Python Learning Path - 2

Python

In this post, we will continue our learning from basic to advance topics of python.

1. Deep Dive into Data Structures:
   • Understand advanced data structures like heaps, linked lists, and trees.
   • Learn about collections module (e.g., deque, Counter, defaultdict).
   • Resources:
     • Python Data Structures
     • Collections Module
2. Advanced Functions:
   • Master higher-order functions, lambda functions, and functional programming concepts.
   • Explore decorators and their use cases.
   • Resources:
     • Python Decorators
     • Functional Programming in Python
3. Iterators and Generators:
   • Learn about iterators and the iterator protocol.
   • Understand generators and generator expressions for efficient looping.
   • Resources:
     • Iterators and Iterables
     • Generators
4. Context Managers:
   • Use context managers to manage resources with with statements.
   • Create custom context managers using contextlib.
   • Resources:
     • Context Managers and the with Statement
     • Contextlib Module
5. Metaprogramming:
   • Understand metaclasses and their applications.
   • Explore dynamic code generation and manipulation.
   • Resources:
     • Metaclasses in Python
     • Dynamic Code Generation
6. Concurrency and Parallelism:
   • Learn about threading, multiprocessing, and asynchronous programming with asyncio.
   • Understand the Global Interpreter Lock (GIL) and its implications.
   • Resources:
     • Concurrency in Python
     • Asyncio
7. Networking and Web Development:
   • Dive into network programming with socket and asyncio.
   • Explore web frameworks like Flask, Django, and FastAPI for building web applications.
   • Resources:
     • Network Programming
     • Flask
     • Django
     • FastAPI
8. Testing and Debugging:
   • Write unit tests using unittest and pytest.
   • Learn advanced debugging techniques and tools.
   • Resources:
     • Unit Testing
     • Pytest
     • Debugging Techniques
9. Performance Optimization:
   • Profile and optimize code for performance using cProfile, timeit, and other tools.
   • Understand memory management and garbage collection.
   • Resources:
     • Profiling and Optimization
     • Memory Management

10. Interfacing with C/C++: * Use ctypes and cffi to interface with C libraries. * Explore writing Python extensions in C for performance-critical code. * Resources: * Ctypes * CFFI * Python Extensions in C

11. Deployment and Distribution: * Learn about packaging and distributing Python applications with setuptools and pip. * Explore containerization with Docker and deployment on cloud platforms. * Resources: * Setuptools * Docker * Deploying Python Applications

12. Security: * Understand common security practices and vulnerabilities. * Learn about cryptography and secure coding practices. * Resources: * Python Security * Cryptography