Django ORM Practice Online with Django ORM Playground

Got to know about FastAPI while building something with Python… and honestly? I didn’t expect backend development to feel this clean. 👀 As a beginner, I thought APIs would be: confusing code heavy setup 100 files open instant headache 💀 Then I tried FastAPI. and got to know: ⚡ It’s fast 🧠 Easy to read 📄 Auto docs generation felt magic 🚀 Clean structure for real projects 🐍 Perfect if you already know Python basics For the first time, backend felt less scary and more buildable. That feeling when your API actually runs… different level dopamine 😭 Still learning. Still beginner. But now I understand why people love FastAPI. Sometimes all you need is one good tool to make tech feel possible. Anyone here started with FastAPI too? #FastAPI #LearningInPublic #Python #DevOps #AI #Automations

Your users are waiting. And leaving. Because your response takes too long. You send everything at once. Big mistake. Django has a hidden weapon: StreamingHttpResponse. Instead of waiting… It sends data in chunks. User sees data instantly ⚡ No loading pain. No frustration. Use it when: → Large files → Real-time output → Slow processing Stop making users wait. Stream it. #Django #Python #WebDevelopment #BackendDevelopment #DjangoTips

#Flask turns 16 today 🎉 Did you know Flask started as an April Fools’ joke by Armin Ronacher? What began as a small experiment became one of the most widely used Python web frameworks. 16 years later, it’s still powering everything from quick prototypes to production apps. 💡 About the original “Denied” microframework: Armin created “Denied” to poke fun at early microframeworks that avoided dependencies by packing everything into a single file. So he did exactly that – embedding Jinja2 and Werkzeug as a base64-encoded `.zip` inside a single Python file. A month later, the idea evolved into something real. That project became Flask – turning a joke into a framework developers still rely on today. What do you use Flask for the most?

Flask has long been my go-to for deploying ML models. It's easy to use and lightweight. Companies sometimes assume that using custom ML models means having to adopt [insert big, complicated framework here]. Maybe they'll need that down the road. Maybe. But for those first steps, Flask is the way to go. (I can already see the confused looks, so: yes, I still write code and build models! It's no longer my everyday. But it's my often-enough.)

If you’ve ever felt like type hints in Python are getting…out of hand, you’re not alone. In this talk, Carlton Gibson (Django Steering Council) breaks down a real tension: Python was designed to stay dynamic, and type hints were never meant to be mandatory. But today, many teams feel pressure to add them anyway. Consider #Django, for example: • It’s built on dynamic patterns (introspection, minimal boilerplate, etc.). • Static typing often can’t fully represent those patterns. • Adding types can increase complexity without real safety gains. • Sometimes you’re just repeating yourself to satisfy the type checker. So what’s the alternative? Don’t force typing where it doesn’t fit. Keep Python dynamic – and add types where they actually bring value. The key takeaway: Instead of rewriting frameworks like Django, build typed layers on top – keeping flexibility while adding structure where needed. Don’t think “types vs. no types.” Think about using the right tool in the right place. ▶️ Watch the full talk: https://lnkd.in/eptmtpHj #Python #Django #TypeHints #StaticTyping #WebDevelopment

Today I learned something powerful while building my backend with Django At first, I thought all text fields were the same… but I quickly realized that’s not the case. ✅ CharField is best for short text (like names, titles, etc.)
✅ TextField is designed for longer content (like user complaints or descriptions) That small difference can actually affect how flexible and scalable your application becomes. But what really stood out to me was this: ✅ ForeignKey allows you to connect different parts of your system together. Instead of storing random text like a user’s name, you can link an appointment directly to: * A real user * A real doctor This makes your system:
✅ More structured
✅ More reliable
✅ Closer to real-world applications I’m currently building a system where appointments are no longer just data they represent real relationships between users and doctors. Small concepts… big impact 🚀 #Django #BackendDevelopment #WebDevelopment #SoftwareEngineering #LearningInPublic #Python #APIs

