Visual Studio 2019 Python | Installation Details Of Python

Prerequisites

• Visual Studio. To install the product, follow the steps in Install Visual Studio.

• You can only switch between existing environments. If you don’t have an environment other than the default global environment, see the following sections about working with virtual environments. For more information, see Create and manage Python environments in Visual Studio.

Configure and run the debugger

Let’s now try debugging our Python program. Debugging support is provided by the Python Debugger extension, which is automatically installed with the Python extension. To ensure it has been installed correctly, open the Extensions view (⇧⌘X (Windows, Linux Ctrl+Shift+X)) and search for

@installed python debugger

. You should see the Python Debugger extension listed in the results.

Next, set a breakpoint on line 2 of

hello.py

by placing the cursor on the

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.

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 start, and then 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 can see that the

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

Roll a dice!

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:


msg msg.capitalize() msg.split()


Select the blue Continue button on the toolbar again (or press F5) to run the program to completion. “Roll a dice!” 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

Rich editing, IntelliSense, and code comprehension

Visual Studio provides a first-class Python editor, including syntax coloring, autocomplete across all your code and libraries, code formatting, signature help, refactoring, linting, and type hints. Visual Studio also provides unique features like class view, Go to Definition, Find All References, and code snippets. Direct integration with the Interactive window helps you quickly develop existing Python code in a file.

For more information:

Install packages using the Python Environments window

1. From the Python Environments window, select the default environment for new Python projects and choose the Packages tab. You’ll then see a list of packages that are currently installed in the environment.

2. Install

   
matplotlib

   by entering its name into the search field and then selecting the Run command: pip install matplotlib option. Running the command will install
   
matplotlib

   , and any packages it depends on (in this case that includes
   
numpy

   ).

3. Choose the Packages tab.

4. Consent to elevation if prompted to do so.

5. After the package is installed, it appears in the Python Environments window. The X to the right of the package uninstalls it.

6. Consent to elevation if prompted to do so.

7. After the package installs, it appears in the Python Environments window. The X to the right of the package uninstalls it.

   Note

   A small progress bar might appear underneath the environment to indicate that Visual Studio is building its IntelliSense database for the newly-installed package. The IntelliSense tab also shows more detailed information. Be aware that until that database is complete, IntelliSense features like auto-completion and syntax checking won’t be active in the editor for that package.

   Visual Studio 2017 version 15.6 and later uses a different and faster method for working with IntelliSense, and displays a message to that effect on the IntelliSense tab.

View and manage installed packages

In Solution Explorer, you can view and manage the packages installed in an environment. These packages can be imported and used in your code when the environment is active.

• To quickly view the packages installed in an environment, expand the environment node under the Python Environments node for your project in Solution Explorer:

• To install new packages or manage existing packages, right-click the environment node and select Manage Python Packages. You can also use the package button on the Python toolbar:

  The Python Environments window opens and shows the installed packages for the selected environment on the Packages (PyPI) tab:

  In Visual Studio, packages and dependencies for most environments are downloaded from the Python Package Index (PyPI), where you can also search for available packages. Visual Studio’s status bar and output window show information about the install.

• To uninstall (remove) a package, locate the package in the list and select the x icon at the right.

• To look for updated versions of a package or other packages, enter a search term (usually a package name):

  Visual Studio displays matching packages. In this example, the search is for packages that match the term blinker.

  Visual Studio displays a list of matching results as active command links.

  • The first command refreshes the package to the most current version and current dependencies. The command is similar to

    
Run command: pip install

    . If you select Enter after your search term, Visual Studio automatically runs this first command.

  • The other links are for commands that install a specific package, version, or dependency, such as

    
Install blinker-async (0.0.3)

    . To run one of these commands, select the link.

Installation details of Python

We can see the installation details of the Python on the right-hand side in the installer after selecting the Python development. We can find how much MB of memory have been taken for installing Python.

Click the modify to enable Python in Visual Studio 2019. If you are installing new, we can find the installation button in the bottom instead of the Modify button. Once clicked, the Modify installation will be started.

Features in Visual Studio for Python

1. Editing is very easy and user-friendly. We can easily edit the Python code with the help of Tooltip, completion and code snippets.
2. We can install the libraries without trouble. Using search options, find the libraries and install whatever we need for our Python applications.
3. Debugging is very helpful to find the complex issues. Python in visual studio support debugging without project.
4. We can use effective source controller Git and TFS. We can use Git and TFS without a command line.
5. Unit testing is validating your changes in the editor. We can verify the code is working correctly without leaving the visual studio. We can view, edit, and debug the unit test from the test window.
6. Python tool for Visual Studio is a free extension, develop and support by Microsoft with contribution from the community.

