Programming Tutorials

Test your knowledge of the PATH variable and learn how to add Python on Windows, Linux, and macOS for easy terminal access.

Create a weekly Python study schedule you can stick to. Build a realistic 7-day plan, stay consistent, and turn learning Python into a sustainable hab

Test your understanding of Python data types and built-in functions to write clearer, more reliable code.

Learn to download files from URLs with Python using urllib and requests, including data streaming for large files.

Learn Python linked lists, deques, and circular & doubly linked structures with practical examples and efficient operations.

Learn how to use the Spyder IDE, a Python code editor built for scientists, engineers, and data analysts working with data-heavy workflows.

Test your Python concurrency knowledge: CPU vs I/O-bound tasks, GIL, asyncio, race conditions, and multiprocessing.

Brush up on splitting, concatenating, and joining strings in Python. Test your understanding of methods, immutability, and common pitfalls.

Test your knowledge of setting up a Python dev environment on Windows, from updates and terminals to paths, tools, and WSL.

What goes into creating the tutorials you read at Real Python? What are the steps in the editorial process, and who are the people behind the scenes?

Learn how to use Pydantic AI to build type-safe LLM agents in Python with structured outputs, function calling, and dependency injection patterns.

Learn how to consume REST APIs with Python using the requests library, including authentication, query parameters, and handling responses.

Catch up on the latest Python news: frozendict joins the built-ins, Django patches SQL injections, and AI SDKs race to add WebSocket transport.

Access models from popular AI providers in Python through OpenRouter's unified API with smart routing, fallbacks, and cost controls.

Learn how Python's __init__.py declares packages, initializes variables, simplifies imports, and controls what gets exported.

Automate exploratory data analysis by transforming DataFrames into interactive reports with one command from YData Profiling.

Do you have complex logic and unpredictable dependencies that make it hard to write reliable tests? How can you use Python's mock object library to im