Visual Studio Python Mac

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  1. Visual Studio for Mac. Both the point releases and the major updates are guided by user feedback, with, for example, the new Python and Live Share features coming in direct response to user.
  2. Installing and Configuring Visual Studio Code for Python Development. Installing Visual Studio Code is very accessible on any platform. Full instructions for Windows, Mac, and Linux are available, and the editor is updated monthly with new features and bug fixes. You can find everything at the Visual Studio Code website. In case you were wondering, Visual Studio Code (or VS Code for short.
  1. Visual Studio Python Machine Learning
  2. Visual Studio For Mac Tutorial
  3. Visual Studio Mac Python Support

Python support is not presently available in Visual Studio for Mac, but is available on Mac and Linux through Visual Studio Code. See questions and answers. Visual Studio 2019 and Visual Studio 2017 Download and run the latest Visual Studio installer.

In this tutorial, you use Python 3 to create the simplest Python 'Hello World' application in Visual Studio Code. By using the Python extension, you make VS Code into a great lightweight Python IDE (which you may find a productive alternative to PyCharm).

This tutorial introduces you to VS Code as a Python environment, primarily how to edit, run, and debug code through the following tasks:

  • Write, run, and debug a Python 'Hello World' Application
  • Learn how to install packages by creating Python virtual environments
  • Write a simple Python script to plot figures within VS Code

Visual Studio Python Machine Learning

This tutorial is not intended to teach you Python itself. Once you are familiar with the basics of VS Code, you can then follow any of the programming tutorials on python.org within the context of VS Code for an introduction to the language.

If you have any problems, feel free to file an issue for this tutorial in the VS Code documentation repository.

Prerequisites

To successfully complete this tutorial, you need to first setup your Python development environment. Specifically, this tutorial requires:

  • VS Code
  • VS Code Python extension
  • Python 3

Install Visual Studio Code and the Python Extension

  1. If you have not already done so, install VS Code.

  2. Next, install the Python extension for VS Code from the Visual Studio Marketplace. For additional details on installing extensions, see Extension Marketplace. The Python extension is named Python and it's published by Microsoft.

Install a Python interpreter

Along with the Python extension, you need to install a Python interpreter. Which interpreter you use is dependent on your specific needs, but some guidance is provided below.

Windows

Install Python from python.org. You can typically use the Download Python button that appears first on the page to download the latest version.

Note: If you don't have admin access, an additional option for installing Python on Windows is to use the Microsoft Store. The Microsoft Store provides installs of Python 3.7, Python 3.8, and Python 3.9. Be aware that you might have compatibility issues with some packages using this method.

For additional information about using Python on Windows, see Using Python on Windows at Python.org

macOS

The system install of Python on macOS is not supported. Instead, an installation through Homebrew is recommended. To install Python using Homebrew on macOS use brew install python3 at the Terminal prompt.

Note On macOS, make sure the location of your VS Code installation is included in your PATH environment variable. See these setup instructions for more information.

Linux

The built-in Python 3 installation on Linux works well, but to install other Python packages you must install pip with get-pip.py.

Other options

  • Data Science: If your primary purpose for using Python is Data Science, then you might consider a download from Anaconda. Anaconda provides not just a Python interpreter, but many useful libraries and tools for data science.

  • Windows Subsystem for Linux: If you are working on Windows and want a Linux environment for working with Python, the Windows Subsystem for Linux (WSL) is an option for you. If you choose this option, you'll also want to install the Remote - WSL extension. For more information about using WSL with VS Code, see VS Code Remote Development or try the Working in WSL tutorial, which will walk you through setting up WSL, installing Python, and creating a Hello World application running in WSL.

Verify the Python installation

To verify that you've installed Python successfully on your machine, run one of the following commands (depending on your operating system):

  • Linux/macOS: open a Terminal Window and type the following command:

  • Windows: open a command prompt and run the following command:

Python

If the installation was successful, the output window should show the version of Python that you installed.

Note You can use the py -0 command in the VS Code integrated terminal to view the versions of python installed on your machine. The default interpreter is identified by an asterisk (*).

