Python Learning
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Python learning resources

Beginner to advanced Python guides, cheatsheets, books and projects.

For data science, backend and automation.
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Python_Cheatsheet_Zero_To_Mastery.pdf
450.1 KB
πŸ‘¨β€πŸ« The Zero to Mastery Python Cheat Sheet is a clean, colorful cheatsheet packed with practical code snippets for everyday tasks like loops, functions, and list comprehension.

🀩 It’s visually organized with clear sections and real examples, which makes it a favorite for beginners and intermediates who want to code faster and smarter.
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Decorators Are Not Magic. They’re Callbacks in Disguise

You’ve used @lru_cache to speed up a slow function, and it worked... until your app started eating RAM because the cache never forgot anything.

from functools import lru_cache

@lru_cache
def fib(n):
return fib(n-1) + fib(n-2) # ← Cache grows forever!


πŸ‘‰Here’s what’s really happening:
A decorator is just a function that wraps another function. When you write @lru_cache, Python replaces your fib with a new version that remembers every answer it’s ever given. CoolπŸ˜„ until n goes from 1 to 100,000.

βœ… Fix it like a pro:
from functools import lru_cache

@lru_cache(maxsize=128) # Only keep last 128 results
def fib(n):
if n > 1000:
return manual_calc(n) # Skip cache for huge inputs
return fib(n-1) + fib(n-2)


Now the cache stays small, predictable, and safe.

πŸ“ŒBonus: Write your own @timerdecorator in 5 lines. no more time.time() spam.
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πŸ”₯ Python vs SQL: Who Cleans Data Better? 🧹
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any() and all() function in Python
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Python Data Structures: Quick Visual Guide 🐍

πŸ”Ή Lists: Ordered, mutable, created with [ ]
β†’ Access/modify via index: myList[0], myList[-1]
β†’ Methods: .append(), .sort(), .pop()
β†’ Mixed types allowed
β†’ Loop: for item in myList:

πŸ”Ή Tuples: Immutable, ordered β†’ (1, 2, 3)

πŸ”Ή Sets: Unordered, unique elements

πŸ”Ή Dictionaries: Key-value pairs, fast lookups

πŸ”Ή Arrays: Mainly for numeric data (array/NumPy)

πŸ”‘ Key Points:
βœ… Indexing: 0 to len-1 (forward), -1 backward
βœ… Assignment myList[i] = x modifies in place
βœ… Lists are the most versatile & commonly used

This is the perfect cheat sheet for beginners and for quick revision!
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Put your answers in the comment belowπŸ”½
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FREE Courses On Python Asyncio

Advanced asyncio: Solving Real-World Production Problems
πŸ†“
Free Video Course
⏰ Duration: 41 Min
πŸƒβ€β™‚οΈ Self paced
πŸ“Š Difficulty: Advanced
πŸ‘¨β€πŸ« Created by: PyVideo
πŸ”— Course Link

Async IO Basics
πŸ†“ Free Online Course
⏰ Duration: ~22 minutes
πŸƒβ€β™‚οΈ Self paced
πŸ“Š Difficulty: Beginner
πŸ‘¨β€πŸ« Created by: Very Academy
πŸ”— Course Link

Asyncio in Python - Full Tutorial
πŸ†“
Free Video Course
⏰ Duration: 25 Min
πŸƒβ€β™‚οΈ Self paced
πŸ“Š Difficulty: Beginner
πŸ‘¨β€πŸ« Created by: Tech with Tim
πŸ”— Course Link

Asyncio Basics - Asynchronous programming with coroutines
πŸ†“
Step-by-step text + video
⏰ Duration: 25 Min
πŸƒβ€β™‚οΈ Self paced
πŸ“Š Difficulty: Beginner - Intermediate
πŸ‘¨β€πŸ«Created by: Python Programming Tutorials
πŸ”— Course Link


Reading Materials

πŸ“– Python's Ayncio
πŸ“– Asyncio Tutorial for Beginners
πŸ“– Python Asyncio: The Complete Guide
πŸ“– Official Asyncio Docs
πŸ“– Asyncio Learning Path


#python  #asyncio
βž–βž–βž–βž–βž–βž–βž–βž–βž–βž–
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What is Walrus Operator (:=) in Python?
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Important Python Function and their Purpose
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Put your answers in the comment belowπŸ”½
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PythonNotesForProfessionals.pdf
6.1 MB
Concise reference compiled from Stack Overflow Q&A covering syntax, OOP, modules, error handling, and advanced topics like decorators.
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Decorators in Python
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Put your answers in the comment below
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Python Roadmap For AI/ML
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Python For Data Science Cheatsheet: Part 1
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Python For Data Science Cheatsheet: Part 2
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Image Caption Generator

Multimodal AI: CNN-RNN combo generates descriptive captions for images (e.g., "dog chasing ball"). Showcases encoder-decoder architectures.

πŸ”— Repo Link: https://github.com/yunjey/show-attend-and-tell


#PythonProjects  #ImageCaptionGenerators
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Put your answers in the comment below!πŸ”½
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Python vs R for Data Analysis: When to use which
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