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.
👉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. Cool😄 until n goes from 1 to 100,000.
✅ Fix it like a pro:
Now the cache stays small, predictable, and safe.
📌Bonus: Write your own @timerdecorator in 5 lines. no more time.time() spam.
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!👉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. Cool😄 until n goes from 1 to 100,000.
✅ 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.
📌Bonus: Write your own @timerdecorator in 5 lines. no more time.time() spam.
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Python Data Structures: Quick Visual Guide 🐍
🔹 Lists: Ordered, mutable, created with [ ]
→ Access/modify via index: myList[0], myList[-1]
→ Methods: .append(), .sort(), .pop()
→ Mixed types allowed
→ Loop: for item in myList:
🔹 Tuples: Immutable, ordered → (1, 2, 3)
🔹 Sets: Unordered, unique elements
🔹 Dictionaries: Key-value pairs, fast lookups
🔹 Arrays: Mainly for numeric data (array/NumPy)
🔑 Key Points:
✅ Indexing: 0 to len-1 (forward), -1 backward
✅ Assignment myList[i] = x modifies in place
✅ Lists are the most versatile & commonly used
This is the perfect cheat sheet for beginners and for quick revision!
🔹 Lists: Ordered, mutable, created with [ ]
→ Access/modify via index: myList[0], myList[-1]
→ Methods: .append(), .sort(), .pop()
→ Mixed types allowed
→ Loop: for item in myList:
🔹 Tuples: Immutable, ordered → (1, 2, 3)
🔹 Sets: Unordered, unique elements
🔹 Dictionaries: Key-value pairs, fast lookups
🔹 Arrays: Mainly for numeric data (array/NumPy)
🔑 Key Points:
✅ Indexing: 0 to len-1 (forward), -1 backward
✅ Assignment myList[i] = x modifies in place
✅ Lists are the most versatile & commonly used
This is the perfect cheat sheet for beginners and for quick revision!
❤3
FREE Courses On Python Asyncio
Advanced asyncio: Solving Real-World Production Problems
🆓 Free Video Course
⏰ Duration: 41 Min
🏃♂️ Self paced
📊 Difficulty: Advanced
👨🏫 Created by: PyVideo
🔗 Course Link
Async IO Basics
🆓 Free Online Course
⏰ Duration: ~22 minutes
🏃♂️ Self paced
📊 Difficulty: Beginner
👨🏫 Created by: Very Academy
🔗 Course Link
Asyncio in Python - Full Tutorial
🆓 Free Video Course
⏰ Duration: 25 Min
🏃♂️ Self paced
📊 Difficulty: Beginner
👨🏫 Created by: Tech with Tim
🔗 Course Link
Asyncio Basics - Asynchronous programming with coroutines
🆓 Step-by-step text + video
⏰ Duration: 25 Min
🏃♂️ Self paced
📊 Difficulty: Beginner - Intermediate
👨🏫Created by: Python Programming Tutorials
🔗 Course Link
Reading Materials
📖 Python's Ayncio
📖 Asyncio Tutorial for Beginners
📖 Python Asyncio: The Complete Guide
📖 Official Asyncio Docs
📖 Asyncio Learning Path
#python #asyncio
➖➖➖➖➖➖➖➖➖➖
👉Join @bigdataspecialist for more👈
Advanced asyncio: Solving Real-World Production Problems
🆓 Free Video Course
⏰ Duration: 41 Min
🏃♂️ Self paced
📊 Difficulty: Advanced
👨🏫 Created by: PyVideo
🔗 Course Link
Async IO Basics
🆓 Free Online Course
⏰ Duration: ~22 minutes
🏃♂️ Self paced
📊 Difficulty: Beginner
👨🏫 Created by: Very Academy
🔗 Course Link
Asyncio in Python - Full Tutorial
🆓 Free Video Course
⏰ Duration: 25 Min
🏃♂️ Self paced
📊 Difficulty: Beginner
👨🏫 Created by: Tech with Tim
🔗 Course Link
Asyncio Basics - Asynchronous programming with coroutines
🆓 Step-by-step text + video
⏰ Duration: 25 Min
🏃♂️ Self paced
📊 Difficulty: Beginner - Intermediate
👨🏫Created by: Python Programming Tutorials
🔗 Course Link
Reading Materials
📖 Python's Ayncio
📖 Asyncio Tutorial for Beginners
📖 Python Asyncio: The Complete Guide
📖 Official Asyncio Docs
📖 Asyncio Learning Path
#python #asyncio
➖➖➖➖➖➖➖➖➖➖
👉Join @bigdataspecialist for more👈
❤2
PythonNotesForProfessionals.pdf
6.1 MB
Concise reference compiled from Stack Overflow Q&A covering syntax, OOP, modules, error handling, and advanced topics like decorators.
❤4
Image Caption Generator
Multimodal AI: CNN-RNN combo generates denoscriptive captions for images (e.g., "dog chasing ball"). Showcases encoder-decoder architectures.
🔗 Repo Link: https://github.com/yunjey/show-attend-and-tell
#PythonProjects #ImageCaptionGenerators
Multimodal AI: CNN-RNN combo generates denoscriptive captions for images (e.g., "dog chasing ball"). Showcases encoder-decoder architectures.
🔗 Repo Link: https://github.com/yunjey/show-attend-and-tell
#PythonProjects #ImageCaptionGenerators
GitHub
GitHub - yunjey/show-attend-and-tell: TensorFlow Implementation of "Show, Attend and Tell"
TensorFlow Implementation of "Show, Attend and Tell" - GitHub - yunjey/show-attend-and-tell: TensorFlow Implementation of "Show, Attend and Tell"
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