Perfect Your Python Development Setup
Learning Path ⋅ Skills: VS Code, PyCharm, Virtual Environments, pyenv, Docker, Git, GitHub, IDEs, Code Editors, Claude Code, Cursor, Gemini CLI, GitHub Copilot
In this learning path, you’ll set up a productive Python development environment. You’ll start with environment setup and editor selection, then learn to use VS Code and PyCharm. From there, you’ll work with virtual environments, Git, and pyenv to manage Python versions, and explore Docker for running different Python releases. Finally, you’ll get started with AI-assisted coding tools like Claude Code, Cursor, and Gemini CLI.
Perfect Your Python Development Setup
Learning Path ⋅ 16 Resources
Setting Up Your Environment
Get started by setting up an effective Python coding environment. You’ll learn best practices for configuring your system and setting up your tools on any platform.
Tutorial
An Effective Python Environment: Making Yourself at Home
This guide will walk you through the decisions you need to make when customizing your development environment for working with Python.
Tutorial
Your Python Coding Environment on Windows: Setup Guide
With this opinionated guide to setting up a basic, fully featured and flexible setup for Python coding and open source contributing when working from Windows, you'll go from a fresh install to ready to contribute, and even check out a PowerShell script to automate much of the process.
Editors and IDEs
Choose the right editor for your workflow. You’ll explore popular options, then learn to use VS Code and PyCharm for Python development.
Course
Finding the Perfect Python Code Editor
Find your perfect Python development setup with this review of Python IDEs and code editors. Writing Python using IDLE or the Python REPL is great for simple things, but not ideal for larger programming projects. With this course you'll get an overview of the most common Python coding environments to help you make an informed decision.
Course
Python Development in Visual Studio Code (Setup Guide)
Learn how to set up Visual Studio Code for Python development. By following examples, you'll cover everything from installing and configuring VSCode, to running tests and debugging Python apps.
Tutorial
Advanced Visual Studio Code for Python Developers
Learn how you can configure, extend, and optimize Visual Studio Code for a more effective and productive Python development environment. By digging into this customizable code editor and IDE, you'll put yourself on track to be a VS Code power user.
Tutorial
PyCharm for Productive Python Development (Guide)
Learn how you can use PyCharm to be a more productive Python developer. PyCharm makes debugging and visualization easy so you can focus on business logic and just get the job done.
Virtual Environments and Version Management
Isolate your project dependencies and manage multiple Python installations. You’ll learn virtual environments, Git and GitHub basics, and how to use pyenv.
Course
Working With Python Virtual Environments
This course demonstrates how Python's virtual environments work as a "sandbox" and you get a quick walkthrough on how to set up a new environment (or virtualenv, as they're called for short) and how to install third-party packages into it using the pip command.
Interactive Quiz
Python Virtual Environments: A Primer
Course
Introduction to Git and GitHub for Python
What is Git, what is GitHub, and what's the difference? Learn the basics of Git and GitHub from the perspective of a Pythonista in this step-by-step video course.
Course
Start Managing Multiple Python Versions With pyenv
Learn how to install multiple Python versions and switch between them with ease, including project-specific virtual environments, with pyenv.
Interactive Quiz
Managing Multiple Python Versions With pyenv
Python Versions and Customization
Learn to run different Python versions using Docker, install pre-release builds, and choose the best coding font for your editor.
Tutorial
Run Python Versions in Docker: How to Try the Latest Python Release
Learn how to run different Python versions in Docker. By following the examples, you'll see how you can play with the latest development version of Python, and how to use Dockerfiles to set up Python environments and package your own scripts.
Tutorial
How Can You Install a Pre-Release Version of Python?
If you want to have a peek at what's coming in the next stable version of Python, then you can install a pre-release version. In this tutorial, you'll learn how to access the latest Python versions and help test them.
Tutorial
Choosing the Best Coding Font for Programming
The font that you use is an important piece in your tool kit as a programmer. After all, you look at your programming font the whole time when writing code. In this tutorial, you'll find your perfect font for coding.
Interactive Quiz
Choosing the Best Font for Programming
AI-Assisted Coding
AI-powered tools can help you write, review, and debug code faster. You’ll explore Claude Code, Cursor, Gemini CLI, and GitHub Copilot to see how they fit into your Python workflow.
Course
Getting Started With Claude Code
Learn to set up and use Claude Code for Python projects: install, run commands, and integrate with Git.
Course
Tips for Using the AI Coding Editor Cursor
Learn Cursor fast: Use AI-powered coding with agents, project-aware chat, and inline edits to supercharge your VS Code workflow.
Course
Getting Started With Google Gemini CLI
Learn how to use Gemini CLI to bring Google's AI-powered coding assistance into your terminal for faster code analysis, debugging, and fixes.
Tutorial
GitHub Copilot: Fly With Python at the Speed of Thought
In this tutorial, you'll get your hands dirty with GitHub Copilot, a virtual pair programmer powered by artificial intelligence trained on billions of lines of code. You'll explore several practical use cases in Python for this amazing productivity tool.
Congratulations on completing this learning path! You’ve set up a productive Python development environment with editors, virtual environments, version management, and Docker.
Continue your intermediate Python journey with the next learning path:
Learning Path
Modules and Packages
14 Resources ⋅ Skills: Packages, Modules, Import System, pip, PyPI, uv, __init__.py, Namespace Packages
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