Django MVT Pattern Explained

Today, I’ve been working on Django Views to bridge the gap between user input and the database. 💻 Key Learning: Why use commit=False? I learned that using item = form.save(commit=False) is crucial when you need to modify an object before saving it to the database. In this case, I used it to manually attach the currently logged-in user to the new item. Other implementations today: ✅ Access Control: Secured views with the @login_required decorator. ✅ Dynamic Queries: Used get_object_or_404 for better error handling and filtered related items for a better UX. ✅ Request Handling: Managed the flow between GET (viewing the form) and POST (submitting data). Backend development is like solving a puzzle—every piece of logic matters! 🧩 #Django #Python #BackendDeveloper #CleanCode #SoftwareEngineering #CodingJourney #WebDevelopment

One serializer change turned my API from 1.8s to 200ms. ⚡ Everything was working fine. But something felt off. The API was slow… for no obvious reason. The issue wasn’t the database. It wasn’t Django. It was the serializer. What was happening: I was returning way more data than needed. Nested serializers Unnecessary fields Hidden queries All adding up silently. The fixes: 🔹 Use .only() to fetch required fields 🔹 Use .values() for lightweight responses 🔹 Avoid deep nested serializers unless necessary 🔹 Write custom serializers where control matters The realization: APIs don’t slow down suddenly. They get heavier with every extra field you return. The rule: Return only what the client needs. Nothing more. You don’t need all fields. You just never questioned it. What’s one performance mistake you’ve caught in your API? #SoftwareEngineering #BackendDevelopment #Django #Python #APIDesign #Performance #WebDevelopment #RESTAPI #Developers

Stop chaining .filter() and hoping for the best! 🛑 As I dive deeper into 𝕯𝖏𝖆𝖓𝖌𝖔, I’ve realized that while filter() is great for the basics, Q ᴏbjects are the real "𝙨𝙪𝙥𝙚𝙧𝙥𝙤𝙬𝙚𝙧𝙨" 𝙛𝙤𝙧 𝙘𝙤𝙢𝙥𝙡𝙚𝙭 𝙦𝙪𝙚𝙧𝙞𝙚𝙨. 🦸♂️ Here’s the breakdown from my latest learning session: 🔹 𝙛𝙞𝙡𝙩𝙚𝙧(): Your go-to for simple "𝘼𝙉𝘿" 𝙡𝙤𝙜𝙞𝙘. Clean & readable. 🔸 𝙌 𝙊𝙗𝙟𝙚𝙘𝙩𝙨: The Most Valuable Player for "𝙊𝙍" and "𝙉𝙊𝙏" logic. Essential for building real-world search features. I'm loving the challenge of mastering the Django ORM. It’s amazing how much cleaner your backend code becomes when you use the right tool for the job! 🐍💻 The Rule of Thumb: If your logic says "𝘁𝗵𝗶𝘀 𝗔𝗡𝗗 𝘁𝗵𝗮𝘁", 𝘀𝘁𝗶𝗰𝗸 𝘁𝗼 𝗳𝗶𝗹𝘁𝗲𝗿(). 𝗜𝗳 𝗶𝘁 𝘀𝗮𝘆𝘀 "𝘁𝗵𝗶𝘀 𝗢𝗥 𝘁𝗵𝗮𝘁", 𝗶𝘁’𝘀 𝘁𝗶𝗺𝗲 𝘁𝗼 𝗶𝗺𝗽𝗼𝗿𝘁 𝗤. Which one are you reaching for in your current project? Let's talk Django! 👇 #Django #Python #BackendDevelopment #CodingJourney #WebDev #SoftwareEngineering #LearningToCode #ORM

Knowledge bites - Day 46 What is flask in python ? Flask is a lightweight Python web framework used to build web applications and APIs quickly. It follows a minimalistic approach, giving developers full control instead of enforcing strict project structures. Key features : 1. Lightweight and flexible (micro-framework) 2. Built-in development server and debugger 3. Uses Jinja2 templating engine 4. REST API friendly 5. Easy integration with databases and extensions How it works ? 1. Define routes (URLs) using decorators 2. Each route maps to a Python function 3. Function processes request and returns response 4. Server renders output (HTML/JSON) Example use case • Backend for AI apps (e.g., serving a model via API) • Lightweight dashboards • MVPs and quick prototypes Why it’s popular ? • Simple to learn and start • Highly customizable • Large ecosystem of extensions , like Flask SQLAlchemy , Flask Login and more . #Actionpackd #KnowledgeBites

FastAPI vs Django — my real-world take after working with both: Django is great when: - You need a full-featured framework out of the box   - Admin panel, auth, ORM — everything ready   - You want to move fast on standard applications  FastAPI shines when: - You need high-performance APIs   - You want async support   - You’re building microservices or data-heavy systems  In most modern systems I’ve worked on: 👉 Django for structured apps   👉 FastAPI for APIs and services  There’s no “better” framework.   There’s only the right tool for the problem.  What’s your go-to: FastAPI or Django? #python #fastapi #django #backend #softwareengineering

