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The Best Python IDE For Mac Users in 2023

Explaining each IDE in detail and also explain how you can use these IDEs in macOS.

Looking for the best Python IDE For Mac? Then here we have gathered the best & most preferable Python IDEs for macOS.

This will be a two-part series where we will explain each IDE in detail and also explain how you can use these IDEs in macOS.

Although, before we start the list, let’s learn a bit about Python & IDE first.

What Is Python & Why It is Popular?

Python is a high-level programming language known for its interpreted nature, object-oriented paradigm, and dynamic semantics. It offers a range of built-in data structures and supports dynamic typing and dynamic binding, making it highly appealing for Rapid Application Development.

Additionally, Python serves as an excellent scripting or glue language, facilitating the integration of existing components. Its syntax is designed for simplicity and readability, minimizing the cost of program maintenance.

Python promotes modularity and code reuse through support for modules and packages. The Python interpreter and extensive standard library are freely available in both source and binary forms, and compatible with major platforms.

Also, it is the top preferred language for data science and research. Since its syntax is easily understandable and adaptable, people with no development experience can easily learn Python and use it to manipulate data for research, reporting, predictable or regression analyses, and more


  • Easy to learn and use
  • Versatile and flexible
  • You can also use it for task automation
  • More productive
  • Large community and extensive libraries
  • Cross-platform compatibility
  • Scalability and integration
  • Strong community support
  • Widely adopted across industries

Python is ubiquitous, contributing to the development of numerous technologies, websites, and systems that people interact with regularly. It serves as the driving force behind a wide range of applications, from popular video streaming services to machine learning algorithms enabling cryptocurrency trading. As an expansive example, even NASA relies on Python to analyze data collected by its advanced James Webb Space Telescope, showcasing its remarkable reach beyond the confines of our planet. Python’s versatility truly makes it a programming language that transcends earthly boundaries. 🚀

Why Do You Need IDEs For Python?

Well, IDE in programming refers to the Integrated Development Environment (IDE). It is a software application that helps programmers write, debug, and run computer programs. IDEs typically provide features such as code editors, compilers, debuggers, and other tools that make it easier to develop software.

IDEs can be used for any programming language, but they are especially useful for languages such as Python which are known for their large standard libraries and complex syntax. IDEs can help programmers to:

  • Write code more quickly and easily by providing features such as code completion and syntax highlighting.
  • Debug code more easily by providing features such as breakpoints and step-by-step execution.
  • Manage projects more easily by providing features such as version control and project templates.

Benefits of Using IDE

Here are some of the benefits of using an IDE for Python:

  • Increased productivity: IDEs can help you to write code more quickly and easily by providing features such as code completion and syntax highlighting.
  • Improved debugging: IDEs can help you to debug code more easily by providing features such as breakpoints and step-by-step execution.
  • Easier project management: IDEs can help you manage projects more easily by providing features such as version control and project templates.

How to pick the best IDE?

The best IDE for you will depend on your individual needs and preferences. If you are a beginner, we recommend starting with a simple IDE such as IDLE. Once you have gained some experience, you can then explore more powerful IDEs such as PyCharm or Visual Studio Code.

Following are some of the parameters that you can consider while choosing one:

