FastAPI with Python: Building Efficient APIs

Built my first Python API using FastAPI! Coming from a MERN background, I decided to explore Python backend development—and it’s been an eye-opening experience. What I built: A simple REST API with GET & POST endpoints Request validation using Pydantic models Auto-generated API docs (Swagger UI) Key Learnings: How FastAPI handles routing (similar to Express but cleaner) Request body validation without extra libraries Importance of virtual environments (and debugging them the hard way) Running production-ready APIs using Uvicorn One thing that really stood out: FastAPI feels like TypeScript + Express, but with built-in validation and performance advantages. Example: Created a POST /user endpoint that validates incoming data using a schema and returns structured responses. GitHub Repo: https://lnkd.in/gF4FFR2u Would love feedback from the community #Python #FastAPI #BackendDevelopment #LearningInPublic #100DaysOfCode

𝗨𝗻𝗱𝗲𝗿𝘀𝘁𝗮𝗻𝗱 𝗬𝗼𝘂𝗿 𝗙𝗶𝗿𝘀𝘁 𝗔𝘅𝘂𝗺 𝗦𝗲𝗿 v𝗲𝗿 𝗕𝘆 𝗖𝗼𝗺𝗽𝗮𝗿𝗶𝗻𝗴 𝗪𝗶𝘁𝗵 𝗙𝗮𝘀𝘁𝗔𝗣𝗜 If you're coming from Python and have used FastAPI, learning Rust's Axum can feel confusing at first. But the good news is: the core ideas are almost the same. Let's break down a simple Axum server step by step and compare it with FastAPI. Here's what you need to know: - Create a web app - Define a route - Start a server - Return a response when someone visits In Axum, you use Router to create the app, get to define GET routes, and SocketAddr to define IP + port. In FastAPI, you use FastAPI to create the app, @app.get to define GET routes, and host + port to define IP + port. The key difference is that in Axum, you manually start the server, while in FastAPI, uvicorn.run does everything for you. You can create a web server that listens on port 3000 and returns a simple message when someone visits. If you're already comfortable with FastAPI, you're much closer to mastering Axum than you think. The concepts are the same - Rust just makes things more explicit and safe. Source: https://lnkd.in/gtHUr9TM

The "Shadow" Fix: Python Version Compatibility **Hook:** Building for the "Latest & Greatest" is easy. Building for the "Real World" is where the engineering gets messy. **Body:** While finalizing my Enterprise RAG pipeline, I hit a silent production-breaker: A `TypeError` buried deep in a third-party dependency. The culprit? The `llama-parse` library uses Python 3.10+ type union syntax (`|`), but the production environment was locked to Python 3.9. Result: Immediate crash on boot. Instead of demanding a system-wide upgrade—which isn’t always possible in locked-down enterprise environments—I implemented a **Graceful Fallback Logic**: ✅ **Dynamic Imports**: Wrapped the cloud-parser initialization in a guarded `try-except` block. ✅ **Smart Routing**: If the Python environment is incompatible, the system automatically redirects to a local, high-fidelity `PyMuPDF` parser. ✅ **System Resilience**: The app stays online, the UI remains responsive, and 99% of RAG functionality remains available without a single user noticing a failure. Real Engineering isn't just about using the best tools—it’s about writing code that doesn't break when the environment isn't perfect. #Python #SoftwareEngineering #RAG #AIEngineering #SystemDesign #Resilience

Have you ever been to dependency hell? A situation where a Python library version is causing a problem in your environment, but you don’t know which library it is and which version you should choose to fix it. Plotly staff member, Celia López Monreal, created a Plotly Dash App to debug dependency issues. More precisely, the app gets insights into library versions that might be causing issues in your Python environment. https://lnkd.in/eEKZYPmj

🚀 Turn any Python CLI script into a modern GUI – with zero extra dependencies. I just open‑sourced PyScript-to-GUI, a tool that instantly wraps your command‑line scripts into a clean, functional graphical interface. ⚡ No more boring terminals. Your users get a real window with dark mode, real‑time output, and interactive input dialogs – without writing a single line of GUI code. ✨ Key features: ✅ Zero external dependencies – uses only tkinter (built into Python) ✅ Smart input() handling – automatically converts prompts into pop‑up dialogs ✅ Live logging – all print() output appears in a scrollable terminal‑style area ✅ Multi‑threaded – the GUI never freezes, even during heavy tasks ✅ Hacker aesthetic – dark grey + lime green theme, ready to impress 🔧 Perfect for: Sharing your scripts with non‑technical colleagues Building quick internal tools with a professional look Teaching Python without scaring beginners with the terminal 🔗 GitHub repo: https://lnkd.in/dDpXCYSk 👨💻 Built by NULL200OK – because every script deserves a beautiful face. #Python #GUI #Tkinter #OpenSource #DeveloperTools #CLItoGUI #PyScriptToGUI #Coding

