Python

Clean code is code that other developers can read and understand quickly. It is not about cleverness. It is about clarity. The best code reads like a well-written paragraph. These 10 rules will make your code better immediately. Each rule includes bad and good examples in both Kotlin and Python. You can apply these today, no matter what language you use. Rule 1: Use Descriptive Names Names should tell you what a variable, function, or class does. If you need a comment to explain a name, the name is wrong. ...

Backend development is the engine behind every app and website. In 2026, the backend landscape is more exciting than ever. New frameworks, better tooling, and AI assistants make it faster to build production-ready APIs. This roadmap covers everything you need to become a backend developer. It includes language choices, databases, deployment, and a realistic timeline. Follow the stages in order for the best results. Why Backend Development in 2026? Every mobile app, website, and service needs a backend. The demand is constant and growing. Here is what makes 2026 special: ...

Python is one of the most popular languages in 2026. It dominates AI/ML, web development, data science, and automation. This guide covers the 30 most common Python interview questions. Answers are short and practical with code examples. Quick Reference — Python Key Features Feature Description Dynamically typed No need to declare types (but type hints are recommended) Interpreted Runs line by line, no compilation step GIL Global Interpreter Lock limits true multi-threading Indentation-based Uses whitespace instead of braces for blocks Duck typing “If it walks like a duck…” — type is determined by behavior Garbage collected Automatic memory management with reference counting Batteries included Large standard library for common tasks Package manager pip (or uv for faster installs) Beginner Questions (1-12) 1. What is Python? Python is a high-level, interpreted, dynamically-typed programming language. It was created by Guido van Rossum and released in 1991. Python emphasizes readability with its use of indentation. It is widely used for web development, AI/ML, automation, and data analysis. ...

Python and Rust could not be more different. Python is the world’s most popular language — easy, flexible, everywhere. Rust is the most loved language — fast, safe, precise. But here is the interesting part: in 2026, they are not competitors. They are partners. Many of the fastest Python tools are actually written in Rust underneath. This guide will help you understand when to use each language and when to use them together. ...

Last time we built a CLI todo app in 35 minutes. That was a local app. This time, we go bigger: a REST API that runs on the web. The goal: build a bookmark manager API with CRUD operations, pagination, search, rate limiting, tests, and a Docker setup. All with Claude Code prompts. Deploy it and get a live URL. Total time: 52 minutes from empty folder to deployed API. What We’re Building A bookmark manager REST API with these features: ...

Enough theory. Let us build something real. In this article, you will build a complete CLI tool using AI — from the initial description to a published package on PyPI. Every prompt, every AI response, and every manual fix is shown. You will see where AI excels, where it struggles, and how to handle both. The project: linkcheck — a markdown link checker that scans your documentation files and reports broken links. It is a small, useful tool with enough complexity to show real patterns. ...

Can you build a working CLI application in 30 minutes using only Claude Code? I tried it. Here is exactly what happened — every prompt, every mistake, and the final result. The goal was simple: start with an empty folder, talk to Claude Code in the terminal, and end up with a fully working todo app. No manual coding. Just prompts. Spoiler: it took 35 minutes, not 30. But the result was better than expected. ...

In the previous tutorial, we built a web scraper. Now let’s build an automation script — a file organizer that sorts files by type, processes CSV data, and logs everything properly. This is the final project in the Python Tutorial series. It ties together everything: file I/O, dataclasses, error handling, logging, testing, and packaging. By the end, you will have a practical tool you can use every day. What We Are Building A file organizer that: ...

In the previous tutorial, we built a REST API with FastAPI. Now let’s build a web scraper — a program that extracts data from web pages automatically. We will use httpx to fetch pages and BeautifulSoup to parse HTML. By the end, you will know how to extract data, save it to JSON and CSV, and scrape responsibly. When to Scrape (and When Not To) Web scraping is useful for: Collecting data that is not available via an API Monitoring prices, job listings, or news Research and data analysis But check these first: ...

In the previous tutorial, we built a CLI tool with Click and Rich. Now let’s build a REST API — a web API that any frontend, mobile app, or other service can call. We will use FastAPI, the fastest-growing Python web framework. It has automatic documentation, type checking, and built-in validation. By the end of this tutorial, you will have a working Bookmark Manager API. Why FastAPI? Automatic API docs — Swagger UI at /docs (free, no setup) Type-safe — uses Python type hints for validation Fast — built on Starlette and Pydantic (one of the fastest Python frameworks) Async support — native async/await (from Tutorial #18) Pydantic validation — automatic input validation (from Tutorial #10) Install the dependencies: ...