  • Ease of use: Look for an IDE that has a user-friendly interface and intuitive features for easy development and debugging.
  • Code editing capabilities: Ensure the IDE provides essential features like syntax highlighting, code completion, and intelligent code suggestions to enhance your coding experience.
  • Debugging support: The IDE should have robust debugging tools, such as breakpoints, step-through execution, and variable inspection, to help you identify and fix errors efficiently.
  • Integration with version control: If you work with version control systems like Git, choose an IDE that seamlessly integrates with them, allowing you to manage your code repositories directly from the IDE.
  • Package management: Consider IDEs that provide built-in support for package management systems like pip, allowing you to easily install, update, and manage Python libraries and dependencies.
  • Project management: Look for IDEs that offer project management features, enabling you to organize and navigate through your codebase efficiently, including support for virtual environments.
  • Plugin ecosystem: Check if the IDE has a vibrant plugin ecosystem, as it allows you to extend its functionality with additional features and integrations, customizing it to your needs.
  • Performance: Consider the IDE’s performance, particularly if you’re working on larger projects or resource-intensive tasks. A lightweight and responsive IDE can significantly improve your productivity.
  • Community support and documentation: Ensure the IDE has an active community and good documentation resources, including tutorials, forums, and online resources, which can be valuable for troubleshooting and learning.
  • Cross-platform compatibility: If you work across multiple operating systems, choose an IDE that offers cross-platform compatibility, allowing you to use the same development environment regardless of your workstation.
  • Cost and Licensing: Consider the pricing and licensing model of the IDE, especially if you’re looking for a commercial solution. Evaluate whether the features provided align with your budget and requirements.

Note: The choice of IDE ultimately depends on personal preference, workflow, and specific project needs, so it’s recommended to try out different IDEs and determine which one suits you best.

Now, let’s start the collection of the best Python IDEs for Mac users!

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The Best Python IDE For Mac:

There are many different IDEs available for Python, each with its own strengths and weaknesses. Some of the most popular IDEs for Python include VS Code, Pycharm, IDLE, Spyder, etc.

In this part, we will talk about the 1st five IDEs from this two-part series:

  1. VS Code
  2. PyCharm
  3. Jupyter
  4. Spyder
  5. IDLE

Let’s start with the VS Code.

VS Code

Virtual Studio Code (VS Code) is a perfect Integrated Development Environment for Python. It is simple and comes with built-in features that enhance the development experience.

VS Code Python extensions come with powerful features like syntax autocomplete, linting, debugging, unit testing, GitOps, virtual environments, notebooks, editing tools, and the ability to customize the editor.


  • Command Palette to access all commands by typing keywords.
  • Fully customizable keyboard shortcuts.
  • Jupyter extension for data science. Run Jupyter Notebook within the IDE.
  • Auto linting and formatting.
  • Debugging and Testing.
  • Git integration.
  • Custom code snippets.
  • Enhanced editing tools. Multi cursor selection, column selection, outline view, side-by-side preview, and search and modify.

Step-by-step guide on how to run Python IDE VS Code on macOS?


  1. Download Visual Studio Code for macOS.
  2. Double-click on the downloaded archive to expand the contents.
  3. Drag Visual Studio to the Applications folder, making it available in the Launchpad.


  1. Launch Visual Studio Code.
  2. Open the Command Palette (⇧⌘P) and type Install ‘code’ command in PATH command.
  3. Restart the terminal for the new $PATH value to take effect. You''ll be able to type ''code .'' in any folder to start editing files in that folder.

Using Python with VS Code:

  1. Simply download the latest version of Python from the official website
  2. Install the Python extension for VS Code. (Install the extension named Python which is maintained by Microsoft.)
  3. Choose the Python Interpreter
  • Open a folder for Python workspace by going to Files >> Open … >> Select or create a folder if the finder window opens it. This will be your Python workspace.
  • Now, open the Command Palette, by pressing Shift, Command, and P keys.
  • In the Command Palette, type in and select Python: Select Interpreter.
  • Select the appropriate Python 3.x interpreter from the list of interpreters. This action will create a folder .vscode inside your workspace. Inside this .vscode folder, you can find the settings.json file which stores the settings specific to the workspace. In our case, you can find the Python interpreter path.
  • At the bottom left corner of VS Code window, you can see the Python version as well.

Now Visual Studio Code is ready to interpret and run Python code.

Also, check this tutorial video.

Useful Keyboard Shortcuts:

  • Ctrl+⌥+N - To run Python code in VS Code
  • ⇧+⌘+P or F1 - Show Command Palette
  • ⌘+F To find & ⌥+⌘+F To replace
  • ⇧+⌘+V - To open the markdown preview
  • ⇧+⌘+D - Show Debug

For further macOS shortcodes check the official cheatsheet by VS Code.

