Django Debug Queries in Templates

Built an API in Django today. What I expected: “Quick endpoints. Clean responses. Done in 1 hour.” What actually happened: 1 missing comma 2 migrations 5 server restarts 17 “Why is this not working?” moments But when that endpoint finally returns 200 OK… Nothing feels more powerful. 💻🔥 Still building. Still debugging. Still loving Python. #Python #Django #API #BackendDeveloper #DevLife

I optimized a Django API from 12s → 200ms. Here's the 6-step playbook 👇 1️⃣ Measure first — Django Debug Toolbar showed N+1 queries everywhere 2️⃣ Fix N+1 — select_related() and prefetch_related() = biggest win 3️⃣ Count in SQL — replaced Python loops with annotate() 4️⃣ Paginate — stop returning massive datasets 5️⃣ Add indexes — on fields you actually filter and sort by 6️⃣ Cache last — Redis only after fixing the real problems The lesson? Caching should come LAST, not first. Performance isn't magic. It's: Measure → Fix → Measure again. #Django #Python #BackendDevelopment #APIOptimization #WebDevelopment #DRF #SoftwareEngineering

Do Django Devs Use Proxy Models? Did you know you can create a "Ghost Model" called a Proxy Model that lets you add Python methods or custom managers without creating a new DB table? It’s the perfect way to extend behavior without touching the schema or doing expensive joins. Full Video Link in Comments!

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

Code the Web. Power It with Python. HTML gives structure. CSS gives style. JavaScript gives interaction. But Python? Python gives logic, automation, data, and intelligence. This is where the web stops being static and starts becoming smart: • APIs that actually scale • AI features that solve real problems • Backends that connect everything together I stopped asking “Which language should I learn next?” and started asking “What can I build with what I know?” That shift changed everything. If you’re learning web development: 👉 Don’t chase tools 👉 Build projects 👉 Let Python power the web you create What’s one thing you’ve built (or want to build) with Python + Web? Drop it in the comments 👇

One Python backend mistake that quietly hurts performance ❌ Running database queries inside loops for user in users: profile = Profile.objects.get(user=user) Looks harmless… until your user base grows 😬 Congrats, you've just invited the N+1 query problem. ✅ Better approach profiles = Profile.objects.filter(user__in=users) 📈 Why this small change matters: Prevents N+1 queries Drastically cuts down database hits Improves API response time Scales much better in production 💡 Backend performance isn't about writing more code. It's about writing smarter queries. 💬 Have you run into N+1 issues in real-world projects? How did you catch or fix them? #python #django #backenddevelopment #performanceoptimization #database #softwareengineering #webdevelopment https://lnkd.in/dxwAC3FF

My Python 'imports' for every project. ```python import requests import pandas as pd from bs4 import BeautifulSoup import time import random ``` The building blocks of the web scraping world. What is your first import? #python #code #developer #basics

One Python backend mistake that silently kills performance Doing database queries inside loops: for user in users:   profile = Profile.objects.get(user=user) This looks fine… until your user count grows 😬 Optimized approach: profiles = Profile.objects.filter(user__in=users) Why this matters: Avoids N+1 query problem Reduces database hits drastically Improves API response time Scales better in production Backend performance is not about writing more code, it’s about writing efficient queries. 💬 Have you faced N+1 issues in real projects? #python #django #backenddeveloper #performanceoptimization #database #softwareengineering

Today, I deepened my understanding of backend development using Python and Flask. What I learned: ✔️ How Flask handles routing ✔️ GET vs POST requests ✔️ Connecting frontend forms with backend logic ✔️ Basic project structure organization Understanding how data flows between client and server made the concepts much clearer. Step by step, I’m building a strong foundation in backend development. #Python #Flask #BackendDevelopment #WebDevelopment #LearningJourney

💡 𝗧𝗶𝗽 𝗼𝗳 𝘁𝗵𝗲 𝗗𝗮𝘆 — 𝗗𝗷𝗮𝗻𝗴𝗼 𝗗𝗶𝗱 𝘆𝗼𝘂 𝗸𝗻𝗼𝘄? Using "only()" and "defer()" in Django can significantly reduce query payload when you don’t need every model field. 🔧 "only()" → Load 𝘰𝘯𝘭𝘺 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘤 𝘧𝘪𝘦𝘭𝘥𝘴 🔧 "defer()" → Load 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘦𝘹𝘤𝘦𝘱𝘵 𝘴𝘱𝘦𝘤𝘪𝘧𝘪𝘦𝘥 𝘧𝘪𝘦𝘭𝘥𝘴 Why it matters: - Less data transferred from DB - Lower memory usage - Faster responses for large models Smart field selection = better performance. #Django #Python #BackendDevelopment #WebDevelopment #PerformanceOptimization #SoftwareEngineering #CodingTips #FullstackDeveloper