Muhammad Usman’s Post

A lot of backend discussions today revolve around performance. One framework that impressed me recently while building APIs is FastAPI. What stands out is how quickly you can build clean, high-performance APIs without adding too much complexity. A few things I personally like while working with it: • Automatic API documentation without extra setup • Type hints that make code easier to maintain • Great performance for async workloads • Very simple to connect with existing Python services For projects that are API-first — microservices, integrations, or mobile backends — it feels very efficient. Sometimes the right tool isn’t the biggest framework… it’s the one that keeps things simple and fast. Curious to hear from other developers — Are you using FastAPI, or sticking with Django or Flask for APIs? #FastAPI #Python #BackendDevelopment #APIDevelopment #SoftwareEngineering #Developers

🚀 Why Pagination is Important in APIs (A Small Learning) While working with APIs, I realized that returning large amounts of data at once can impact performance and user experience. Here’s what I understood about pagination: 🔹 Instead of sending all records, APIs return data in smaller chunks 🔹 Improves response time and reduces server load 🔹 Makes it easier for frontend to handle and display data 💡 In Django REST Framework, pagination can be easily implemented using built-in classes like PageNumberPagination. ⚠️ One thing I noticed: Without pagination, APIs may work fine initially but can become slow and inefficient as data grows. This made me understand how important it is to design APIs keeping scalability in mind. Still exploring more ways to build efficient and scalable backend systems 🚀 How do you usually handle large data responses in your APIs? #Django #Python #BackendDevelopment #API #WebDevelopment #LearningInPublic

I kept writing Django APIs… but something felt off. The code was working. Responses were coming. But if someone asked me: 👉 “What actually happens when a request hits your API?” …I didn’t have a clear answer. That bothered me. So I went back to basics. Not tutorials. Not copying code. Just understanding one simple flow: User → request → view → model → database → response And suddenly, things started clicking: Patient.objects.all() is not just a line of code… it’s a query hitting the database and returning structured data. request is not just a parameter… it’s literally everything the user is sending to your backend. GET, POST, PUT, DELETE are not just methods… they define how your system behaves. The biggest realization? 👉 I was focusing on “how to write code” 👉 instead of “how things actually work” Now I approach backend differently: I don’t start with code. I start with flow. And that small shift is making a huge difference. Still learning. But now it feels real. #Django #BackendDevelopment #Python #LearningInPublic #SoftwareEngineering #BuildInPublic

Django became easier when I stopped memorizing and started thinking about systems. Earlier, I was focused on learning syntax: views, models, forms... But things only started making sense when I shifted my thinking. Now I see backend development like this: • A request enters the system • It gets routed through URLs • Logic runs inside views • Data is handled through models/ORM • Validation protects the system • Permissions control access • A clean response is returned This simple shift changed everything for me. Instead of asking: “How do I write this in Django?” I now ask: “How should this system behave?” That mindset is helping me: • understand backend concepts faster • write cleaner code • prepare better for real-world backend interviews Backend development is not about memorizing features. It is about understanding systems. What changed your thinking as a developer? #Django #Python #BackendDevelopment #SoftwareEngineering #PythonDeveloper #WebDevelopment #LearningInPublic

FastAPI vs Django: Which Wins in 2026? The best framework isn’t the one with the most features—it’s the one that solves your specific bottleneck. If you’re choosing for your next project, here’s a breakdown: Why the industry is shifting to FastAPI - Performance: Built on Starlette and Pydantic, it’s one of the fastest Python - - frameworks. Ideal for high-concurrency or I/O-bound tasks. - Developer velocity: Automatic OpenAPI (Swagger) docs and Python type hints reduce time spent on documentation. - Modern stack: Designed for microservices, AI/ML deployments, and modern frontends like React or Next.js. Why Django isn’t going anywhere - Batteries included: Comes with admin panel, authentication, and ORM out of the box. - Security: Built-in protection against common web vulnerabilities. - Stability: Strong structure for large-scale monoliths and enterprise applications. The verdict Use FastAPI if you want a high-performance engine for modern APIs or microservices. Use Django if you need a fully equipped framework for complex, data-heavy applications. Which side are you on? Are we moving toward a “FastAPI-first” world, or does Django’s ecosystem still reign supreme? #Python #WebDevelopment #FastAPI #Django #SoftwareEngineering #Backend #CodingTips

==Early Import vs Lazy Import (Python / Django) While working on backend projects, I kept facing slow startup and occasional circular import issues. Then I realized — the problem wasn’t always the logic… it was how I was importing modules. ==Early Import (Eager Import) Modules are loaded at the start of the program Example: import math -Simple and clean -Can slow down startup -May cause circular import issues ==Lazy Import Modules are loaded only when needed Example: def calc(): import math return math.sqrt(16) -Faster startup -Reduces unnecessary memory usage -Helps avoid circular dependencies - Real-world (Django) use case: Instead of importing heavy services at the top, import them inside views/functions when needed. -Key takeaway: Don’t always import everything at the top. Sometimes, importing later is the smarter choice. Curious — do you use lazy imports in your projects? 🤔 #Python #Django #Backend #SoftwareEngineering #CleanCode