🐍 Day 23 & 24 of My 30-Day Python Learning Challenge 🚀 Over the last two days, I transformed my Log File Analyzer into a simple web app using Streamlit. 📌 What I Built: ✅ File Upload Feature Users can upload any text file for analysis import streamlit as st file = st.file_uploader("Upload a file") --- ✅ File Reading & Preview if file: content = file.read().decode("utf-8") st.write(content[:200]) --- ✅ Integrated My Previous Logic • Word frequency counting • Data cleaning (punctuation removal) • Stopwords removal • Top frequent words --- 📊 What This Means: • Python script ➝ Interactive Web App • More practical and user-friendly • Closer to real-world applications 💡 Key Learning: Building a UI makes projects more impactful than just writing scripts. 📊 Quick Question Which command is used to run a Streamlit app? A) python app.py B) run app.py C) streamlit run app.py D) start app Answer tomorrow 👇 #Python #Streamlit #MiniProject #WebDevelopment #LearningInPublic #SoftwareDeveloper

𝗣𝘆𝘁𝗵𝗼𝗻 𝗠𝗲𝘁𝗮𝗰𝗹𝗮𝘀𝘀𝗲𝘀 𝗘𝘅𝗽𝗹𝗮𝗶𝗻𝗲𝗱 Everything in Python is an object. Classes are objects too. They are instances of a metaclass. Type is the default metaclass. It builds your classes. Call type to create a class without the class keyword. Python follows four steps to build a class: - Find the metaclass. - Set up the namespace. - Run the class body. - Create the class object. Use the new method to change the class before it exists. Use the init method to record the class after it exists. Most developers do not need metaclasses. Use the init subclass method instead. It handles registration and interface checks. It is simpler to read. Avoid metaclasses in app code. They are hard to debug. Use them for frameworks. Otherwise, use decorators. The best metaclass is the one you do not write. Source: https://lnkd.in/gMfJU9Nx

I built my first real Python project today. 🐍 A fully functional Contact Book — runs in the terminal, no frameworks, no tutorials to copy from. What it does: → ➕ Add multiple contacts at once → 📋 View all saved contacts → ❌ Delete contacts by number → 🔁 Keeps running until you choose to exit What I used to build it: → Dictionary — to store name + phone pairs → While loop — to keep the app running → Functions — to avoid repeating code → Enumerate — to number contacts cleanly 3 weeks ago I didn't know what a dictionary was. Today I built an app with one. That's what consistent learning looks like. 💪 #Python #LearningInPublic #DataAnalytics #PythonProject #BBA #buildinpublic

Day 42 of #60DaysOfMiniProjects Today I built a Time Capsule Message App using Python Not just another project… This one lets you send a message to your future self Some thoughts aren’t meant for now… they’re meant for the version of you that’s still growing. What this system does: • Write a message to your future self • Set a time delay (in seconds) • Stores messages in a file • Reveals messages only when time is reached • Keeps messages “locked” until the right moment Why this project matters: • Encourages self-reflection • Helps track personal growth • Feels like a digital memory capsule • Shows how simple logic can create meaningful apps Concepts used: • Python basics • File Handling (Read/Write) • Date & Time module • Conditional logic • Simple CLI interaction From storing messages → revealing emotions at the right time. Next improvements: • Auto-delete after reading • Add password protection • GUI version (Tkinter) • Notification-based reveal • Store in database (SQLite) Building consistently. Learning daily. Improving step by step. 🚀 #Python #MiniProjects #BuildInPublic #CodingJourney #DeveloperLife #LearningInPublic #60DaysOfCode

Software news: teiphy v.0.1.24 is now available at https://lnkd.in/gjXnatFh! I've made some Dependabot-informed dependency updates (which unfortunately required me to drop Python 3.9 support); conversion methods now include a progress bar; and BEAST 2.7 XML outputs are more streamlined to reduce unnecessary computation. As always, you can check out the source code directly on GitHub, or you can install the latest version easily with pip via pip install teiphy