Python Programming & AI Resources

DSA in Python 👆👆

Useful Python for data science cheat sheets 👆 React ♥️ for more

Python Handwritten Notes 👆

Python Roadmap for 2025: Complete Guide 1. Python Fundamentals 1.1 Variables, constants, and comments. 1.2 Data types: int, float, str, bool, complex. 1.3 Input and output (input(), print(), formatted strings). 1.4 Python syntax: Indentation and code structure. 2. Operators 2.1 Arithmetic: +, -, *, /, %, //, **. 2.2 Comparison: ==, !=, <, >, <=, >=. 2.3 Logical: and, or, not. 2.4 Bitwise: &, |, ^, ~, <<, >>. 2.5 Identity: is, is not. 2.6 Membership: in, not in. 3. Control Flow 3.1 Conditional statements: if, elif, else. 3.2 Loops: for, while. 3.3 Loop control: break, continue, pass. 4. Data Structures 4.1 Lists: Indexing, slicing, methods (append(), pop(), sort(), etc.). 4.2 Tuples: Immutability, packing/unpacking. 4.3 Dictionaries: Key-value pairs, methods (get(), items(), etc.). 4.4 Sets: Unique elements, set operations (union, intersection). 4.5 Strings: Immutability, methods (split(), strip(), replace()). 5. Functions 5.1 Defining functions with def. 5.2 Arguments: Positional, keyword, default, *args, **kwargs. 5.3 Anonymous functions (lambda). 5.4 Recursion. 6. Modules and Packages 6.1 Importing: import, from ... import. 6.2 Standard libraries: math, os, sys, random, datetime, time. 6.3 Installing external libraries with pip. 7. File Handling 7.1 Open and close files (open(), close()). 7.2 Read and write (read(), write(), readlines()). 7.3 Using context managers (with open(...)). 8. Object-Oriented Programming (OOP) 8.1 Classes and objects. 8.2 Methods and attributes. 8.3 Constructor (init). 8.4 Inheritance, polymorphism, encapsulation. 8.5 Special methods (str, repr, etc.). 9. Error and Exception Handling 9.1 try, except, else, finally. 9.2 Raising exceptions (raise). 9.3 Custom exceptions. 10. Comprehensions 10.1 List comprehensions. 10.2 Dictionary comprehensions. 10.3 Set comprehensions. 11. Iterators and Generators 11.1 Creating iterators using iter() and next(). 11.2 Generators with yield. 11.3 Generator expressions. 12. Decorators and Closures 12.1 Functions as first-class citizens. 12.2 Nested functions. 12.3 Closures. 12.4 Creating and applying decorators. 13. Advanced Topics 13.1 Context managers (with statement). 13.2 Multithreading and multiprocessing. 13.3 Asynchronous programming with async and await. 13.4 Python's Global Interpreter Lock (GIL). 14. Python Internals 14.1 Mutable vs immutable objects. 14.2 Memory management and garbage collection. 14.3 Python's name == "main" mechanism. 15. Libraries and Frameworks 15.1 Data Science: NumPy, Pandas, Matplotlib, Seaborn. 15.2 Web Development: Flask, Django, FastAPI. 15.3 Testing: unittest, pytest. 15.4 APIs: requests, http.client. 15.5 Automation: selenium, os. 15.6 Machine Learning: scikit-learn, TensorFlow, PyTorch. 16. Tools and Best Practices 16.1 Debugging: pdb, breakpoints. 16.2 Code style: PEP 8 guidelines. 16.3 Virtual environments: venv. 16.4 Version control: Git + GitHub. 👇 Python Interview 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 https://t.me/dsabooks 📘 𝗣𝗿𝗲𝗺𝗶𝘂𝗺 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲 𝗜𝗻𝘁𝗲𝗿𝘃𝗶𝗲𝘄 𝗥𝗲𝘀𝗼𝘂𝗿𝗰𝗲𝘀 : https://topmate.io/coding/914624 📙 𝗗𝗮𝘁𝗮 𝗦𝗰𝗶𝗲𝗻𝗰𝗲: https://whatsapp.com/channel/0029VaxbzNFCxoAmYgiGTL3Z Join What's app channel for jobs updates: t.me/getjobss