Start VS Code in a project (workspace) folder

Using a command prompt or terminal, create an empty folder called 'hello', navigate into it, and open VS Code (code) in that folder (.) by entering the following commands:

Note: If you're using an Anaconda distribution, be sure to use an Anaconda command prompt.

By starting VS Code in a folder, that folder becomes your 'workspace'. VS Code stores settings that are specific to that workspace in .vscode/settings.json, which are separate from user settings that are stored globally.

Alternately, you can run VS Code through the operating system UI, then use File > Open Folder to open the project folder.

Select a Python interpreter

Python is an interpreted language, and in order to run Python code and get Python IntelliSense, you must tell VS Code which interpreter to use.

From within VS Code, select a Python 3 interpreter by opening the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), start typing the Python: Select Interpreter command to search, then select the command. You can also use the Select Python Environment option on the Status Bar if available (it may already show a selected interpreter, too):

The command presents a list of available interpreters that VS Code can find automatically, including virtual environments. If you don't see the desired interpreter, see Configuring Python environments.

Note: When using an Anaconda distribution, the correct interpreter should have the suffix ('base':conda), for example Python 3.7.3 64-bit ('base':conda).

Selecting an interpreter sets the python.pythonPath value in your workspace settings to the path of the interpreter. To see the setting, select File > Preferences > Settings (Code > Preferences > Settings on macOS), then select the Workspace Settings tab.

Note: If you select an interpreter without a workspace folder open, VS Code sets python.pythonPath in your user settings instead, which sets the default interpreter for VS Code in general. The user setting makes sure you always have a default interpreter for Python projects. The workspace settings lets you override the user setting.

Create a Python Hello World source code file

From the File Explorer toolbar, select the New File button on the hello folder:

Name the file hello.py, and it automatically opens in the editor:

By using the .py file extension, you tell VS Code to interpret this file as a Python program, so that it evaluates the contents with the Python extension and the selected interpreter.

Note: The File Explorer toolbar also allows you to create folders within your workspace to better organize your code. You can use the New folder button to quickly create a folder.

Now that you have a code file in your Workspace, enter the following source code in hello.py:

When you start typing print, notice how IntelliSense presents auto-completion options.

IntelliSense and auto-completions work for standard Python modules as well as other packages you've installed into the environment of the selected Python interpreter. It also provides completions for methods available on object types. For example, because the msg variable contains a string, IntelliSense provides string methods when you type msg.:

Feel free to experiment with IntelliSense some more, but then revert your changes so you have only the msg variable and the print call, and save the file (⌘S (Windows, Linux Ctrl+S)).

For full details on editing, formatting, and refactoring, see Editing code. The Python extension also has full support for Linting.

Run Hello World

It's simple to run hello.py with Python. Just click the Run Python File in Terminal play button in the top-right side of the editor.

The button opens a terminal panel in which your Python interpreter is automatically activated, then runs python3 hello.py (macOS/Linux) or python hello.py (Windows):

There are three other ways you can run Python code within VS Code:

  • Right-click anywhere in the editor window and select Run Python File in Terminal (which saves the file automatically):

  • Select one or more lines, then press Shift+Enter or right-click and select Run Selection/Line in Python Terminal. This command is convenient for testing just a part of a file.

  • From the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), select the Python: Start REPL command to open a REPL terminal for the currently selected Python interpreter. In the REPL, you can then enter and run lines of code one at a time.

Configure and run the debugger

Let's now try debugging our simple Hello World program.

First, set a breakpoint on line 2 of hello.py by placing the cursor on the print call and pressing F9. Alternately, just click in the editor's left gutter, next to the line numbers. When you set a breakpoint, a red circle appears in the gutter.

Next, to initialize the debugger, press F5. Since this is your first time debugging this file, a configuration menu will open from the Command Palette allowing you to select the type of debug configuration you would like for the opened file.

Note: VS Code uses JSON files for all of its various configurations; launch.json is the standard name for a file containing debugging configurations.

These different configurations are fully explained in Debugging configurations; for now, just select Python File, which is the configuration that runs the current file shown in the editor using the currently selected Python interpreter.

The debugger will stop at the first line of the file breakpoint. The current line is indicated with a yellow arrow in the left margin. If you examine the Local variables window at this point, you will see now defined msg variable appears in the Local pane.