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PyCharm is a full-featured IDE that offers many features, including code completion, code navigation, refactoring, and debugging. It is available in both a free and paid version. The free version is limited in features, but it is still a great option for beginners. The paid version offers additional features, such as a built-in debugger, a code inspection tool, and a code coverage tool.

It supports tools like IPython Notebook, Anaconda, NumPy, and Matplotlib and possesses an intuitive Python console. PyCharm is a cross-platform IDE and works on Windows, Linux, and Mac OS with one license key.


  • Python 2: Version 2.7
  • Python 3: Version 3.6 up to version 3.12
  • macOS 10.15 or later


  • It comes with an intelligent Python editor, smart code navigation, and fast and safe refactoring.
  • PyCharm is integrated with features like debugging, testing, profiling, deployments, remote development, and tools for the database.
  • With Python, PyCharm also provides support to Python web development frameworks, JavaScript, HTML, CSS, Angular JS, and Live edit features.
  • It has a powerful integration with IPython Notebook, python console, and scientific stack.
  • Automatic PEP Formatting
  • Graphical Installation of Python Modules

Here are some additional tips for using PyCharm:

  • You can use the PyCharm documentation to learn more about the features and functionality of the IDE
  • You can use the PyCharm community forum to get help from other PyCharm users.
  • You can use the PyCharm plugin repository to install plugins that add new features and functionality to the IDE.

Step-by-step guide on how to use PyCharm with MacOS?

To run PyCharm on macOS, you can follow these steps:

  1. Download the latest version of PyCharm from the JetBrains website.
  2. Once the download is complete, open the .dmg file and drag the icon to your Applications folder.
  3. Open PyCharm by double-clicking on the icon.
  4. When you first open PyCharm, you will be prompted to create a new project or open an existing project.
  5. If you are creating a new project, you will need to select a Python interpreter. You can select the default Python interpreter that is installed on your Mac, or you can select a different interpreter.
  6. Once you have created a new project, you can start writing code.
  7. To run your code, use the command: python

If you are running PyCharm for the first time then refer to the official documentation. You can also merge the existing project.

Also, check the tutorial video for the installation process.

Useful Keyboard Shortcuts:

  • Ctrl+⌥+R - To Run action
  • ^SPACE - Basic code completion
  • ⌘+⇧+ - To Complete the statement
  • ⌘+/ - To comment line
  • ^+J - For Quick documentation lookup
  • ⌘+⌥+L - To reformat the code

Check the further shortcodes on the official cheatsheet by PyCharm


Jupyter is an open-source web-based interactive computing environment that allows you to create and share documents called notebooks. These notebooks can contain live code, visualizations, explanatory text, equations, and rich media.

Jupyter Notebooks are based on the IPython kernel, which provides a powerful interactive computing environment. The IPython kernel can be used to run code in a variety of programming languages, including Python, Julia, R, and Scala.

Jupyter provides a flexible and interactive environment for data analysis, scientific computing, machine learning, and prototyping.


  • Interactive computing environment
  • Web-based interface accessible from any modern browser
  • Support for multiple programming languages through kernels
  • Organize code, text, equations, and visualizations in notebook format
  • Execute code in individual cells or collectively
  • Data visualization capabilities with the integration of popular libraries
  • Markdown support for documentation and explanations
  • Collaboration and sharing capabilities
  • Export notebooks to various formats like HTML, PDF, and Markdown
  • Extensible with a vast ecosystem of extensions and plugins
  • Suitable for data analysis, scientific computing, and prototyping
  • Enables reproducibility and sharing of computational workflows


  • The Python version required differs between Jupyter Notebook releases (e.g. Python 3.6+ for Notebook v6.3, and Python 3.7+ for Notebook v7

Step-by-step guide on how to use Jupyter with MacOS?

