Python Threading Explained: Speed Up Your Code

Python just stopped being "slow." For 20 years, the biggest insult you could throw at a Python dev was: "But what about the GIL?" (The Global Interpreter Lock—the thing that made true parallelism impossible). As of the 3.14 release, the GIL is dead. Free-threading is here. This isn't just a minor version update. This is a fundamental rewrite of how Python handles compute. * True multi-core execution. * Zero overhead parallelism. * Data processing speeds that rival compiled languages. The "slow language" just woke up. If you are still optimising by rewriting in Rust, check the new benchmarks first. You might not need to leave Python anymore. #Python #Programming #Performance #TechNews #SoftwareEngineering

At first, I skipped Iterator, Generator, and Decorator while revising Python. I thought they were confusing and not that important. But during revision, when I properly understood them, everything became clear — what they are, why they exist, and where Python actually uses them. ✨ Quick learning summary : 🔹 Iterator Used to go through data one value at a time. Example: reading large files, database records. 🔹 Generator An easier and smarter way to create iterators using yield. Used when working with large data, streams, or infinite sequences. 🔹 Decorator Used to add extra behavior to a function without changing its code. Commonly used for logging, authentication, caching . 👉 After understanding these concepts, Python feels more powerful and logical, not complex. 📌 Lesson learned: Never skip a topic just because it looks difficult. Once you understand the why, the how becomes easy. #Python #LearningJourney #CorePython #Iterator #Generator #Decorator #ProgrammingBasics #Revision #InnomaticsResearchLabs #AdvancedPython #Syntax #Example

😳 Python says 6 - 5.7 = 0.2999999999999998 Is Python bad at maths? The first time I saw this, I thought I broke Python. 6 - 5.7 Expected: 0.3 Got: 0.2999999999999998 Turns out… Python is innocent. 🔍 The real reason: Computers don’t understand decimals the way humans do. They store numbers in binary (base-2), and decimals like 0.1, 0.2, 0.3, 5.7 cannot be stored exactly in binary. So Python stores the closest possible value. Just like: 1/3 = 0.3333... (never ends in decimal) 0.1 never ends in binary 💡 Fun fact: 0.1 + 0.2 == 0.3 # False This isn’t a Python bug. It’s a computer science reality (IEEE floating-point standard). 📌 Key takeaway: Integers → exact Floating-point numbers → approximations Once you know this, a LOT of “weird” bugs suddenly make sense. Learning Python is not just about syntax — it’s about understanding how computers think. #Python #LearningInPublic #ComputerScience #DataScience #Programming #FloatingPoint #TechInsights

Multiple inheritance in Python can be powerful when a class genuinely needs to combine behaviors from different parents (e.g., a string-like object that also counts elements). But the moment those inheritance paths reconnect, you run into the classic diamond problem: the same base class can be reached through multiple routes, so method lookup can become ambiguous if it isn’t handled consistently. Python addresses this with the Method Resolution Order (MRO), computed via C3 linearization. In practice, this gives a predictable search path for attributes and methods: subclasses are checked before base classes, and the order of base classes in the class definition matters. When things are well-formed, you can always inspect the exact lookup chain using ClassName.__mro__ to understand why a specific method implementation is selected. super() fits into this same model: it forwards the call to the next class in the MRO—not simply “the parent.” That makes cooperative multiple inheritance possible (especially with mixins), but it also raises the bar for design discipline. When the goal is clean, safe APIs, the recommended default is often composition over inheritance, keeping mixins small and focused, and using narrower interfaces (e.g., protocols) so classes expose only what they truly need. #Python #SoftwareEngineering #OOP #Programming #CleanCode

