Introducing Honeybadger's adaptive dashboards for error monitoring

THE STATE OF DJANGO 2025: MY HUMBLE INSIGHTS The annual survey is out, and to save you a long read, here are my top takeaways. Surprising Facts: - shift back toward server-side templates - HTMX/Alpine.js are on the rise, dedicated frontends (React, Vue) on decline (back to full-stack Django?) - StackOverflow is still the #2 learning resource, 1% ahead of AI. - VS Code beats PyCharm for Django users and best dedicated AI IDE (Cursor) is only at 2% - 70% of Django devs whose primary language isn't Python use C/C++ (what is the link here?) - 80% use print or log statements for debugging (is this saying about the "importance" of advanced debug tools or more about Django devs' skills? 🙂 ) Interesting Facts: - pytest is more popular than Django's built-in unittest - 75% are on the latest stable release (while 21% on the latest LTS) - 80% use Django for full-stack development - despite AWS being the top cloud host, only 3% use AWS CodePipeline for CI and 5% use CloudFormation for infra (it’s good to be an outlier 🙂 ) - 84% want type hints in Django core (step the right way if you ask me) Warning/Disappointing Fact: - Django is heavily used by highly skilled developers - 30% have 11+ years of experience (is this a sign of a high learning curve, or is the framework slowly dying?) New Fact (I Learned): - DRF has an alternative in django-ninja. Need to check this out. - there is several Django dedicated podcasts! Look it up on the listening platform of your choice! Closing Fact: - 19% of Django devs are in their 40s. (just saying) None of the above makes any difference to the most important fact: I happily continue my Django journey into the 4th year in both professional and personal web software development. Long live Django! #python #django #insights #softwaredevelopment Source: https://lnkd.in/gh5V45Ke

🚀 Unleash Performance: A Deep Dive into Django's Asynchronous ORM Queries The 5-Second Wait That Changed Everything I watched my Django API return data in 5 seconds. Five Entire Seconds. The culprit? Sequential database queries waiting for each other like customers in a slow checkout line. Then I discovered Django's async ORM, and those 5 seconds became 500 milliseconds—a 10x performance boost. Today, I'll show you exactly when to use synchronous vs asynchronous Django, how async/await transforms database operations, and which approach fits your project. By the end, you'll make confident architectural decisions that scale. Imagine a restaurant with one chef who: Takes order #1 → Cooks it → Serves it Takes order #2 → Cooks it → Serves it Takes order #3 → Cooks it → Serves it This is synchronous programming. Each task blocks the next one. Customers wait in line. # Synchronous Django \(Traditional\) def get\_dashboard\_data\(request\): user = User.objects.get\(id=1\) # Wait 50ms orders = Order.objects.filter\(user=user\) # Wait 100ms products = Pr https://lnkd.in/ghSEfDGQ

TaskMaster – A Personal To-Do List Web Application #todolist🧠💻 I’m excited to share my latest project — TaskMaster, a fully functional and responsive To-Do List Web App built from scratch using HTML, CSS, and Python (Flask), integrated with MongoDB Atlas for seamless data storage. ✨ About the Project: TaskMaster is designed to help users stay organized and productive by allowing them to create, manage, and delete their daily tasks efficiently. Each user has a personalized dashboard — so after signing up and logging in, they see only their own to-do items securely stored in the database. 💡 Key Features: 🔐 User Authentication: Secure sign-up and sign-in using Flask and bcrypt encryption. 🧾 Personal Dashboard: Each user’s tasks are stored and retrieved independently. ⚡ CRUD Functionality: Add, view, and delete tasks with real-time updates. 🖥️ Responsive UI: Built with clean and modern HTML/CSS for a smooth experience on any device. ☁️ Cloud Integration: MongoDB Atlas is used for remote database hosting, ensuring scalability and data persistence. 🧠 REST API Handling: Flask backend handles API requests efficiently for user and task management. 🎯 What I Learned: This project helped me strengthen my understanding of backend-frontend integration, RESTful APIs, and database connectivity. I also gained practical experience with Flask routing, JSON handling, and user session management. Designing a simple yet professional interface enhanced my front-end skills and focus on user experience. 🛠️ Tech Stack Used: Frontend: HTML, CSS, JavaScript Backend: Python (Flask) Database: MongoDB Atlas Libraries: Flask-PyMongo, Flask-Bcrypt, Flask-CORS I’m proud of how this project turned out — clean, responsive, and user-friendly. TaskMaster is more than a to-do app; it’s a small step toward mastering full-stack development and building practical, real-world applications. 🚀 Next step: deploying it online and adding extra features like task deadlines, priority levels, and user profile customization. #WebDevelopment #FullStack #Python #Flask #MongoDB #HTML #CSS #JavaScript #DeveloperJourney #CodingProjects #ProductivityApp #ToDoApp #TaskMaster #Programmer #SoftwareDevelopment #LearningByBuilding #ProjectShowcase

