Python Advanced — Complete Guide to Advanced Python Programming
Python Advanced Tutorial
Welcome to the Python Advanced tutorial track. This series takes you from solid Python fundamentals to production-grade advanced techniques — covering generators, decorators, concurrency, testing, metaprogramming, and everything in between.
What is Python Advanced?
This is a comprehensive, hands-on tutorial that teaches you advanced Python programming. You’ll learn to write high-performance, well-tested, and production-ready code using iterators, generators, async/await, type hints, and proven engineering practices.
Advanced Python is where you stop writing code that works and start writing code that scales. Whether you’re building backend services, data pipelines, CLI tools, or preparing for the PCPP1 certification — these are the skills that separate hobbyists from professionals.
Tutorial Details
| Detail | Info |
|---|---|
| Level | Intermediate to Advanced |
| Chapters | 26 (with 180+ sub-topics) |
| Prerequisites | Python Basics + Python OOP completed |
| Estimated Time | 60–80 hours |
| Python Version | 3.10+ |
What You’ll Learn
- Iterators, Generators & Decorators — Custom iterators,
yield, generator pipelines, decorators with arguments, context managers - Functional Programming — First-class functions, closures,
itertools,functools,operatormodule - Type System & Metaprogramming — Type hints, generics, protocols, dynamic attributes, AST, code generation
- Concurrency & Parallelism — Threading, multiprocessing, asyncio, async generators, TaskGroups
- Testing & Quality — unittest, pytest, fixtures, mocking, logging, debugging, profiling
- Data, I/O & Networking — Regular expressions, databases, REST APIs, web scraping
- Packaging & Performance — pyproject.toml, PyPI publishing, caching, memory optimization, C extensions
- Practice — Mini projects, coding challenges, best practices, FAQ
Prerequisites
Before starting this track, you should have completed:
- Python Basics — variables, data types, functions, modules, file I/O, error handling
- Python OOP — classes, inheritance, polymorphism, design patterns, magic methods
- Comfort writing classes, using decorators, and understanding closures
Not there yet? Complete the Python Basics and Python OOP tutorials first — they’re free and build the foundation you need.
Chapters
| # | Chapter | Topic Area |
|---|---|---|
| 1 | Iterators & Iterables | Iterators, Generators & Decorators |
| 2 | Generators | Iterators, Generators & Decorators |
| 3 | Decorators | Iterators, Generators & Decorators |
| 4 | Advanced Decorators | Iterators, Generators & Decorators |
| 5 | Context Managers | Iterators, Generators & Decorators |
| 6 | Advanced Functions | Functional Programming |
| 7 | Itertools Deep Dive | Functional Programming |
| 8 | Functools & Operator | Functional Programming |
| 9 | Type Hints Fundamentals | Type System & Metaprogramming |
| 10 | Advanced Typing | Type System & Metaprogramming |
| 11 | Metaprogramming | Type System & Metaprogramming |
| 12 | Threading | Concurrency & Parallelism |
| 13 | Multiprocessing | Concurrency & Parallelism |
| 14 | Asyncio Fundamentals | Concurrency & Parallelism |
| 15 | Advanced Asyncio | Concurrency & Parallelism |
| 16 | Unit Testing with unittest | Testing & Quality |
| 17 | Testing with pytest | Testing & Quality |
| 18 | Logging | Testing & Quality |
| 19 | Debugging & Profiling | Testing & Quality |
| 20 | Regular Expressions | Data, I/O & Networking |
| 21 | Database Access | Data, I/O & Networking |
| 22 | Networking & HTTP | Data, I/O & Networking |
| 23 | Packaging & Distribution | Packaging & Performance |
| 24 | Performance Optimization | Packaging & Performance |
| 25 | Advanced Mini Projects | Wrap-Up |
| 26 | Practice & Next Steps | Wrap-Up |
