FastAPI Calculator App with Python Backend Development

FastAPI feels like the default choice for new Python backend projects now. I’ve noticed more teams and tutorials standardising on it, and it’s easy to see why: the “pit of success” is real. You can go from a basic REST endpoint to something that’s structured and testable without a lot of boilerplate, and the performance story doesn’t require rewriting everything in a different language. For a junior developer, that simplicity matters: fewer moving parts means I can spend more time thinking about data models, validation, and API design instead of fighting the framework. What’s been your biggest reason for adopting (or avoiding) FastAPI? #Python #Backend

Code the Web. Power It with Python. HTML gives structure. CSS gives style. JavaScript gives interaction. But Python? Python gives logic, automation, data, and intelligence. This is where the web stops being static and starts becoming smart: • APIs that actually scale • AI features that solve real problems • Backends that connect everything together I stopped asking “Which language should I learn next?” and started asking “What can I build with what I know?” That shift changed everything. If you’re learning web development: 👉 Don’t chase tools 👉 Build projects 👉 Let Python power the web you create What’s one thing you’ve built (or want to build) with Python + Web? Drop it in the comments 👇

🧠 Hoisting - not a programming universal. Look at the following error of two different snippet in attached image👇 In JavaScript, behavior differs based on how variables are declared. Variables declared with var are hoisted and initialized with undefined, so accessing them before declaration does not throw an error. Variables declared with let and const are also hoisted but remain uninitialized in the Temporal Dead Zone, which is why accessing them before declaration throws a ReferenceError. In Python, variable declarations are not hoisted. The interpreter executes code line by line, from top to bottom. When print(message) runs, the variable message has not been created yet, so Python raises a NameError. Shortly: Python binds names only when their definition executes, while js hoists declarations and knows names before execution begin. 👉 Same intent, same flow, same mistake — different outcome due to different working behavior. #programming #Programming #JavaScript #javascript #Python #python #ProgrammingTips #learning #learn #tips

FastAPI is quickly becoming the default choice I see for new Python backend projects. What stands out to me is the combination of strong performance and a low barrier to entry. The framework’s async-first approach makes it easier to reason about concurrency early, and the built-in request validation encourages better API contracts from day one. For someone focused on backend development, that structure matters as much as speed. I also like that it nudges you toward clearer separation between routing, schemas, and database logic, which maps well to how real services are maintained. When you’re choosing a backend framework, do you optimise first for performance or for developer experience? #python #backend

Ever wondered how a Python app actually serves a web page? Think of a Python web server like a waiter in a restaurant, it takes requests from users, passes them to the kitchen (your app), and delivers the response back to the table. From simple websites to full-scale web applications, Python web servers quietly handle requests, routes, and data behind the scenes to keep everything running smoothly. Curious how it all works and which tools are involved? Full blog link is shared in the first comment. 👇 #Python #PythonWebServer #WebTech #ServerBasics

This weekend, I was exploring how to build a frontend using Python. While experimenting, I discovered Streamlit and ended up creating a simple CSV Data Explorer app. What the app does: - Upload and preview any CSV file - Show dataset summary (rows, columns, missing values) - Generate descriptive statistics for numeric data - Create interactive charts (Line, Bar, Scatter, Area, Histogram, Box Plot) - Customize chart size and color - Download charts as PNG This was a fun hands-on way to learn how quickly Python can be used to build useful frontends for data exploration. GitHub repository: https://lnkd.in/dFYfy6xq

A “simple Python script” rarely stays simple in production. 🧩😅 In our latest article, we show how to turn Kitsu pipeline scripts into a single command-line tool that runs anywhere! No Python installs, no dependency headaches, no environment setup. ⚙️🚀 By wrapping Gazu in a CLI and compiling it into a standalone binary, studios can deploy reliable tools across artist machines, render nodes, and CI servers with confidence. 💡🖥️ Read the full article here:

An animation pipeline can start with something very basic, but the whole concept of deployment is a showstopper for many small studios that don't have sufficient IT resources. There are solutions to make it simpler, and this one is Open Source. Check it out.

I recently completed a URL Shortener web application using Django, and this video shows the project in action 🎥 What this project does: Converts long URLs into short, unique links using Base62 encoding Allows short links to be opened directly from any browser Redirects users to the original website seamlessly Tracks how many times each short link is visited Includes user authentication so links are user-specific Deployed using Gunicorn and Whitenoise Live demo: https://lnkd.in/ggquvJ5r Repo: https://lnkd.in/g-7XwVyM 📌 Tech used: Python | Django | SQLite | Gunicorn | Whitenoise Feedback and suggestions are welcome — especially around scaling, security, or analytics improvements. #DjangoProject #PythonDeveloper #BackendDevelopment #WebApp #LearningByDoing #StudentDeveloper #BuildInPublic