Django REST Framework Simplifies API Building with Python

🚀 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 🚀

Django-style Python ORM. Powered by Rust. We are thrilled to announce the very first release of Ryx. It combines the ergonomic query API you love from Django with the raw, async performance of a compiled Rust core. ✨ Highlights ⚡ Rust Engine: Async `sqlx` core, zero GIL blocking, compiled performance. 🐍 Python API: Familiar `.filter()`, `Q` objects, aggregations, and relationships. 🛠️ Full Stack: Migrations, CLI, Validation, Signals, and 30+ Field types. 🗄️ Multi-Backend: PostgreSQL, MySQL, and SQLite support. ⚡️ Quick Start python import ryx from ryx import Model, CharField, Q class Post(Model): title = CharField(max_length=200) active = BooleanField(default=True) await ryx.setup("postgres://user:pass@localhost/db") Query like Django, run like Rust posts = await Post.objects.filter( Q(active=True) | Q(title__startswith="Draft") ).order_by("-title").limit(10) 📦 Installation ...bash pip install ryx 🔗 Links 📖 [Documentation](https://ryx.alldotpy.com 🤝 [Contributing](https://lnkd.in/ecRyYqy3) 🐛 [Report an Issue](https://lnkd.in/eVVsM5rA) Built from scratch with ❤️. If you find this interesting, please leave a ⭐ — it helps a lot!*

Your unittest.mock is lying to you. Tests pass in CI, production breaks, and nobody knows why. The problem? Hand-written mocks drift from the real API silently. I've been contributing to the Microcks open-source ecosystem, and I want to share my latest work on Microcks Testcontainers https://lnkd.in/edzprW5k family for Python. Microcks Testcontainers takes a different approach: your OpenAPI spec becomes the mock. Load it into a Microcks container inside your test suite, and it: - Mocks your dependencies using spec-defined examples - Contract tests your implementation against the spec - Catches API drift automatically I also built a demo app with Flask showing the pattern end-to-end. Library: https://lnkd.in/eXyXwpnB Demo app (Flask): https://lnkd.in/eRhXfKeZ Full step-by-step guide: https://lnkd.in/eBvxUJy8 #Python #Testing #Microservices #API #OpenAPI

🐍📰 The Ultimate Guide to Django Redirects In this detailed guide, you'll learn everything you need to know about HTTP redirects in Django. All the way from the low-level details of the HTTP protocol to the high-level way of dealing with them. #python

Day 544 of Learning – Exploring Python Backend Frameworks 🌐🐍 Explored different Python backend frameworks used to build web applications and APIs, each designed for specific use cases and performance needs. Frameworks like Django provide a full-stack solution with built-in features such as authentication, ORM, and admin panels, making it ideal for large-scale applications. Flask is a lightweight and flexible framework that allows developers to build applications with minimal setup and more control. Modern frameworks like FastAPI and Starlette focus on high performance and asynchronous processing, making them perfect for APIs and real-time applications. Frameworks such as Falcon and Sanic are optimized for speed and are commonly used in high-performance systems. Bottle and CherryPy are simple and beginner-friendly options for smaller applications, while Pyramid offers flexibility by allowing developers to scale from simple to complex applications. Understanding these frameworks helps in choosing the right tool based on project requirements, scalability, and performance needs. Each framework plays an important role in modern backend development and API design. 🚀 #BackendDevelopment #Python #Django #Flask #FastAPI #WebDevelopment #APIs #LearningJourney #Day644

Building APIs shouldn’t feel repetitive. That’s exactly where Django REST Framework (DRF) shines. It abstracts the repetitive parts of backend development—while still giving you control when you need it. You don’t just build APIs faster, you build them cleaner: • Structured serializers • Reusable viewsets • Clear separation of concerns If you’re using Django and not leveraging DRF yet, you’re probably writing more code than you need to. smartData Enterprises Inc. #DjangoRESTFramework #SoftwareEngineering #APIs #Python #smartDataEnterprisesInc

Optimizing Django Queries: How to Avoid N+1 Problems One of the quickest ways to slow down your Django backend is the classic N+1 query issue. While working on Inboxit, I had to be deliberate about this especially when dealing with relationships between models. The fix I use most often: prefetch_related() It’s perfect for optimizing reverse relationships (when you have a ForeignKey pointing to your model and you need to access related data). Instead of making one query per object (which explodes with more records), prefetch_related fetches all the related data in just two queries one for the main objects and one for the related ones. This small change keeps response times fast and your API scalable as usage grows. Have you run into N+1 issues in your Django projects? What’s your go-to optimization technique? #Django #DRF #Python #BackendDevelopment #QueryOptimization #TechNigeria #webdev

Your Django app might be slow… and you don’t even know why 👇 One common mistake: ❌ Fetching related data inefficiently Here’s how I fixed a slow API 👇 Before ❌ Multiple DB queries (N+1 problem) After ✅ Used select_related for ForeignKey Used prefetch_related for ManyToMany 💡 Result: Response time reduced from seconds → milliseconds 👉 Rule I follow: select_related → JOIN (single query) prefetch_related → Separate queries, optimized Small changes = huge performance boost 🚀 Have you faced performance issues in Django? #Django #Python #PerformanceOptimization #BackendDeveloper #Database #DjangoDeveloper #DjangoTips #PythonDeveloper #BackendDevelopment #DjangoRestFramework #APIDevelopment #ServerSide #Programming #SoftwareDevelopment #CodingLife #DevCommunity

Not all Python backend frameworks are the same 🤯 If you're new to backend or just curious how apps are built, here’s a simple breakdown: 🔹 Flask → Lightweight & flexible 👉 You build everything yourself 🔹 Django → Full-stack framework 👉 Comes with admin panel, auth, database tools 🔹 FastAPI → Fast & modern 👉 Built for high-performance APIs 💡 Simple way to understand: Flask = Empty kitchen 🍳 Django = Full restaurant 🍽️ FastAPI = Smart automated kitchen ⚡ Each one is powerful — it just depends on your use case 👉 Which one do you prefer or want to learn? #Python #BackendDevelopment #Django #FastAPI #Flask #WebDevelopment #Programming #TechExplained

Most Django developers don’t realize this… The ORM is silently killing their performance. I’ve seen APIs go from: ⚠️ 300 queries → ⚡ 3 queries Just by fixing QuerySet usage. In this carousel, I broke down: - N+1 problem - select_related vs prefetch_related - F expressions - Real production mistakes If you're working with Django, this is a must-know. Full guide here 👇 https://lnkd.in/dVuaXBMq #Django #Python #DjangoORM #WebDevelopment #BackendDevelopment #SoftwareEngineering #DatabaseOptimization #ProgrammingTips #Developers #CodingLife #BuildInPublic