It is recommended to use the Anaconda distribution to install Python and Jupyter. Although, if you are already using Python then follow the steps below to use Jupyter Notebook on macOS:


  • Install Python from
  • Create a virtual environment with python3 -m venv .
  • Activate the virtual environment with source bin/activate (Mac/linux) or .\Scripts\activate (windows)
  • Install jupyter: Open the Terminal application on your macOS and run the pip install jupyter
  • Run jupyter: jupyter notebook - This command will start a Jupyter server and open a new tab in your default web browser with the Jupyter interface.
  • Create a new notebook: In the Jupyter interface, you can create a new notebook by clicking on the “New” button and selecting “Python 3” (or any other available kernel) under the “Notebooks” section. This will open a new notebook where you can write and execute Python code.

That’s it! You now have Jupyter running on your macOS. You can create new cells in the notebook to write and execute code, and you can also use Markdown cells for documentation and explanations. Remember to save your work regularly as Jupyter notebooks are autosaved but it’s always a good practice to save explicitly.

For further info refer to the official GitHub Repo.

You can check the tutorial video as well.

Note: It’s recommended to use a virtual environment or conda environment for your Jupyter projects to isolate the dependencies and avoid conflicts with your system-wide Python installation.

Useful Keyboard Shortcuts:

  • ⌘+F - to find items in your notebook
  • ⌘+Shift+ Right Arrow Key (or Left Key) - Highlight what you want to enclose with your punctuation
  • Shift+9 - To populate with opening and closing parenthesis
  • TAB Button - To Autofill Variables
  • Shift+Tab Key - To view documentation
  • ⌘+/ - To comment out a whole line

For more shortcuts in Jupyter Notebook, press the ESC key to highlight a cell blue. Then press the H key. A prompt should appear with more shortcuts for your needs or simply pull up the command palette by Cmd + Shift+P.

You can also check the official list of commands on the GitHub repo.


Spyder is a free and open-source scientific environment written in Python, for Python, and designed by and for scientists, engineers, and data analysts.

It features a unique combination of the advanced editing, analysis, debugging, and profiling functionality of a comprehensive development tool with the data exploration, interactive execution, deep inspection, and beautiful visualization capabilities of a scientific package. Besides, it is relatively easy to use with macOS.


  • Powerful code editor with syntax highlighting and code completion.
  • Interactive console for executing code snippets and exploring data.
  • Integrated IPython console with advanced features and capabilities.
  • Support for multiple programming languages, including Python, R, and Julia.
  • Project management tools for organizing and navigating code projects.
  • Extensibility through plugins and the ability to create custom plugins.
  • Integration with Jupyter Notebook for combining the benefits of both environments.
  • Cross-platform compatibility, supporting Windows, macOS, and Linux.
  • Active community and regular updates for bug fixes and feature enhancements.

Step-by-step guide on how to use SpyderIDE with MacOS?

To start with the Spyder on macOS, simply follow the steps below.


  1. Go to the installation page for Spyder.
  2. Under the heading for Standalone installers, click on the link for macOS Installer
  3. Launch the .dmg file
  4. Drag Spyder to your Applications folder.

It is strongly recommended that you use Python 3.6 on OSX to avoid any problems.

To Run The IDE follow the installation steps for Miniconda Python:

  1. Download the OSX miniconda installer. Click the link:, it will start downloading the latest package for macOS
  2. Open a Terminal window.
  3. Within the Terminal change directories into the folder where your downloaded file lives, i.e. cd ~/Downloads
  4. Now run the bash “shell” program to install Miniconda bash
  5. Close the Terminal program. Then, restart it. Within the Terminal type: conda install pillow
  • Enter y at the Proceed prompt.
  • When the installation completes, close the Terminal window

Install Spyder IDE and Connect It to Miniconda Python

The second half of the installation is the Spyder IDE development environment. This is the software that you use to write, edit and test your Python programs. Spyder IDE calls Python to actually run the program. Spyder is included by default in the Anaconda Python distribution, which comes with everything you need to get started in an all-in-one package.