View environments

1. Select the View > Other Windows > Python Environments menu command. The Python Environments window opens as a peer to Solution Explorer and shows the different environments available to you. The list shows both environments that you installed using the Visual Studio installer and environments you installed separately. That includes global, virtual, and conda environments. The environment in bold is the default environment that’s used for new projects. For more information about working with environments, see How to create and manage Python environments in Visual Studio environments.

   Note

   You can also use the Ctrl+K, Ctrl+` keyboard shortcut to open the Python Environments window from the Solution Explorer window. If the shortcut doesn’t work and you can’t find the Python Environments window in the menu, it’s possible that you haven’t installed the Python workload. See How to install Python support in Visual Studio on Windows for guidance about how to install Python.

   With a Python project open, you can open the Python Environments window from Solution Explorer. Right-click Python Environments and select View All Python Environments.

2. Now, create a new project with File > New > Project, selecting the Python Application template.

3. In the code file that appears, paste the following code, which creates a cosine wave like the previous tutorial steps, only this time plotted graphically. You can also use the project you previously created and replace the code.

   
from math import radians import numpy as np # installed with matplotlib import matplotlib.pyplot as plt def main(): x = np.arange(0, radians(1800), radians(12)) plt.plot(x, np.cos(x), 'b') plt.show() main()


4. In the editor window, hover over the

   
numpy

   and
   
matplotlib

   import statements. You’ll notice that they aren’t resolved. To resolve the import statements, install the packages to the default global environment.

5. When you look at the editor window, notice that when you hover over the

   
numpy

   and
   
matplotlib

   import statements that they aren’t resolved. The reason is the packages haven’t been installed to the default global environment.

   For example, select Open interactive window and an Interactive window for that specific environment appears in Visual Studio.

6. Use the drop-down list below the list of environments to switch to the Packages tab.The Packages tab lists all packages that are currently installed in the environment.

Full-featured debugging

One of Visual Studio’s strengths is its powerful debugger. For Python in particular, Visual Studio includes Python/C++ mixed-mode debugging, remote debugging on Linux, debugging within the Interactive window, and debugging Python unit tests.

In Visual Studio 2019 and later, you can run and debug code without having a Visual Studio project file. See Quickstart: Open and run Python code in a folder for an example.

For more information:

• Debug Python
• Python/C++ mixed-mode debugging
• Remote debugging on Linux
• Feature tour of the Visual Studio Debugger

Download and install the Python workload

Complete the following steps to download and install the Python workload.

1. Download and run the latest Visual Studio Installer for Windows. Python support is present in release 15.2 and later. If you have Visual Studio installed already, open Visual Studio and run the installer by selecting Tools > Get Tools and Features.

   Tip

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

2. The installer provides a list of workloads that are groups of related options for specific development areas. For Python, select the Python development workload and select Install:

   Python installation options Description Python distributions Choose any combination of Python distribution that you plan to work with. Common options include 32-bit and 64-bit variants of Python 2, Python 3, Miniconda, Anaconda 2, and Anaconda 3. Each option includes the distribution’s interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of preinstalled packages. Visual Studio automatically detects existing Python installations. For more information, see The Python Environments window. Also, if a newer version of Python is available than the version shown in the installer, you can install the new version separately and Visual Studio detects it. Cookiecutter template support Install the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. For more information, see Use the Cookiecutter extension. Python web support Install tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. For more information, see Python web project templates. Python native development tools Install the C++ compiler and other necessary components to develop native extensions for Python. For more information, see Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.

   By default, the Python workload installs for all users on a computer under:

   %ProgramFiles%\Microsoft Visual Studio\
   
   \
   
   Common7\IDE\Extensions\Microsoft\Python
   
   

   where
   
   is 2022 and
   
   is Community, Professional, or Enterprise.
   
   

   %ProgramFiles(x86)%\Microsoft Visual Studio\
   
   \
   
   Common7\IDE\Extensions\Microsoft\Python
   
   

   where
   
   is 2019 or 2017 and
   
   is Community, Professional, or Enterprise.
   
   

Install and use packages

Let’s build upon the previous example by using packages.

In Python, packages are how you obtain any number of useful code libraries, typically from PyPI, that provide additional functionality to your program. For this example, you use the

numpy

package to generate a random number.