Is Python removing the GIL? First — what is the GIL? The Global Interpreter Lock (GIL) is a mechanism in Python that allows only one thread to execute Python bytecode at a time, even on multi-core CPUs. Think of it like a traffic signal: only one thread runs Python code while others wait. So… is Python removing it? Yes — Python is moving toward a GIL-optional future. PEP 703 has been accepted, which means: • The GIL is not removed yet. • Python 3.13+ introduces experimental no-GIL builds. • GIL-free Python will be optional at first. • Libraries need time to adapt. Reality today, - GIL is still here. - Most Python code still runs with GIL. - True multi-core CPU threading is coming — gradually. 💡 Quick summary • GIL = safety over speed. • Threads ≠ parallel CPU execution (today). • I/O-bound tasks are mostly unaffected. • GIL removal is real — but it’s a journey, not a switch. Save this if Python threading ever confused you, What confused you most about the GIL when you first learned it? #Python #GIL #Multithreading #PEP703 #SoftwareEngineering #PythonDeveloper

Ever wondered why Python sometimes says two equal-looking numbers are not equal? 🤔 Python Code: a = 0.1 + 0.2 b = 0.3 print(a == b) print(round(a, 1) == b) At first glance, 0.1 + 0.2 should be exactly 0.3. But Python works with binary floating-point values, not human-friendly decimals. So instead of storing 0.3, Python internally gets something extremely close to it — but not exactly the same. That tiny difference is enough to make a == b evaluate to False. Rounding brings both values into the same precision range, which is why the second comparison evaluates to True. This is the reason why, in real-world data science and analytics, direct float comparisons are avoided. A safer approach: Copy code Python import math math.isclose(a, b) Key takeaway: Numbers in Python can look equal, behave equal, and still be unequal in memory. #Python #DataScience #ProgrammingInsights #FloatingPoint #TechLearning #CodingConcepts

LeetCode Progress | 219. Contains Duplicate II (Python) Today I solved “Contains Duplicate II” on LeetCode. Problem: Given an integer array nums and an integer k, return True if there exist two different indices i and j such that: -- nums[i] == nums[j] -- abs(i - j) <= k My approach: I used a dictionary to store the most recent index of each number. While iterating: -- If the number already exists in the dictionary and the index difference is <= k, return True -- Otherwise, update the number’s index in the dictionary What I learned: -- A dictionary helps track the latest occurrence efficiently (average O(1) lookup) -- Updating the stored index ensures we always compare with the closest previous occurrence -- This gives an optimal solution with O(n) time complexity #leetcode #python #dsa #datastructures #algorithms #coding #programming #problemSolving #softwareengineering #computerscience #interviewprep #codinginterview #100daysofcode #pythonprogramming

Performance while running your code, it makes a big difference. Can Python code be compiled to native CPU ? Can a python code be optimized for GPU, pre-compiled to specific HW? no interpreter required at "runtime". means remove interpreter loop. Execution-wise: Much closer to C/C++ Syntax-wise: Much closer to Python This is why Codon is often described as: "Python syntax with C-like performance" Think of Codon as: A new compiled language that looks like Python, not “Python made faster” How Codon Fits Between 'C' and 'Python' Codon: Uses Python-like syntax Removes interpreter overhead Produces C-like binaries try https://lnkd.in/gxZqFgjA no learning curve.

🌙 Day 28/100 | #100DaysOfCode 🚀 Today was all about File Handling in Python — and it felt really powerful! 🐍📁 Here’s what I learned today: 🔹 File Modes "r" → Read file "w" → Write file (overwrite) "a" → Append data "rb" / "wb" → For binary files like images & PDFs Understanding file modes helped me control how data is read and written in files. 🔹 with Statement I learned how with automatically handles opening and closing files, which makes the code cleaner and safer. No need to manually close files ✅ 🔹 Built a Simple File Copier Using file modes + with statement, I created a program that copies data from one file to another — even works for images and PDFs in binary mode! 😄 Small steps, but learning things that are actually used in real projects 💪 Consistency over perfection — moving forward every day. 👉 Tomorrow: more practice + deeper concepts! #Python #FileHandling #100DaysOfCode #LearningInPublic #PythonBeginner #DeveloperJourney #Consistency #TechSkills #DailyLearning