Python Learning Roadmap: From Intermediate to Advanced

1. Core Intermediate Concepts

Data Structures in Depth

• Lists, tuples, sets, dictionaries (advanced usage)
• Comprehensions (list, set, dict)
• Iterators & generators

Functions & Functional Programming

• Default & keyword arguments
• *args and **kwargs
• Lambda, map(), filter(), reduce()
• Closures and decorators

Error Handling

• Custom exceptions
• Context managers (with statement)

Modules & Packages

• Import system
• Virtual environments (venv, pip, poetry basics)

2. Object-Oriented Programming (OOP)

• Classes & Objects
• Inheritance (single, multiple)
• Method Resolution Order (MRO)
• Polymorphism & abstraction
• Dunder methods (__str__, __repr__, __len__, etc.)
• Class vs static methods
• Metaclasses (intro)

3. File Handling & Persistence

• Working with text, CSV, JSON, and XML
• Pickling and serialization
• SQLite with sqlite3
• Introduction to ORMs (SQLAlchemy, Django ORM basics)

4. Advanced Python Concepts

• Iterators, Generators, and Coroutines
• Decorators (function & class-based)
• Context Managers (custom __enter__/__exit__)
• Descriptors & Properties
• Abstract Base Classes (abc module)
• Type hints & typing module
• Memory management & garbage collection

5. Concurrency & Parallelism

• Multithreading (threading, GIL implications)
• Multiprocessing (multiprocessing)
• Asyncio (async/await, event loop)
• Futures, Tasks, Executors
• When to use threading vs multiprocessing vs asyncio

6. Testing & Debugging

• Debugging with pdb, logging
• Unit testing (unittest, pytest)
• Test-driven development (TDD)
• Mocking and patching
• Profiling & performance testing

7. Advanced Libraries & Tools

• Data handling: pandas, numpy
• Visualization: matplotlib, seaborn
• Networking: requests, httpx
• Web scraping: BeautifulSoup, scrapy
• CLI tools: argparse, click
• Regular expressions (re)

8. Design Patterns in Python

• Singleton, Factory, Builder
• Observer, Strategy, Adapter
• Dependency Injection
• Pythonic patterns (duck typing, EAFP vs LBYL)

9. Advanced Topics

• Metaprogramming (introspection, modifying classes at runtime)
• Decorator factories & higher-order functions
• Cython & performance optimization
• Memory profiling
• Python internals (bytecode, disassembly with dis)
• Understanding CPython vs PyPy vs Jython

10. Practical Applications

• Web development (Flask, FastAPI, Django)
• APIs (REST, GraphQL basics)
• Automation & scripting
• Data analysis projects
• Machine learning (scikit-learn, TensorFlow/PyTorch intro)
• DevOps scripting with Python (automation, cloud SDKs)