Return to the Explorer view (the top-most icon on the left side, which shows files), open

hello.py

, and paste in the following source code:


import numpy as np msg = "Roll a dice" print(msg) print(np.random.randint(1,9))


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, run the file in the debugger using the “Python: Current file” configuration as described in the last section.

You should see the message, “ModuleNotFoundError: No module named ‘numpy'”. This message indicates that the required package isn’t available in your interpreter. If you’re using an Anaconda distribution or have previously installed the

numpy

package you may not see this message.

To install the

numpy

package, stop the debugger and use the Command Palette to run Terminal: Create New Terminal (⌃⇧` (Windows, Linux Ctrl+Shift+`)). This command opens a command prompt for your selected interpreter.

To install the required packages in your virtual environment, enter the following commands as appropriate for your operating system:

1. Install the packages

   
# Don't use with Anaconda distributions because they include matplotlib already. # macOS python3 -m pip install numpy # Windows (may require elevation) py -m pip install numpy # Linux (Debian) apt-get install python3-tk python3 -m pip install numpy


2. Now, rerun the program, with or without the debugger, to view the output!

Congrats on completing the Python tutorial! During the course of this tutorial, you learned how to create a Python project, create a virtual environment, run and debug your Python code, and install Python packages. Explore additional resources to learn how to get the most out of Python in Visual Studio Code!

Getting Started with Python in VS Code

In this tutorial, you will learn how to use Python 3 in Visual Studio Code to create, run, and debug a Python “Roll a dice” application, work with virtual environments, use packages, and more! By using the Python extension, you turn VS Code into a great, lightweight Python editor.

If you are new to programming, check out the Visual Studio Code for Education – Introduction to Python course. This course offers a comprehensive introduction to Python, featuring structured modules in a ready-to-code browser-based development environment.

To gain a deeper understanding of the Python language, you can explore any of the programming tutorials listed on python.org within the context of VS Code.

For a Data Science focused tutorial with Python, check out our Data Science section.

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Tutorial: Work with Python in Visual Studio

In this tutorial, you learn how to work with Python in Visual Studio. Python is a popular programming language that’s reliable, flexible, easy to learn, and free to use on all operating systems. Python is supported by a strong developer community and many free libraries. The language supports all kinds of development, including web applications, web services, desktop apps, scripting, and scientific computing. Many universities, scientists, casual developers, and professional developers use Python. Visual Studio provides first-class language support for Python.

This tutorial guides you through a six-step process:

• Step 1: Create a Python project (this article)
• Step 2: Write and run code to see Visual Studio IntelliSense at work
• Step 3: Create more code in the Interactive REPL window
• Step 4: Run the completed program in the Visual Studio debugger
• Step 5: Install packages and manage Python environments
• Step 6: Work with Git

This article covers the tasks in Step 1. You create a new project and review the UI elements visible in Solution Explorer.

Create a Python source code file

From the File Explorer toolbar, select the New File button on the

hello

folder:

Name the file

hello.py

, and VS Code will automatically open it 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

:


msg = "Roll a dice" print(msg)


When you start typing

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.

:

Finally, save the file (⌘S (Windows, Linux Ctrl+S)). At this point, you’re ready to run your first Python file in VS Code.

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

Test your install

Quickly check your installation of Python support:

1. Launch Visual Studio.

2. Select Alt + I to open the Python Interactive window.

3. In the window, enter the statement

   
2+2

   .

   The statement output

   displays in the window. If you don’t see the correct output, recheck your steps.

Version Control integration

Collaborate on code with Git

Use Git as the default source control experience in Visual Studio right out of the box. From the new Git menu, you can create or clone repositories from GitHub or Azure DevOps. Use the integrated Git tool windows to commit and push changes to your code, manage branches, sync with your remote repositories, and resolve merge conflicts.

Configure Python in Visual Studio 2019

We need to enable the Python while installing the Visual Studio 2019. If you already installed Visual Studio, then we can enable it using the Visual Studio installer. Steps are the same to enable Python for those who are installing new or updating the Visual Studio which we have installed already. Open the installer and select the “Python development” as shown below.

Remove a virtual environment

Follow these steps to remove an existing environment for a project:

1. In Solution Explorer, right-click the virtual environment and select Remove.

2. Visual Studio asks whether you want to remove or delete the virtual environment.

   • Select Remove to make the environment unavailable to the project but leave it on the file system.
   • Select Delete to both remove the environment from the project and delete it from the file system. The base interpreter is unaffected.

