Python Challenge #1 – Answer Revealed! b = a[:] ---> creates a shallow copy of a. So a and b are separate lists. Appending 4 to b changes only b, not a. #python #code #programmer #challenge #trending #list
Python Challenge: Shallow Copy of List a
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Python Logic: Is this Math or Magic?🤔 Day 8 of my Python journey! C++ logic tells me: You can't add words to numbers. Python logic says: Hold my coffee ☕ Check out this snippet: result = True + True + False * True What do you think the print(result) output will be? Drop your guess in the comments! 👇 A) True B) 2 C) 3 D) Error Hint💡: It comes down to how Python stores Booleans as Integers! #Python #LearninginPublic #30DaysOfCode #ProgrammingLogic #Day8
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That simple x = 10 in Python? It’s doing much more than storing the number 10. Under the hood, a Python integer is a full object (implemented in C) that includes: -- The actual value (stored as a dynamic array of digits) -- Type information -- A size field -- A reference count for memory management Unlike C, where an integer is just fixed-size raw bytes, Python stores a reference to an object. This is why a Python list of 1000 integers is actually 1000 separate objects in memory, each with its own overhead. And this is exactly where NumPy shines: -- Fixed-type arrays -- Contiguous memory -- No per-object overhead More flexibility = more memory. That’s the trade-off Python makes for you silently, every single day. #Python #SoftwareEngineering #BackendDevelopment #NumPy #PythonInternals
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Hot take: Python is fast enough for most things. For the other things? 🦀 Rust. Just published a guide on using PyO3 v0.28 + maturin to drop Rust into your Python stack — the same approach Polars, Ruff, and Pydantic v2 use. One function. Native speed. Still pip install-able. 👉 https://lnkd.in/g794MZxa #Rust #Python #PyO3 #Engineering #Performance
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🚀 Python Tip: len(obj) -> obj.__len__() next(obj) -> obj.__next__() Built-in functions delegate behavior to dunder (double-underscore) methods implemented on objects. That’s how Python lets your own classes behave like built-in types. #Python #PythonTips #PythonProgramming #LearnPython #CodeNewbie #100DaysOfCode #Programming #SoftwareEngineering #CleanCode #PythonInternals #PythonTricks #DevTips
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Here's a Python dictionary merge challenge from @dontmisstmr — can you get it right without running the code? dict1 = {"name": "Alice", "age": 25} dict2 = {"city": "Noida", "age": 26} merged = dict1 | dict2 print(merged) The | operator was introduced in Python 3.9. When both dicts share a key, which value wins? Drop your answer in the comments! #Python #SoftwareDevelopment #CodingChallenge #ProgrammingTips #TechCommunity
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Here's a Python collections challenge from @dontmisstmr — can you get it right without running the code? from collections import Counter data = [1, 2, 2, 3, 3, 3, 4, 4] top_element = Counter(data).most_common(1) print(top_element) Counter is one of Python's most underrated built-ins. Do you know what format most_common(1) returns? Drop your answer in the comments! #Python #SoftwareDevelopment #CodingChallenge #ProgrammingTips #TechCommunity
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Built a simple Number Guessing Game using Python 🎯 Features: Random number generation Input validation Limited attempts User-friendly feedback (Too high / Too low) This helped me understand loops, conditions, and error handling better. Next step: Adding difficulty levels and score tracking 🚀 #Python #DataAnalytics #Learning #Projects
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Built a simple Dice Roller using Python. As part of practicing Python basics, I created a small program that simulates rolling a dice. This program: • Generates a random number between 1 and 6 • Allows the user to roll multiple times • Uses loops and user input for interaction Through this project, I practiced: • Random module • Loops • Conditional statements • Handling user input It’s a simple project, but it helped me understand how randomness and control flow work together. Still learning and building step by step. #Python #BeginnerProject #DiceRoller #LearningInPublic #CodingJourney
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Day 72 of filter() function: Today I explored Python’s powerful filter() function. It helps extract elements from lists based on conditions—like filtering even numbers or names containing specific letters. This concise approach makes code cleaner and more efficient. Github link: https://lnkd.in/gFtmaYZS #Python #CodingChallenge #100DaysOfCode #LearningInPublic #GitHub #CodeNewbie
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