A debug toolbar appears along the top with the following commands from left to right: continue (F5), step over (F10), step into (F11), step out (⇧F11 (Windows, Linux Shift+F11)), restart (⇧⌘F5 (Windows, Linux Ctrl+Shift+F5)), and stop (⇧F5 (Windows, Linux Shift+F5)).

The Status Bar also changes color (orange in many themes) to indicate that you're in debug mode. The Python Debug Console also appears automatically in the lower right panel to show the commands being run, along with the program output.

To continue running the program, select the continue command on the debug toolbar (F5). The debugger runs the program to the end.

Tip Debugging information can also be seen by hovering over code, such as variables. In the case of msg, hovering over the variable will display the string Hello world in a box above the variable.

You can also work with variables in the Debug Console (If you don't see it, select Debug Console in the lower right area of VS Code, or select it from the .. menu.) Then try entering the following lines, one by one, at the > prompt at the bottom of the console:

Select the blue Continue button on the toolbar again (or press F5) to run the program to completion. 'Hello World' appears in the Python Debug Console if you switch back to it, and VS Code exits debugging mode once the program is complete.

If you restart the debugger, the debugger again stops on the first breakpoint.

To stop running a program before it's complete, use the red square stop button on the debug toolbar (⇧F5 (Windows, Linux Shift+F5)), or use the Run > Stop debugging menu command.

For full details, see Debugging configurations, which includes notes on how to use a specific Python interpreter for debugging.

Tip: Use Logpoints instead of print statements: Developers often litter source code with print statements to quickly inspect variables without necessarily stepping through each line of code in a debugger. In VS Code, you can instead use Logpoints. A Logpoint is like a breakpoint except that it logs a message to the console and doesn't stop the program. For more information, see Logpoints in the main VS Code debugging article.

Install and use packages

Let's now run an example that's a little more interesting. In Python, packages are how you obtain any number of useful code libraries, typically from PyPI. For this example, you use the matplotlib and numpy packages to create a graphical plot as is commonly done with data science. (Note that matplotlib cannot show graphs when running in the Windows Subsystem for Linux as it lacks the necessary UI support.)

Return to the Explorer view (the top-most icon on the left side, which shows files), create a new file called standardplot.py, and paste in the following source code:

Tip: If you enter the above code by hand, you may find that auto-completions change the names after the as keywords when you press Enter at the end of a line. To avoid this, type a space, then Enter.

Next, try running the file in the debugger using the 'Python: Current file' configuration as described in the last section.

Unless you're using an Anaconda distribution or have previously installed the matplotlib package, you should see the message, 'ModuleNotFoundError: No module named 'matplotlib'. Such a message indicates that the required package isn't available in your system.

To install the matplotlib package (which also installs numpy as a dependency), stop the debugger and use the Command Palette to run Terminal: Create New Integrated Terminal (⌃⇧` (Windows, Linux Ctrl+Shift+`)). This command opens a command prompt for your selected interpreter.

A best practice among Python developers is to avoid installing packages into a global interpreter environment. You instead use a project-specific virtual environment that contains a copy of a global interpreter. Once you activate that environment, any packages you then install are isolated from other environments. Such isolation reduces many complications that can arise from conflicting package versions. To create a virtual environment and install the required packages, enter the following commands as appropriate for your operating system:

Note: For additional information about virtual environments, see Environments.

  1. Create and activate the virtual environment

    Note: When you create a new virtual environment, you should be prompted by VS Code to set it as the default for your workspace folder. If selected, the environment will automatically be activated when you open a new terminal.

    For Windows

    If the activate command generates the message 'Activate.ps1 is not digitally signed. You cannot run this script on the current system.', then you need to temporarily change the PowerShell execution policy to allow scripts to run (see About Execution Policies in the PowerShell documentation):

    For macOS/Linux

  2. Select your new environment by using the Python: Select Interpreter command from the Command Palette.

  3. Install the packages

  4. Rerun the program now (with or without the debugger) and after a few moments a plot window appears with the output:

  5. Once you are finished, type deactivate in the terminal window to deactivate the virtual environment.

For additional examples of creating and activating a virtual environment and installing packages, see the Django tutorial and the Flask tutorial.