Step 1: Create a new Python project

A project is how Visual Studio manages all the files that come together to produce a single application. Application files include source code, resources, and configurations. A project formalizes and maintains the relationships among all the project’s files. The project also manages external resources that are shared between multiple projects. A project allows your application to effortlessly expand and grow. Using projects is easier than managing relationships by hand in unplanned folders, scripts, text files, and your memory.

This tutorial begins with a simple project containing a single, empty code file.

1. In Visual Studio, select File > New > Project to open the New Project dialog. You can also use the keyboard shortcut Ctrl+Shift+N. In the dialog, you can browse templates across different languages, select a template for your project, and specify where Visual Studio places files.

2. To view Python templates, select Installed > Python on the left menu, or search for “Python.” The search option is a great way to find a template when you can’t remember its location in the languages tree.

   Python support in Visual Studio includes several project templates, including web applications using the Bottle, Flask, and Django frameworks. For the purposes of this walkthrough, however, let’s start with an empty project.

3. Select the Python Application template, specify a name for the project, and select OK.

1. In Visual Studio, select File > New > Project or use the keyboard shortcut Ctrl+Shift+N. The Create a new project screen opens, where you can search and browse templates across different languages.

2. To view Python templates, search for python. Search is a great way to find a template when you can’t remember its location in the languages tree.

   Python web support in Visual Studio includes several project templates, such as web applications in the Bottle, Flask, and Django frameworks. When you install Python with the Visual Studio Installer, select Python Web Support under Optional to install these templates. For this tutorial, start with an empty project.

3. Select the Python Application template, and select Next.

4. On the Configure your new project screen, specify a name and file location for the project, and then select Create.

After a few moments, your new project opens in Visual Studio:

Here’s what you see:

• (1) The Visual Studio Solution Explorer window shows the project structure.
• (2) The default code file opens in the editor.
• (3) The Properties window shows more information for the item selected in Solution Explorer, including its exact location on disk.

Python Project Template

Open Visual Studio, click the new project and type the Python in the search bar in Visual Studio 2019. We can see all Python-related templates, as shown below.

We have more than five templates available. In the Python application; it is used to create the command line project. Python Web Project, it is used to creating a generic Python web project. Django Web Project, it is one of the frameworks. A project for creating an application using the Django web framework. We have Django, Flask, and Bottle web framework for Python. It features sample pages that use the Twitter Bootstrap framework for responsive web design.

Test your install

Quickly check your installation of Python support:

1. Launch Visual Studio.

2. Select Alt + I to open the Python Interactive window.

3. In the window, enter the statement

   
2+2

   .

   The statement output

   displays in the window. If you don’t see the correct output, recheck your steps.

Run Python code

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:

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

2. 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.

3. 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.

Congrats, you just ran your first Python code in Visual Studio Code!

Start VS Code in a workspace folder

By starting VS Code in a folder, that folder becomes your “workspace”.

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:


mkdir hello cd hello code .


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

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

Project system, and project and item templates

Visual Studio helps you manage the complexity of a project as it grows over time. A Visual Studio project is more than a folder structure. A project aids in the understanding of how different files are used and how they relate to each other. Visual Studio helps you distinguish app code, test code, web pages, JavaScript, build scripts, and so on, which then enable file-appropriate features. A Visual Studio solution helps you manage multiple related projects, such as a Python project and a C++ extension project.

Note

In Visual Studio 2019 and later, you can open a folder containing Python code and run that code without creating a Visual Studio project or solution file. For more information, see Quickstart: Open and run Python code in a folder. Keep in mind that there are benefits to using a project file, as explained in this section.

The following image shows an example of a Visual Studio solution containing both Python and Flask projects in Solution Explorer.

Project and item templates automate the process of setting up different types of projects and files. The templates save you valuable time and relieve you from managing intricate and error-prone details. Visual Studio provides templates for web, Azure, data science, console, and other types of projects. You can find templates for files like Python classes, unit tests, Azure web configuration, HTML, and even Django apps.

For more information:

• Manage Python projects
• Item templates reference
• Python project templates
• Work with C++ and Python
• Create project and item templates
• Solutions and projects in Visual Studio

Next steps

To learn how to build web apps with popular Python web frameworks, see the following tutorials:

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

• Python profile template – Create a new profile with a curated set of extensions, settings, and snippets
• 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.
• Deploy Python to Azure App Service
• Deploy Python to Container Apps

Install Python support in Visual Studio

Python support is available only on Visual Studio for Windows. On Mac and Linux, Python support is available through Visual Studio Code.