  1. Go to the terminal window & type the command: $ conda install spyder
  2. Proceed ([y]/n)? prompt will appear, click ''y''
  3. Type the command: $ which spyder to know the location of spyder
  4. Go to the terminal window & type the command: $ spyder

Also, check the tutorial video:

Useful Keyboard Shortcuts:

  • Ctrl+Space - Code completion
  • ⌘+a - Start of line
  • ⌘+e - end of line
  • ⌘+p - Previous line
  • Ctrl+t - New Tab for iPython console
  • Ctrl+. - Restart kernel

To view the Editor’s primary keyboard shortcuts, consult its section under Help ‣ Shortcuts Summary. The full list can be browsed, searched, and customized (on double-click) in Preferences ‣ Keyboard shortcuts. Also, check the detailed list of Shortcut commands for Spyder IDE.


IDLE is Python’s Integrated Development and Learning Environment. It is the default IDE that comes bundled with Python. It can be a good choice for macOS users due to its simplicity and ease of use. With its clean interface and straightforward functionality, IDLE provides a beginner-friendly environment for Python development.

On macOS, there is one application menu. It dynamically changes according to the window currently selected. It has an IDLE menu, and some entries described below are moved around to conform to Apple guidelines. Under System Preferences: Dock, one can set “Prefer tabs when opening documents” to “Always”. This setting is not compatible with the tk/tkinter GUI framework used by IDLE, and it breaks a few IDLE features.

It offers basic features such as syntax highlighting, code completion, and an interactive Python shell, making it suitable for quick scripting tasks or introductory programming.


  • Coded in 100% pure Python, using the tkinter GUI toolkit
  • Cross-platform: works mostly the same on Windows, Unix, and macOS
  • Python shell window (interactive interpreter) with colorizing of code input, output, and error messages
  • Multi-window text editor with multiple undo, Python colorizing, smart indent, call tips, auto-completion, and other features
  • Search within any window, replace within editor windows, and search through multiple files (grep)
  • Debugger with persistent breakpoints, stepping, and viewing of global and local namespaces
  • Configuration, browsers, and other dialogs

Here’s a step-by-step guide on how to use IDLE in macOS:

  1. Launch the Terminal application on your macOS system. You can find it in the “Utilities” folder within the “Applications” directory, or you can use Spotlight to search for it.
  2. To launch IDLE type the idle3 command and press Enter to launch IDLE . It will launch IDLE for Python 3.x versions. If you are using Python 2.x, you can use the command idle instead.
  3. Once the IDLE opens, click on the “File” menu and select “New File” to create a new Python file.
  4. In the newly created file, write your Python code. For example, you can start with a simple “Hello, World!” program: print("Hello, World!")
  5. Click on the “File” menu and select “Save” to save your Python file. Choose a suitable file name and directory for saving the file.
  6. Run your code, by clicking on the “Run” menu and selecting “Run Module” or pressing the F5 key. The output of your program will be displayed in the IDLE shell.

That’s it! You can now use IDLE in macOS to write, execute, and test your Python code. Remember to save your files with the “.py” extension (e.g., “”) for Python scripts.

Why IDLE is not working on Mac? > It appears that if the Files & Folder security setting is set to disallow access to your Documents Folder, IDLE. app will fail on start-up but it will launch from the command line. Check the following in System Preferences. Apple Menu (upper left corner) -> System Preferences -> Security & Privacy

Useful Keyboard Shortcuts:

  • Fn+ F5 - To run the script
  • Ctrl+ P - To see the last run command
  • ⌘+a - beginning of line
  • ⌘+e - end of line
  • ⌘+k - kill line (but doesn''t put it in clipboard)
  • ⌘+l - centre window around the insertion point
  • ⌘+b - go backward one character without deleting (usually you can also use the cursor key for this)
  • ⌘+f - go forward one character without deleting (usually you can also use the cursor key for this)
  • ⌘+p - go up one line (usually you can also use the cursor key for this)
  • ⌘+d - delete next character



So, here we talked about the first five best Python IDEs for macOS users. Hope it will help you choose the best option. Thank you for reading!

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