When you search for Python IDE, you’ll get hundreds of options, and it will be confusing to pick the best one. To make it easier for you, I’ve listed the best IDE for Python so you can pick based on your experience level and requirements.
IDE = Integrated Development Environment
Best Python IDE for Windows and Mac
You can download the following Python IDE for Windows, Mac, and Linux computers. These are suitable for professional developers who code for a living.
IDE Name | Suitable for |
---|---|
PyCharm | Data Scientists, ML professionals |
Visual Studio Code | All Developers (Highly Customizable) |
Sublime Text | Intermediate and Experienced Programmers |
Jupyter Notebook | Data Analysts & ML Developers |
Spyder | Data Scientists & Data Analysts |
Thonny | Beginners & Students |
Replit | Startups and Beginner Coders |
Eric Python IDE | Intermediate and Experienced Programmers |
Eclipse + PyDev | Eclipse Users & Experienced Developers |
Komodo IDE | Experienced Developers & Full-Stack Developers |
AWS Cloud9 (cloud-based) | AWS Developers, Experienced |
Bluefish | Experienced Developers |
NetBeans (via nbPython plug-in) | Intermediate and Experienced Developers |
PyDev | Experienced Developers |
Anaconda | ML Developers & Data Scientists |
Rodeo | Data Analysts & Data Scientists |
Codeium | Experienced Developers |
KDevelop | Intermediate and Experienced Programmers |
Geany | Beginners and Intermediate Coders |
Wing | Professional Python Developers |
Best Online Python Compiler
You can use Python compilers within your favorite browsers like Chrome, Edge, or Firefox. These are good to practice, use one-time, during travel or teaching. They are all free to use.
Online Python Compiler | Suitable For |
---|---|
Google Colab | ML Developers, AI Researchers, and Data Scientists |
Domsignal | Beginners |
Ideone | Startups and Experienced Programmers |
Code with Mu | Beginners |
PythonAnywhere | Startups, and Experienced Programmers |
JDoodle | Beginners and Intermediate Coders |
Programiz Python Compiler | Students and Beginners |
Trinket | Educators, Students, and Beginners |
OneCompiler | Intermediate and Experienced Programmers |
Pynative Compiler | Beginners and Data Analysts |
OnlineGDB | Startups and Experienced Programmers |
SoloLearn | Beginners |
People Often Ask About Python IDE
Which Python IDEs are AI-powered?
Several Python IDEs incorporate AI-powered features to enhance coding efficiency and automation. Some popular AI-powered Python IDEs include:
- PyCharm – Offers AI-powered code completion, smart refactoring, and debugging assistance.
- Visual Studio Code – Equipped with AI-powered extensions like GitHub Copilot and IntelliCode for smarter code suggestions.
- Codeium – An AI-native coding assistant offering intelligent code & Intent-driven suggestions.
- Wing – Features AI-assisted code analysis and debugging tools.
- Anaconda – Offers AI capabilities like Anaconda Assistant and AI Navigator.
- AWS Cloud9 – Provides cloud-based AI-powered code completion and debugging.
Which Python IDE is best for Windows?
The best Python IDE for Windows depends on your project needs, and requirements. If you want a feature-rich environment, PyCharm offers smart code assistance, AI-powered debugging, and easy refactoring, making it ideal for large-scale projects. If you prefer a lightweight and highly customizable environment, Visual Studio Code is a great choice with 100+ powerful Python extensions to enhance your workflow.
Is Jupyter Notebook an IDE?
Jupyter Notebook is not a full-fledged IDE, but rather an interactive computing tool designed for exploratory coding, exploratory analysis, visualization, and documenting experiments. It allows users to write and execute code in a web-based notebook format.
Which online Python IDE is best?
Replit is a top choice for online Python IDE. It offers a beginner-friendly environment, a simple interface, and collaborative coding features, making it ideal for both learners and teams.
What is the best IDE for machine learning?
PyCharm is the best IDE for machine learning, offering AI Assistant for code and data fixes, built-in debugging, and efficient integration with machine learning libraries like TensorFlow, PyTorch, Hugging Face, NumPy, Pandas, PyTorch and Matplotlib. It offers Jupyter Notebook and Anaconda integration to streamline ML development.