Day 9 of #30DaysOfPython ✅ Today I stopped letting my code crash. Exception handling. Here's what my scripts looked like before today. You type the wrong thing, Python throws a wall of red text at you, the whole program dies, and you sit there feeling personally attacked. Today I learned how to catch those errors before they explode. Wrap the risky code in a try block, tell Python exactly what to do if something goes wrong in the except block, and your program keeps running like nothing happened. The moment that sold me: I wrote a simple division script. Without exception handling, typing 0 as the divisor crashed everything with a ZeroDivisionError. With a try/except block, it just printed "hey, you can't divide by zero" and moved on. Same error. Completely different experience. The thing that tripped me up: I was writing bare except blocks — catching every possible error without specifying which one. My mentor's voice in my head (okay, it was a Stack Overflow answer) told me that's bad practice. If you catch everything, you also catch errors you didn't know existed and hide real bugs from yourself. Always name the exception. except ValueError, except FileNotFoundError, except ZeroDivisionError. Be specific. The finally block was the other thing that clicked today. Code inside finally runs no matter what — whether the try succeeded or the except caught something. Perfect for cleanup tasks. Closing a connection. Printing a summary. Saying goodbye gracefully. What I covered today: try / except — the basic safety net Catching specific exceptions by name else block — runs only if no error occurred finally block — runs always, no matter what Raising your own errors with raise Today's mini project: a safe calculator. It handles division by zero, invalid inputs, and unknown operations — all without crashing once. Day 9 done. My code finally fails gracefully. 🎯 👇 What's the most unexpected error you've ever had to catch in Python? I want to know what's waiting for me further down this road! #Python #30DaysOfPython #ExceptionHandling #BuildInPublic #CleanCode

I did not expect a Python topic about “unique items” to feel this useful… but sets changed that fast. 🐍 Day 7 of my #30DaysOfPython journey was all about sets, and this one felt different because it was less about storing data and more about controlling it. A set is an unordered collection of distinct items. It cannot hold duplicates, which makes it super handy in real-world coding. Today I explored: 1. Creating sets with set() built-in function and {} 2. Checking length with len() 3. Using in to check if an item exists 4. Adding items with add() to add a single item and update() for multiple items 5. Removing items with remove() (raise error if item not present), discard() (does not raise error), and pop() (removes a random item) 6. Clearing a set with clear() 7. Deleting a set with del 8. Converting a list to a set to remove duplicates 9. Set operations like union(), intersection(), difference(), and symmetric_difference() 10. Checking issubset(), issuperset(), and isdisjoint() What made sets interesting to me today was how practical they are when you want uniqueness, comparison, or clean data without duplicates. They may look simple on the surface, but they solve a very specific kind of problem really well. Which Python data type has surprised you the most so far: lists, tuples, or sets? Github Link - https://lnkd.in/eJfTX-HQ #Python #LearnPython #CodingJourney #30DaysOfPython #Programming #DeveloperJourney

🚀 Not every day needs to be posted… but every day needs progress. While I’ve been a little silent here, I’ve been consistently working behind the scenes — focusing on what truly matters: building strong fundamentals. 💡 Over the past few days, I’ve been: • Sharpening logic building & problem-solving skills • Practicing and implementing concepts in Python & SQL • Building and refining projects using HTML, CSS, and Django • Focusing on writing clean, structured, and efficient code This phase isn’t about speed — it’s about clarity, depth, and real understanding. I’ve learned that: 👉 Strong basics = Real confidence 👉 Consistency > Motivation 👉 Small daily improvements create big results No shortcuts. Just discipline, practice, and growth. 📈 Back again — stronger, clearer, and more focused! #LearningJourney #Consistency #GrowthMindset #Python #WebDevelopment #Django #SQL #PlacementPreparation #KeepBuilding 🚀

Day 46/60 of #60DaysOfMiniProjects Built a Smart Study & Mood Tracker using Flask! Excited to share my latest project where I combined productivity tracking with a touch of intelligent suggestions Features: • Track daily study sessions with mood & notes • Smart suggestions based on mood and activity • Productivity score calculation • Daily streak tracking • Search, edit, and manage past sessions • Clean and simple user interface Tech Stack: Python | Flask | JSON | HTML/CSS This project helped me understand how small data insights can improve consistency and focus in daily routines. Would love your feedback and suggestions to improve it further! #Python #Flask #WebDevelopment #StudentProjects #Productivity #CodingJourney #OpenToLearn