C++ under the hood of Python's success

Python looks fast. Until you realize C++ is the one carrying it. Python is the Ferrari everyone brags about. But behind every production ML pipeline, game engine, and real-time system? C++ is the flatbed truck doing the actual heavy lifting. → NumPy? C under the hood. → PyTorch? C++ core. → CPython itself? Written in C. Python gives you the syntax. C++ gives it the speed to exist. Most devs never look under the hood. The ones who do? They build differently. I’m not saying ditch Python. I’m saying: know what's actually running your code. The abstraction is the feature. But ignorance of what's beneath it is a liability. What’s one thing you devs never bother to learn about their stack? Drop it below 👇 #Python #CPlusPlus #SoftwareEngineering #SystemsThinking #Developer

𝗪𝗵𝘆 𝗱𝗼𝗲𝘀 𝗣𝘆𝘁𝗵𝗼𝗻 𝗰𝗼𝗱𝗲 𝗳𝗲𝗲𝗹𝘀 𝘀𝗹𝗼𝘄 𝗱𝗲𝘀𝗽𝗶𝘁𝗲 𝘂𝘀𝗶𝗻𝗴 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝘁𝗵𝗿𝗲𝗮𝗱𝘀 ? The secret lies in how Python handles execution. I’ve put together a 12-slide deep dive into Python Concurrency, moving from absolute basics to the future of Python 3.13. What’s inside? ✅ Synchronous vs. Async: Why "𝘄𝗮𝗶𝘁𝗶𝗻𝗴" is the biggest bottleneck. ✅ The Event Loop: How 𝗮𝘀𝘆𝗻𝗰𝗶𝗼 manages thousands of tasks on a single thread. ✅ The 𝗚𝗜𝗟 (𝗚𝗹𝗼𝗯𝗮𝗹 𝗜𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗲𝗿 𝗟𝗼𝗰𝗸): Why traditional Python threading isn't always "parallel." ✅ The 𝗙𝘂𝘁𝘂𝗿𝗲 (𝗙𝗿𝗲𝗲-𝗧𝗵𝗿𝗲𝗮𝗱𝗶𝗻𝗴): How Python 3.13+ finally enables true multi-core parallelism. 🟪 𝗧𝗵𝗲 "𝗞𝗶𝘁𝗰𝗵𝗲𝗻" 𝗔𝗻𝗮𝗹𝗼𝗴𝘆: Think of a single cook (Thread) multitasking between a gas stove (I/O) and a cutting board. That’s Async. Now imagine a kitchen with multiple cooks and multiple gas stoves. That’s Modern Free-Threading. Whether you're building 𝘄𝗲𝗯 𝘀𝗰𝗿𝗮𝗽𝗲𝗿𝘀 (𝗜/𝗢-𝗯𝗼𝘂𝗻𝗱) or 𝗵𝗲𝗮𝘃𝘆 𝗱𝗮𝘁𝗮 𝗽𝗶𝗽𝗲𝗹𝗶𝗻𝗲𝘀 (𝗖𝗣𝗨-𝗯𝗼𝘂𝗻𝗱), choosing the right model is key to performance. Check out the slides below! #Python #Programming #SoftwareEngineering #Concurrency #AsyncIO #Multithreading #Python313 #TechLearning

Practiced Python functions today — *args, **kwargs, return types, and function types. The one thing that clicked — *args is for unknown number of values (stores as tuple), **kwargs is when you don't know the keys either (stores as dict). Simple but I was mixing them up before. Also learned there are actual types of functions — action, transformation, validation. https://lnkd.in/ducSzXzK #Python #LearningInPublic #DataAnalysis

Just shipped LLMPrice 🚀 A lightweight Python + TypeScript library for LLM pricing lookup. - 2500+ models - Offline-first - Search / compare / CLI - Auto-synced pricing data Built for developers who want pricing data only, without pulling in a heavy LLM stack. Links in first comment. #Python #TypeScript #LLM #OpenSource #AIEngineering #DeveloperTools

Day 3/365: Comparing Two Strings Character by Character 🧵🧠 Today I worked on a simple but fundamental logic problem: checking if two strings are the same, without directly using a built-in equality check. First, I compare the lengths of both strings. If lengths differ, they can’t be the same. If lengths match, I loop through each index and compare characters one by one. If any character is different, I break and print that the strings are not the same. If the loop finishes without finding a mismatch, the else block of the for loop runs and prints that the strings are the same. The interesting part is the for-else in Python. The else only runs when the loop completes normally (no break). This makes it a clean way to express: “if I didn’t find any mismatch in the entire loop, then the strings are equal.” Day 3 done ✅ 362 more to go. #100DaysOfCode #365DaysOfCode #Python #LogicBuilding #StringComparison #ForElse #CodingJourney #LearnInPublic #AspiringDeveloper

People sometimes ask me why I still like to work with Python notebooks given that LLMs can also generate web-apps for us. The difference to me comes down to the fact that I really like it when my software is usable like legos. https://lnkd.in/eVDdgBEw

Clean code isn't clever. It's clear. 5 Python patterns every developer should know: 1️⃣ Flatten nested list: flat = [x for sub in nested for x in sub] 2️⃣ Merge dicts (Python 3.9+): merged = dict_a | dict_b 3️⃣ Most frequent item: max(set(lst), key=lst.count) 4️⃣ Swap variables: a, b = b, a 5️⃣ Read + strip file lines: lines = [l.strip() for l in open("file.txt")] --------------- These aren't tricks. They're idiomatic Python. When your code communicates intent: ✅ Reviews go faster ✅ Bugs surface sooner ✅ Onboarding is smoother Write for the developer reading it at 2am before a deployment. That developer is usually you. #Python #CleanCode #Programming #CodingTips #SoftwareEngineering

🚀 Python 3.13+ is a game-changer: Free-threading (no-GIL mode) and experimental JIT boost multithreaded code by 2-5x! Speed gains are real for CPU-heavy tasks. Tested a simple parallel sum script—3x faster than 3.12. Python 3.15 stabilizes JIT fully. Here’s the snippet: # Run with: python3.13 -X free-threading import threading def compute(n): return sum(i*i for i in range(n)) threads = [threading.Thread(target=compute, args=(10**7,)) for _ in range(4)] for t in threads: t.start() for t in threads: t.join() print("Done!") Who’s upgraded? Share your benchmarks below! 👇 #Python #Python313 #Programming

🚀 Built a Python tool that transfers code via QR codes! Introducing PyQR Generator — a desktop app that converts any .py file into scannable QR codes you can read directly on your phone. Here's what it does: → Load any Python file → Generates multiple QR codes (chunks) for large files → Scan each QR with your phone to view the raw code → Copy and use it anywhere — no internet, no USB needed! Built with Python + qrcode — 100% offline and open source. Sometimes the simplest ideas solve real problems. 💡 #Python #Automation #BuildInPublic #QRCode #OpenSource #PythonDeveloper