🚀 What Happens When You Hit an API? (Backend Explained Simply) As a Python & Django developer, one thing I always try to understand deeply is what actually happens behind the scenes when we call an API. Let’s break it down 👇 1️⃣ Client Request You (or frontend) send a request → GET /api/users 2️⃣ Routing Django matches the URL with the correct view 3️⃣ View Logic The view processes the request (authentication, validation, business logic) 4️⃣ Database Interaction ORM queries the database → fetch/update data 5️⃣ Serialization Data is converted into JSON format 6️⃣ Response Server sends back a structured response (status code + data) ⚡ Example Response: { "status": 200, "data": [...] } 💡 Key Learnings: • Clean API design improves scalability • Proper validation = fewer bugs • Efficient queries = better performance 🎯 As developers, we shouldn’t just “use APIs” — we should understand how they work internally. What’s one backend concept you’re currently learning? 👇 #Python #Django #BackendDevelopment #APIs #WebDevelopment #SoftwareEngineering

Async ≠ Non-Blocking (A common mistake I see in FastAPI apps and with Django async views) As backend engineers, we often assume that using async def automatically makes our APIs scalable and non-blocking. But here’s the catch Using blocking code inside async functions can freeze your entire server. The Problem @app.get("/blocking-bad") async def blocking_bad_behavior(): time.sleep(10) # Blocks the event loop! Even though this is an async function, time.sleep() blocks the event loop, meaning: * No other requests are processed * Your API appears “down” for those 10 seconds * No Concurrency The Correct Approach @app.get("/blocking-fixed") async def blocking_fixed(): await asyncio.to_thread(time.sleep, 10) # Offloaded to thread Now: * Event loop stays free * Other requests are handled instantly * True concurrency Even a normal def works safely in FastAPI: @app.get("/normal-def") def normal_def_endpoint(): time.sleep(8) # Runs in thread pool automatically FastAPI smartly runs it in a thread pool — so your event loop is still safe. Key Takeaways async def does NOT guarantee non-blocking behavior Avoid blocking calls like time.sleep(), heavy CPU tasks, or sync I/O Use: * await asyncio.sleep() for async waits * asyncio.to_thread() for blocking work * or stick to def when appropriate Final Thought Async is powerful — but only when used correctly. Misusing it can be worse than not using it at all. If you’re building high-performance APIs with FastAPI, this is something you cannot ignore. #FastAPI #Python #AsyncIO #BackendDevelopment #SystemDesign #Concurrency #SoftwareEngineering

If you’ve ever built APIs in Django REST Framework, you know the pain of writing multiple views for the same model — list, detail, create, update, delete. Messy, repetitive, and error-prone. That’s where ViewSets come in. With just a few lines of code, you get all CRUD endpoints automatically, clean URL routing, and a scalable request flow. In my latest Medium article, I break down: What ViewSets are and why they matter How to secure your APIs with get_queryset() Performance boosts using prefetch_related Query parameter filtering with filter_backends Custom endpoints with @action (like cancel or recent orders) Common mistakes to avoid (permissions, redundant filtering, lost prefetch) This isn’t just about making APIs that “work” — it’s about building APIs that are secure, efficient, and production-ready. 👉 Read the full guide here: https://lnkd.in/diM6UCiZ #Django #RESTAPI #Python #BackendDevelopment #SoftwareEngineering #APIs

🚀 Build Powerful APIs with Python (Django REST Framework & FastAPI) In this post, I've broken down how to create APIs using two of the most popular Python frameworks: Django REST Framework and FastAPI—in a simple, algorithmic, and visual way. 🔹 What's inside the post? Step-by-step API development flow for both frameworks Clear algorithmic approach (from setup -> models -> endpoints -> testing) Practical code snippets to get started quickly Side-by-side comparison of DRF vs FastAPI Tips on when to use each framework 🔹 Django REST Framework Best for large, database-driven applications where you need a complete ecosystem with authentication, ORM, and scalability. 🔹 FastAPI Perfect for high-performance APIs, microservices, and modern apps with automatic validation and interactive docs. 💡 Key Takeaway: Both frameworks are powerful—choose DRF for full-scale applications and FastAPI for speed and lightweight performance. 🔥 Whether you're preparing for interviews or building real-world projects, mastering these tools is essential for every backend developer. #Python #API #Django #FastAPI #BackendDevelopment #WebDevelopment #SoftwareEngineering 🚀