ABHISHEK SAHU’s Post

Python teaches boundaries in the most unexpected ways 😅 Functions really have personalities: Local variables: “I’m only here for this function.” They live inside a function and disappear once it’s done. Global variables “I belong to everyone.” Accessible anywhere in the file… but if you modify them carelessly, your whole program feels it. Nonlocal variables “I’m not global, but I’m not just local either.” They live in an outer function and can only be modified in an inner function if you explicitly declare nonlocal. Here’s what stood out to me: Coming from JavaScript, I was used to closures just working. In JavaScript, if an inner function sees a variable in its outer scope, it can modify it directly. No special keyword. In Python? If you want to modify a variable from an enclosing function, you must explicitly say nonlocal. If you don’t, Python quietly creates a new local variable instead. Same concept. Different philosophy. JavaScript assumes intent. Python requires you to declare it. And that small difference changes how you think about state, structure, and responsibility in your code. Scope isn’t just syntax. It’s architecture. Boundaries matter. In code and in life. #Python #JavaScript #BackendJourney #SoftwareEngineering #WomenInTech

Building in a new language is painful. I felt it myself when I picked Python over Node.js I mainly build in Node.js. But I decided to build a misinformation-detection tool in Python. The first 2 days felt like climbing a mountain — wrong syntax, different patterns, constant confusion. I changed my approach ,first principles over framework habits. Instead of asking "how do I do this in Python like I do in Node?", I asked: "How does this actually work under the hood?" It change how i code and think : => I understood middleware by learning how requests are parsed — not just how to write one. => I stopped copy-pasting patterns and started understanding request cycles and headers => I became faster at picking up new languages If you're stuck in one language or framework, stop learning syntax first. Learn the why behind what the framework is doing for you.

My Python RAG pipeline choked at 50 concurrent users. So I ripped out the orchestration layer and rebuilt it in Node.js. Unpopular opinion: Python is the king of training. But for serving? It’s too heavy. When you move from a Jupyter notebook to real-world WebSockets, things break. I didn't just need inference. I needed: • To handle 1,000+ concurrent embeddings. • Non-blocking streams. • Zero serialization headaches. Python’s GIL (Global Interpreter Lock) fought me every step. Node’s event loop ate the load for breakfast. The new stack: 1. Training: Python (obviously). 2. API/Orchestration: Node.js + TypeScript. 3. Vector DB: Pinecone. The result? 40% lower latency and no thread-blocking nightmares. Use the right tool for the layer, not just the language you learned first. What is the biggest bottleneck in your current stack? #VectorDatabase #RAG #Javascript

What can’t we do with Python? 🤔 Every time I think I’ve explored enough… Python casually unlocks another door. This week, I stumbled upon a library called FreeSimpleGUI — a lightweight way to build desktop applications without diving into heavy frameworks. Curiosity did what it always does. I couldn’t ignore it. So instead of just reading the docs, I built something simple: 👉 A To-Do List desktop application. Nothing fancy. Just: Add tasks Edit tasks Mark complete Clean, minimal UI And honestly? The result was way better than I expected. No complex boilerplate. No overwhelming setup. Just pure Python doing what it does best — making developers feel powerful. Sometimes we think: Python is for data science. Python is for automation. Python is for ML. Python is for backend. But then it quietly whispers: "Hey, I can build desktop apps too." 😄 The best part? You can prototype a working desktop app in hours, not days. 🎥 I’ve attached a short demo video below. 💻 GitHub link is in the comments if you'd like to explore the code: https://lnkd.in/g4nUBw2m If you’re a Python developer and haven’t explored GUI development yet — this might be your sign. What’s the most unexpected thing you’ve built with Python? #Python #OpenSource #DesktopApp #100DaysOfCode #Learning #Developers #FreeSimpleGUI

Python 3.14 is already here—and it’s finally tackling the "Performance Tax." 🐍 After 6 years in the Python ecosystem, I’ve seen my fair share of ‘slow code’ debates. But the 3.14 release (and the 2026 roadmap) is a game-changer for those of us building high-scale backends. Three features I’m currently digging into: 1. Zero-Overhead Debugging (PEP 768): We can finally attach profilers to production processes without the usual "performance hit." This is huge for diagnosing those "it only happens in prod" spikes. 2. Deferred Annotation Evaluation: Faster startup times and cleaner type-hinting without the string-quote hacks. 3. The "No-GIL" Era: We’re moving closer to true multi-core Python. If you’re still writing synchronous, single-threaded code for heavy tasks, it’s time to rethink your architecture. The takeaway? Python isn't just the "easy" language anymore; it’s becoming a performance powerhouse.