Next steps

You can configure VS Code to use any Python environment you have installed, including virtual and conda environments. You can also use a separate environment for debugging. For full details, see Environments.

To learn more about the Python language, follow any of the programming tutorials listed on python.org within the context of VS Code.

To learn to build web apps with the Django and Flask frameworks, see the following tutorials:

There is then much more to explore with Python in Visual Studio Code:

  • Editing code - Learn about autocomplete, IntelliSense, formatting, and refactoring for Python.
  • Linting - Enable, configure, and apply a variety of Python linters.
  • Debugging - Learn to debug Python both locally and remotely.
  • Testing - Configure test environments and discover, run, and debug tests.
  • Settings reference - Explore the full range of Python-related settings in VS Code.
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To install Python support for Visual Studio (also known as Python Tools for Visual Studio or PTVS), follow the instructions in the section that matches your version of Visual Studio:

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To quickly test Python support after following the installation steps, open the Python Interactive window by pressing Alt+I and entering 2+2. If you don't see the output of 4, recheck your steps.

Tip

The Python workload includes the helpful Cookiecutter extension that provides a graphical user interface to discover templates, input template options, and create projects and files. For details, see Use Cookiecutter.

Note

Python support is not presently available in Visual Studio for Mac, but is available on Mac and Linux through Visual Studio Code. See questions and answers.

Visual Studio 2019 and Visual Studio 2017

  1. Download and run the latest Visual Studio installer. If you have Visual Studio installed already, run the Visual Studio Installer, select the Modify option (see Modify Visual Studio) and go to step 2.

    Tip

    The Community edition is for individual developers, classroom learning, academic research, and open source development. For other uses, install Visual Studio 2019 Professional or Visual Studio 2019 Enterprise.

  2. The installer presents you with a list of workloads, which are groups of related options for specific development areas. For Python, select the Python development workload.

    Optional: if you're working with data science, also consider the Data science and analytical applications workload. This workload includes support for the Python, R, and F# languages. For more information, see Data science and analytical applications workload.

    Note

    The Python and Data Science workloads are available only with Visual Studio 2017 version 15.2 and later.

    Optional: if you're working with data science, also consider the Data science and analytical applications workload. This workload includes support for the Python and F# languages. For more information, see Data science and analytical applications workload.

  3. On the right side of the installer, chose additional options if desired. Skip this step to accept the default options.

    OptionDescription
    Python distributionsChoose any combination of the available options, such as 32-bit and 64-bit variants of the Python 2, Python 3, Miniconda, Anaconda2, and Anaconda3 distributions that you plan to work with. Each includes the distribution's interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of pre-installed packages. (You can return to the Visual Studio installer at any time to add or remove distributions.) Note: If you've installed a distribution outside of the Visual Studio installer, there's no need to check the equivalent option here. Visual Studio automatically detects existing Python installations. See The Python Environments window. Also, if a newer version of Python is available than what's shown in the installer, you can install that version separately and Visual Studio will detect it.
    Cookiecutter template supportInstalls the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. See Use the Cookiecutter extension.
    Python web supportInstalls tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. See Python web project templates.
    Python IoT supportSupports Windows IoT Core development using Python.
    Python native development toolsInstalls the C++ compiler and other necessary components to develop native extensions for Python. See Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.
    Azure Cloud Services core toolsProvides additional support for developer Azure Cloud Services in Python. See Azure cloud service projects.
    OptionDescription
    Python distributionsChoose any combination of the available options, such as 32-bit and 64-bit variants of the Python 2, Python 3, Miniconda, Anaconda2, and Anaconda3 distributions that you plan to work with. Each includes the distribution's interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of pre-installed packages. (You can return to the Visual Studio installer at any time to add or remove distributions.) Note: If you've installed a distribution outside of the Visual Studio installer, there's no need to check the equivalent option here. Visual Studio automatically detects existing Python installations. See The Python Environments window. Also, if a newer version of Python is available than what's shown in the installer, you can install that version separately and Visual Studio will detect it.
    Cookiecutter template supportInstalls the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. See Use the Cookiecutter extension.
    Python web supportInstalls tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. See Python web project templates.
    Python native development toolsInstalls the C++ compiler and other necessary components to develop native extensions for Python. See Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.
    Azure Cloud Services core toolsProvides additional support for developer Azure Cloud Services in Python. See Azure cloud service projects.

