — Foundational Python Proficiency and Developer Ecosystem
Contemporary Python Capabilities and Type System
- Foundational typing constructs, generic abstractions, Protocols, and TypeGuard utilities
- Implementation and application of dataclasses, immutable data structures, and the attrs library
- Application of structural pattern matching (PEP 634+) aligned with idiomatic coding standards
Code Integrity and Developer Toolchains
- Standardization of code formatting and linting via black, isort, flake8, and ruff
- Enforcement of static type verification using MyPy and pyright
- Integration of pre-commit hooks to streamline automated developer workflows
Project Governance and Packaging Standards
- Dependency lifecycle management utilizing Poetry and isolated virtual environments
- Best practices for package structure, entry point definitions, and semantic versioning
- Processes for building and distributing packages to PyPI and secure internal registries
Day 2 — Structural Design Patterns and System Architecture
Application of Design Patterns in Python
- Creational strategies: Factory, Builder, and Singleton implementations adapted for Python
- Structural components: Adapter, Facade, Decorator, and Proxy patterns
- Behavioral frameworks: Strategy, Observer, and Command patterns
Architectural Governance Principles
- Application of SOLID principles to maintainable Python codebases
- Implementation of Hexagonal and Clean Architecture models with defined system boundaries
- Strategies for dependency injection and centralized configuration management
Modular Design and Component Reuse
- Distinctions in design considerations between library development and application logic
- Establishment of stable APIs, interface contracts, and semantic versioning protocols
- Management of configuration parameters, secret data, and environment-specific settings
Day 3 — Concurrency Models, Asynchronous I/O, and Performance Optimization
Concurrency and Parallel Execution
- Threading mechanics and the impact of the Global Interpreter Lock (GIL)
- Utilization of multiprocessing and process pools for CPU-intensive operations
- Selection criteria for concurrent.futures versus multiprocessing modules
Asynchronous Programming via asyncio
- Management of async/await flows, event loop mechanics, and cancellation logic
- Design of asynchronous libraries and interoperability with synchronous code
- Patterns for I/O-bound workloads, backpressure regulation, and rate limiting
Performance Profiling and Optimization
- Application of profiling instruments: cProfile, pyinstrument, perf, and memory_profiler
- Optimization of critical execution paths and integration of C-extensions or Numba
- Quantification of latency, throughput, and resource consumption metrics
Day 4 — Quality Assurance, CI/CD, Observability, and Deployment
Testing Methodologies and Automation
- Unit testing frameworks, fixture management, and structural organization using pytest
- Application of property-based testing via Hypothesis and contract validation
- Techniques for mocking, monkeypatching, and testing asynchronous code paths
CI/CD Pipelines, Release Management, and Monitoring
- Integration of test suites and quality gates into GitHub Actions or GitLab CI environments
- Construction of reproducible container images using Docker and multi-stage build processes
- Implementation of application observability via structured logging, Prometheus metrics, and distributed tracing
Security Posture, Hardening, and Operational Best Practices
- Dependency auditing, Software Bill of Materials (SBOM) generation, and vulnerability detection
- Secure coding standards for input validation and cryptographic key management
- Runtime hardening measures including resource limits, privilege management, and container security
Capstone Implementation and Peer Review
- Collaborative exercise: Design and implementation of a discrete service utilizing course-derived patterns
- Establishment of testing suites, type-checking, packaging, and CI pipelines for the capstone project
- Conduct of final review, code critique, and formulation of actionable improvement strategies
Summary and Strategic Outlook
Requirements
- Demonstrated intermediate-level proficiency in Python programming
- Working knowledge of object-oriented programming principles and basic testing methodologies
- Proficiency with command-line interfaces and Git version control systems
Target Audience
- Senior Python developers
- Software engineers responsible for maintaining Python code quality and architectural integrity
- Technical leads and MLOps/DevOps engineers managing Python codebases in government environments
Testimonials (2)
everything was perfect
Florin Vrincianu
Course - Python Programming Fundamentals
Hands-on exercises related to content really helps to understand more about each topic. Also, style of start class with lecture and continue with hands-on exercise is good and helpful to relate with the lecture that presented earlier.