⚛ React Hooks & State Management (#MERN_06 in MERN Series) Unlock the power of React Hooks to manage state, side effects, and reusable logic making your components cleaner, faster, and smarter 💡 What You’ll Learn ● useState useEffect and useContext basics ● Manage component and global state efficiently ● Optimize performance with useMemo and useCallback ● Build reusable logic with custom hooks ⚙ Key Highlights 🎯 Simplify logic with Hooks instead of classes 💻 Handle side effects and data fetching easily 🔄 Reuse logic across components 🚀 Foundation for React Routing and Context API Start mastering React Hooks today 👇 🔗 https://lnkd.in/gtQMp2P5 #MERNStack #ReactJS #WebDevelopment #Frontend #JavaScript #FullStack #Coding #LearnToCode

Tales of a Backend Developer... Most developers overcomplicate FastAPI setup. Here's how I deploy production-ready APIs in under 5 minutes. I've been building backends all through this year, and FastAPI changed everything for me. Let me break down exactly how I set it up (no fluff, just the real steps). Step 1: Install FastAPI Open your terminal and run: pip install fastapi uvicorn That's it. Two libraries. FastAPI for the framework, Uvicorn to run your server. Step 2: Create your main file Make a file called main.py. This is where your API lives. Write a simple endpoint like @app.get("/") and return something basic like {"message": "Hello World"}. Step 3: Run your server Type this in your terminal: uvicorn main:app --reload The reload flag means your server restarts automatically when you change code. Super helpful during development. Step 4: Test it Go to localhost:8000 in your browser. You should see your message. Want to see all your endpoints? Go to localhost:8000/docs. FastAPI gives you automatic documentation. No extra work needed. Step 5: Add your dependencies As you build, you'll add more libraries. Run: pip freeze > requirements.txt This saves all your installed packages. When someone else runs your code, they just do: pip install -r requirements.txt Step 6: Build your endpoints Add GET, POST, PUT, DELETE routes. Handle your data. Connect to databases. FastAPI makes it super clean with type hints. Step 7: Deploy, you can use Railway, Render or Leapcell. Render works best for me but the server can go to sleep if not active. I heard railway is the best but it is only free for 30 days. That's genuinely it. No magic. No complex setup. Just clean, fast Python code. The best part? FastAPI automatically validates your data, generates docs, and runs crazy fast. It's literally the easiest way to build APIs in Python. Been using it for client projects, personal tools, everything. Never looking back. What's your go-to backend framework? #EDCChallenge Glory Agu Day 4

🔥 {5 Django Features That Save Me Hours Every Week} I’ve been building projects in Django long enough to realize one thing you don’t need fancy libraries to be productive. Django itself gives you power tools hidden in plain sight. Here are 5 features I rely on constantly that save me hours every single week 👇 ⚙️ 1️⃣ Django Admin: Instantly create a production-ready dashboard without writing a single line of frontend code. Customize it once and forget about repetitive CRUD UI. ⚙️ 2️⃣ QuerySet API: Write complex database queries in clean, Pythonic code. No messy SQL, no confusion just readable logic that performs. ⚙️ 3️⃣ Signals: Automate side effects like sending emails, updating logs, or syncing data whenever certain actions occur. Less manual handling, fewer bugs. ⚙️ 4️⃣ Middleware: Centralize tasks like authentication, logging, and performance tracking one place, global impact. ⚙️ 5️⃣ Built-in Authentication System: Stop wasting time reinventing user management. Django’s auth system handles registration, login, password resets, and permissions out of the box. 🧠 The takeaway: Django’s real power isn’t in what you add it’s in what you leverage. Master these features, and you’ll build faster, cleaner, and more maintainable systems. 💬 Which Django feature do you think deserves more attention? #Django #Python #WebDevelopment #Backend #SoftwareEngineering #DeveloperProductivity