  4. After installation, the installer provides options to modify, launch, repair, or uninstall Visual Studio. The Modify button changes to Update when updates to Visual Studio are available for any installed components. (The Modify option is then available on the drop-down menu.) You can also launch Visual Studio and the installer from the Windows Start menu by searching on 'Visual Studio'.

Troubleshooting

If you encounter problems installing or running Python in Visual Studio, try the following:

  • Determine whether the same error occurs using the Python CLI, that is, running python.exe from a command prompt.
  • Use the Repair option in the Visual Studio installer.
  • Repair or reinstall Python through Settings > Apps & features in Windows.

Example error: Failed to start interactive process: System.ComponentModel.Win32Exception (0x80004005): Unknown error (0xc0000135) at Microsoft.PythonTools.Repl.PythonInteractiveEvaluator.d__43.MoveNext().

Visual Studio 2015

  1. Run the Visual Studio installer through Control Panel > Programs and Features, selecting Microsoft Visual Studio 2015 and then Change.

  2. In the installer, select Modify.

  3. Select Programming Languages > Python Tools for Visual Studio and then Next:

  4. Once Visual Studio setup is complete, install a Python interpreter of your choice. Visual Studio 2015 supports only Python 3.5 and earlier; later versions generate a message like Unsupported Python version 3.6). If you already have an interpreter installed and Visual Studio doesn't detect it automatically, see Manually identify an existing environment.

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Visual Studio 2013 and earlier

  1. Install the appropriate version of Python Tools for Visual Studio for your version of Visual Studio:

    • Visual Studio 2013: PTVS 2.2.2 for Visual Studio 2013. The File > New Project dialog in Visual Studio 2013 gives you a shortcut for this process.
    • Visual Studio 2010 and 2012: PTVS 2.1.1 for Visual Studio 2010 and 2012

  2. Install a Python interpreter of your choice. If you already have an interpreter installed and Visual Studio doesn't detect it automatically, see Manually identify an existing environment.

Install locations

By default, Python support is installed for all users on a computer.

For Visual Studio 2019 and Visual Studio 2017, the Python workload is installed in %ProgramFiles(x86)%Microsoft Visual Studio<VS_version><VS_edition>Common7IDEExtensionsMicrosoftPython where <VS_version> is 2019 or 2017 and <VS_edition> is Community, Professional, or Enterprise.

For Visual Studio 2015 and earlier, installation paths are as follows:

Visual Studio For Mac Tutorial

  • 32-bit:
    • Path: %Program Files(x86)%Microsoft Visual Studio <VS_ver>Common7IDEExtensionsMicrosoftPython Tools for Visual Studio<PTVS_ver>
    • Registry location of path: HKEY_LOCAL_MACHINESoftwareMicrosoftPythonTools<VS_ver>InstallDir
  • 64-bit:
    • Path: %Program Files%Microsoft Visual Studio <VS_ver>Common7IDEExtensionsMicrosoftPython Tools for Visual Studio<PTVS_ver>
    • Registry location of path: HKEY_LOCAL_MACHINESoftwareWow6432NodeMicrosoftPythonTools<VS_ver>InstallDir

where:

  • <VS_ver> is:
    • 14.0 for Visual Studio 2015
    • 12.0 for Visual Studio 2013
    • 11.0 for Visual Studio 2012
    • 10.0 for Visual Studio 2010
  • <PTVS_ver> is a version number, such as 2.2.2, 2.1.1, 2.0, 1.5, 1.1, or 1.0.

User-specific installations (1.5 and earlier)

Visual Studio Mac Python Support

Python Tools for Visual Studio 1.5 and earlier allowed installation for the current user only, in which case the installation path is %LocalAppData%MicrosoftVisualStudio<VS_ver>ExtensionsMicrosoftPython Tools for Visual Studio<PTVS_ver> where <VS_ver> and <PTVS_ver> are the same as described above.