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  1. Download Python | Python.org

    Python was created in the early 1990s by Guido van Rossum at Stichting Mathematisch Centrum in the Netherlands as a successor of a language called ABC. Guido remains Python’s principal …

  2. Python Tutorial - W3Schools

    Learn Python Python is a popular programming language. Python can be used on a server to create web applications. Start learning Python now » 🏁

  3. How to Use Python: Your First Steps – Real Python

    Oct 13, 2025 · If you’re starting fresh with programming and wondering how to use Python, this tutorial will give you the foundation you need to get started with Python step by step. You’ll …

  4. Welcome to Python.org

    Experienced programmers in any other language can pick up Python very quickly, and beginners find the clean syntax and indentation structure easy to learn. Whet your appetite with our …

  5. History of Python - Wikipedia

    [8] Python 3.0, a major, backwards-incompatible release, was released on December 3, 2008 [9] after a long period of testing. Many of its major features were also backported to the …

  6. Python Basics

    This section helps you start programming from the scratch. After completing this section, you'll know how to write simple Python programs.

  7. Learn Python programming at Python Land

    Python is a powerful and versatile programming language widely used in various fields, including web development, data analysis, artificial intelligence, and scientific computing.

  8. Python For Beginners

    Before getting started, you may want to find out which IDEs and text editors are tailored to make Python editing easy, browse the list of introductory books, or look at code samples that you …

  9. Python Basics – Real Python

    Jul 4, 2025 · On this page you’ll find fundamental concepts for Python beginners that will help you get started on your journey to learn Python. These tutorials focus on the absolutely essential …

  10. 10 Smart Performance Hacks For Faster Python Code

    6 days ago · Learn practical optimization hacks, from data structures to built-in modules, that boost speed, reduce overhead, and keep your Python code clean.