I just released v0.3.1 of an open-source developer tool I built: **DRF to Django Ninja Compiler**. It's a CLI that auto-converts Django REST Framework code into modern Django Ninja — using Python's AST module to reverse-engineer your serializers, views, URLs, permissions, and settings. 🔧 What it does: • Converts DRF Serializers → Pydantic Schemas (including nested serializers and `Meta.depth`) • Converts DRF ViewSets/APIViews → Ninja `@router` or `@api` endpoints • Detects `@action` decorators and generates dedicated routes • Supports all GenericAPIView variants (ListCreateAPIView, RetrieveUpdateDestroyAPIView, etc.) • Parses urls.py → generates NinjaAPI wiring • Parses REST_FRAMEWORK settings → generates a migration report • Maps permission_classes and authentication_classes to Ninja equivalents • Flags anything it can't auto-translate with inline TODO comments • `--project` flag scans an entire Django app directory in one command 📦 Install: `pip install drf-to-ninja` 🔗 GitHub: https://lnkd.in/dwZxszc7 🔗 PyPI: https://lnkd.in/dHPNhTtK 47 automated tests, security scanning with Bandit, and full CI/CD via GitHub Actions. Now officially in Beta! If you're migrating a Django project or know someone who is — give it a ⭐ and share it. #Python #Django #DjangoNinja #OpenSource #DeveloperTools #BackendDevelopment #Migration

A view works fine in development. Slows down in staging. Crawls in production. What is the infamous N+1 query problem? TL;DR - N+1 is a query that looks like one DB call but fires hundreds. How does it happen? 1. One query fetches a list of objects. 2. Then inside the loop, a related object is accessed. 3. Django doesn't have it. So it fetches it. Once per row. So, 10 orders → 11 queries. 100 orders → 101 queries. No errors. No warnings. The reason is lazy evaluation of queries as discussed in last post. How to identify N+1 query problem? Django Debug Toolbar shows exact query counts per request, use it to check the query count. How to fix this issue? - Fetch related data upfront in single query. - select_related for ForeignKey and OneToOne relationships. Uses a SQL JOIN. One query in total. - prefetch_related for ManyToMany and reverse ForeignKey. Uses a second query, joins in Python. The loop stays identical. The query count drops from N+1 to 2 at most. N+1 is not a Django problem. It's a misunderstanding of when evaluation happens and how it works! I’m deep-diving into Django internals and performance. Do follow along and tell your experiences in comments. #Python #Django #DjangoInternals #SoftwareEngineering #BackendDevelopment

I recently developed 𝗕𝗿𝗲.𝗮𝗸 – 𝗨𝗥𝗟 𝗦𝗵𝗼𝗿𝘁𝗲𝗻𝗲𝗿 𝗪𝗲𝗯 𝗔𝗽𝗽𝗹𝗶𝗰𝗮𝘁𝗶𝗼𝗻 using Django. Bre.ak is a web-based application that converts long URLs into short and easy-to-share links in the format bre.ak/XXXXX. The application provides a clean dashboard interface where users can create, view, and manage shortened links efficiently. 𝗙𝗲𝗮𝘁𝘂𝗿𝗲𝘀: •⁠ ⁠Generate short URLs instantly •⁠ ⁠Dashboard with all created links •⁠ ⁠Automatic redirection to the original URL •⁠ ⁠Website favicon displayed for each link •⁠ ⁠Simple and user-friendly interface 𝗧𝗲𝗰𝗵 𝗦𝘁𝗮𝗰𝗸: Python, Django, HTML, CSS, SQLite, Git Through this project, I gained practical experience in backend development, database integration, and building a complete web application workflow using Django. 𝗚𝗶𝘁𝗛𝘂𝗯 𝗥𝗲𝗽𝗼𝘀𝗶𝘁𝗼𝗿𝘆: https://lnkd.in/gSDZyz4r #Python #Django #WebDevelopment #StudentProject #BackendDevelopment #GitHub #Learning

Title: Async Views — Handle High-Volume Flower Orders 🚀 Opening Hook: Imagine a bustling flower shop in spring, bouquets flying off the shelves! 🌸 How do you ensure every order blooms with efficiency? The Problem: Traditional views can wilt under pressure. Let's look at the typical approach: ```python # BAD approach def handle\_order\(request\): flowers = Flower.objects.all\(\) bouquets = Bouquet.objects.filter\(order=request.order.id\) # Processing logic return render\(request, 'order.html', \{'flowers': flowers, 'bouquets': bouquets\}\) ``` The Solution: Let your orders blossom using Django's async views! 🌼 ```python # GOOD approach async def handle\_order\(request\): flowers\_task = Flower.objects.all\(\) bouquets\_task = Bouquet.objects.filter\(order=request.order.id\) flowers, bouquets = await asyncio.gather\(flowers\_task, bouquets\_task\) return render\(request, 'order.html', \{'flowers': flowers, 'bouquets': bouquets\}\) ``` Think of it like arranging multiple bouquets at once, instead of one by one! Did You Know? 💡 Under the hood, Django's async views allow for non-blocking I/O operations, which means your server can handle other requests while waiting for database queries. Why Use It? - ⚡ Performance impact - 🧹 Code quality improvement - 📈 Scalability advantage The Golden Rule: Async views will help your code "rose" to the occasion. Engagement Question: How have async views helped your projects? Or what's your favorite tip for using them? Share below 👇 Hashtags: #Django #Python #WebDevelopment #Backend #Performance #FlowerShop #DjangoORM

Ever wondered why Django is called “the web framework for perfectionists with deadlines”? 🚀 Here’s something interesting 👇 When Django was first created at the Lawrence Journal-World newspaper, the developers needed to build news websites very fast while handling real-world problems like authentication, content management, and database handling. Instead of rewriting the same code again and again, they built reusable components, and that idea became Django. That’s why Django today comes with so many things already built in: ✅ Authentication system ✅ Admin dashboard ✅ ORM for databases ✅ Security protections (CSRF, SQL injection, XSS) In simple words: Django lets developers focus on building features, not reinventing the basics. That’s one reason why companies like Instagram and Pinterest have used Django at scale. 💡 Lesson: The best tools in tech often come from solving real problems under pressure. #Python #Django #WebDevelopment #Programming #SoftwareDevelopment #Tech #Inovation