Day 3 of my Python journey 🐍🚀 Today was all about logic and control flow. Day 3 focused on how Python makes decisions and repeats tasks. Here is a straightforward breakdown of today's concepts and how they compare to my daily TypeScript/JavaScript work: 🔀 Conditionals (If / Elif / Else): Python drops the parentheses () and curly braces {}. It also uses elif instead of else if. It takes a minute to get used to the indentation, but the code reads beautifully, almost like plain English. 🎯 Match Case: This is Python’s exact answer to the JavaScript switch statement! It makes handling multiple specific conditions much neater than writing a giant wall of if/else blocks. 🔁 Loops (For & While): While loops feel very similar to JS, the for loop in Python is wonderfully simplified. Instead of writing out for (let i = 0; i < 10; i++), Python just uses for i in range(10):. It is so much faster to type. 🛑 Break & Continue: The good news? These work exactly the same way they do in JavaScript to stop a loop or skip an iteration entirely. No mental translation needed here! The syntax is really starting to feel natural now. Progress is steady. 📈 #Python #LearningInPublic #SoftwareEngineering #FrontendDev #CodeWithHarry #100DaysOfCode

I almost rewrote my entire Python backend in Rust this weekend. The problem: generating 300 API calls through Claude was taking 5 hours. One at a time, 60 seconds each. Sequential. Painful. I started researching multithreading. Connection pools. Async Python. Rate limit management. Retry queues. Then I found Anthropic's Batch API. You submit all your requests in one call — up to 10,000 at once. Anthropic handles the parallelism, the rate limits, the infrastructure. You get results back within an hour. And it costs 50% less than standard API pricing. My entire pipeline went from this: 1. Manage threads 2. Handle rate limits 3. Retry failures 4. Monitor progress 5. Pray nothing crashes To this: 1. Submit batch 2. Save the batch ID 3. Go make coffee or take a nap 4. Come back and download results If my script dies mid-wait? Doesn't matter. The batch lives on Anthropic's servers. Grab the ID, check back later. Results stay available for 29 days. Stack prompt caching on top and costs drop even further. No Rust. No async. No infrastructure. Just one API call I didn't know about. The lesson: before you optimize your code, read the docs. The answer might already be built.

« The lesson: before you optimize your code, read the docs. The answer might already be built » Worth a read! (🙋🏻♂️ btw PgCache has docs! If you’re running postgres in the cloud it’ll 3-8x your qps: https://lnkd.in/ejM6g6_w)

Day 6 of my Python journey 🐍🚀 Day 6 is in the books! Today was a mix of handling errors gracefully and discovering some syntax that is completely unique to Python. Here is a breakdown of what I learned and how my Next.js/TypeScript brain processed it: 🛡️ Exception Handling (Try / Except / Finally): In JS, we use try...catch to stop bugs from crashing the whole app. Python uses try...except. The logic is exactly the same, including the finally block that runs no matter what. I also learned how to raise custom errors (just like throw new Error in JS). 🤯 Loops with else: Wait, loops can have an else statement?! This blew my frontend mind a little bit. In Python, an else block attached to a for or while loop will run only if the loop finishes naturally (without hitting a break). Very cool, but definitely takes getting used to! ⚖️ Shorthand If/Else: This is Python's version of the JS ternary operator (condition ? true : false). Instead of symbols, Python reads like plain English: result = True if condition else False. 🕵️♂️ Mini-Project: I put it all together by building a Secret Language Encoder/Decoder! It takes user input, manipulates the strings, and spits out an encrypted (or decrypted) message. The pieces are really coming together, and building actual logic feels great. 📈 #Python #LearningInPublic #SoftwareEngineering #FrontendDev #CodeWithHarry #100DaysOfCode

⁉️ Have you ever actually thought about what __name__ == "__main__" means? Most of us wrote it the first time because a tutorial said so. Today I was structuring a small backend service in Python. Nothing flashy yet, just defining the application entry point. And that familiar line showed up again: ✳️ if __name__ == "__main__": It’s simple, but it solves an important architectural problem. In Python, every file is a module. When you execute a file directly: ✳️ python app.py Python assigns: ✳️ __name__ = "__main__" But when the same file is imported somewhere else: ✳️ import app Now: ✳️ __name__ = "__app__" That difference determines whether certain blocks of code run or stay dormant. Why is that useful? Because it lets you: • Keep runtime logic separate from reusable logic • Prevent accidental execution when modules are imported • Define a clear entry point for your application • Expose objects (like a Flask/FastAPI app instance) without auto-starting the server Without this guard, importing a module could trigger execution unintentionally — which becomes messy in larger systems. It’s one of those small Python conventions that quietly enforces better structure. Not flashy. But foundational. #Python #BackendDevelopment #SoftwareEngineering #Architecture