🎯 iterator() vs all() in Django QuerySet: Choose Wisely for Memory Efficiency When working with Django ORM, how you retrieve your data can make a huge difference in memory consumption especially when dealing with large datasets. By default, Django's all() method loads the entire QuerySet into memory and caches it. This is great for smaller datasets where you'll be reusing the same objects multiple times, but it becomes a memory nightmare when processing thousands or millions of records. iterator() changes the game by fetching records in batches and processing them one at a time without caching. It's perfect for one-time iterations over large datasets like bulk exports, data migrations, or batch processing jobs where you don't need to access the same objects repeatedly. all() is your go-to when you need to iterate over a QuerySet multiple times in the same view or function. The caching means subsequent access is lightning-fast, but at the cost of memory overhead. The impact? Using iterator() for large datasets can reduce memory usage by 80-90%, prevent out-of-memory errors, and keep your application responsive even under heavy data processing loads. Pro tip: Combine iterator() with chunk_size parameter to fine-tune batch sizes based on your use case. For example: Model.objects.iterator(chunk_size=2000) gives you control over the memory-performance tradeoff. These methods are built into Django and require zero external dependencies. Sometimes the smartest optimizations are the ones hiding in plain sight in the documentation! #python #django #djangorestframework #orm #queryset #database #performance #optimization #memoryoptimization #scalability #programming #webdevelopment #webdev #cleancode #code #bestpractices #programmingtips #djangotips #developer #backend

💡 Odoo Dev Tip: When in doubt, explore Odoo’s own source code! Today while developing a custom Odoo module, I faced an interesting issue — I needed certain fields to be readonly and also trigger onchange, but when creating a new record, those fields weren’t being saved. I searched everywhere — on the internet, community forums, and even asked AI tools — but couldn’t find a solution that worked. Finally, I decided to dive into Odoo’s core code, and that’s where I found the answer: the hidden gem — the force_save attribute! 💪 ✅ Added force_save="1" in the XML, and boom — problem solved! Always, the best documentation is the Odoo source code itself. #Odoo #OdooDevelopment #DevTips #OdooCommunity #Python #XML #OpenSource #DeveloperLife #CodingTips #odooportal #attendanceportal #timeoffportal #employeeportal #timesheetportal #userportal #customerportal #erpportal #selfportal #miniportal #odoodev #odooservices #odoocrm #crmportal #crmlead

I have just finished building a powerful backend using Node.js and Express.js, powered by a fantastic modern technology called Drizzle ORM! 🚀 This backend handles a unique product transfer system. When you purchase a product, the system seamlessly transfers it to another user, but with a brand new salary attached to it! 💰➡️🔄 Now, you might be asking: "What is Drizzle ORM?" 🤔 Drizzle ORM is a modern, type-safe SQL toolkit and ORM for TypeScript & JavaScript. Think of it as a super-efficient and elegant bridge between your Node.js code and your database! It provides a fantastic developer experience with excellent performance and type safety, making database interactions a joy instead of a chore. It's the perfect tool for building robust and reliable systems like this one! ✨ In short, you don't need to write raw SQL queries; you just write JavaScript/TypeScript code to execute queries, which is a great boost for developer productivity and safety! 🛡️ But you may ask: "What if someone needs to write a complex, optimized query? Can you still work with raw SQL?" Absolutely! Yes, you can! Drizzle ORM is brilliant because it doesn't lock you in. It provides an escape hatch for raw SQL whenever you need it. So for those super-complex reports or performance-critical operations, you can drop down to raw, handwritten SQL queries while still benefiting from Drizzle's type-safety and structure everywhere else. You get the best of both worlds! 🌍✨ #NodeJS #ExpressJS #DrizzleORM #SQL #TypeScript #Developer #BestOfBothWorlds #BackendDev

Django admin panels save us 2 weeks on every MVP build Most founders underestimate this built-in feature. While other teams build custom dashboards from scratch, we're already testing with users. What Django admin gives you out of the box: • Full CRUD operations for all your models • User management with roles and permissions • Bulk actions for data manipulation • Search and filtering across all fields Time savings on typical MVP features: User management dashboard: 40+ hours → 2 hours Content moderation panel: 30+ hours → 1 hour Bulk data operations: 15+ hours → 30 minutes The reality check: Other teams spend weeks building admin interfaces that look prettier but do the exact same thing Django admin does for free. Your users don't care if your backend looks like Bootstrap from 2015. They care if your product solves their problem. When to skip Django admin: You're building a customer-facing dashboard Your data relationships are extremely complex You need a lot of custom complex internal functionality When to use it (90% of MVPs): Content management User support and moderation Any internal tool functionality My rule: If it's not customer-facing, Django admin handles it. Save those 2 weeks for features your users will actually see. What's the most time you've wasted building something that already existed? #Django #MVP #WebDevelopment