Creating a Python Project

We can develop web applications using Python with above one of the frameworks. Open Visual Studio 2019 and select “Create new project”.

Select the language dropdown as “Python”. We can see all the project templates of the project for Python.

We can see the template with a different framework. We can choose and develop any one of the templates a can develop the application based on our requirement.

Create a virtual environment

You can create a new virtual environment directly in Visual Studio as follows:

1. Start the Add Environment process:

   • In Solution Explorer, right-click the Python Environments node for your project and select Add Environment.
   • Or, on the Python toolbar, select Add Environment from the Environment dropdown menu.

2. In the Add Environment dialog, select the Virtual environment tab:

3. Configure the required fields:

   Required field Description Project Identify the project in which to create the environment. Name Provide the name for the new virtual environment. Base interpreter Specify the base language interpreter for the virtual environment. Location The system assigns the default location for the virtual environment. To change the location, select the Change virtual environment location link, browse to the location and choose Select folder.

4. Configure any desired optional fields:

   Optional field Description Install packages from file Specify the path to a requirements.txt file to add packages to the virtual environment. Enter the location and name of the file or browse (…) to the location and select the file. Set as current environment Activate the new environment in the selected project after the environment is created. Set as default environment for new projects Automatically set and activate the environment in any new projects created in Visual Studio. This setting is also available via the Make this the default environment for new projects option in the Python Environments window. When you use this option, place the virtual environment in a location outside of a specific project. View in Python Environments window Specify whether to show the Python Environments window after you create the new environment. Make this environment available globally Specify whether the virtual environment should also act as a global environment. When you use this option, place the virtual environment in a location outside of a specific project.

5. Select Create to finalize the virtual environment.

Visual Studio displays a progress bar while it configures the environment and downloads any necessary packages.

After the process completes, Visual Studio activates the new virtual environment and adds it to the Python Environments node in Solution Explorer. The environment is also available in the Python Environments window for the containing project.

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. 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 supported Python versions.

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, a package management system like 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 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.

Note: 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:


python3 --version


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


py -3 --version


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

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Tutorial: Work with Python in Visual Studio

In this tutorial, you learn how to work with Python in Visual Studio. Python is a popular programming language that’s reliable, flexible, easy to learn, and free to use on all operating systems. Python is supported by a strong developer community and many free libraries. The language supports all kinds of development, including web applications, web services, desktop apps, scripting, and scientific computing. Many universities, scientists, casual developers, and professional developers use Python. Visual Studio provides first-class language support for Python.

This tutorial guides you through a six-step process:

• Step 1: Create a Python project (this article)
• Step 2: Write and run code to see Visual Studio IntelliSense at work
• Step 3: Create more code in the Interactive REPL window
• Step 4: Run the completed program in the Visual Studio debugger
• Step 5: Install packages and manage Python environments
• Step 6: Work with Git

This article covers the tasks in Step 1. You create a new project and review the UI elements visible in Solution Explorer.

Download and install the Python workload

Complete the following steps to download and install the Python workload.

1. Download and run the latest Visual Studio Installer for Windows. Python support is present in release 15.2 and later. If you have Visual Studio installed already, open Visual Studio and run the installer by selecting Tools > Get Tools and Features.

   Tip

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

2. The installer provides a list of workloads that are groups of related options for specific development areas. For Python, select the Python development workload and select Install:

   Python installation options Description Python distributions Choose any combination of Python distribution that you plan to work with. Common options include 32-bit and 64-bit variants of Python 2, Python 3, Miniconda, Anaconda 2, and Anaconda 3. Each option includes the distribution’s interpreter, runtime, and libraries. Anaconda, specifically, is an open data science platform that includes a wide range of preinstalled packages. Visual Studio automatically detects existing Python installations. For more information, see The Python Environments window. Also, if a newer version of Python is available than the version shown in the installer, you can install the new version separately and Visual Studio detects it. Cookiecutter template support Install the Cookiecutter graphical UI to discover templates, input template options, and create projects and files. For more information, see Use the Cookiecutter extension. Python web support Install tools for web development including HTML, CSS, and JavaScript editing support, along with templates for projects using the Bottle, Flask, and Django frameworks. For more information, see Python web project templates. Python native development tools Install the C++ compiler and other necessary components to develop native extensions for Python. For more information, see Create a C++ extension for Python. Also install the Desktop development with C++ workload for full C++ support.

   By default, the Python workload installs for all users on a computer under:

   %ProgramFiles%\Microsoft Visual Studio\
   
   \
   
   Common7\IDE\Extensions\Microsoft\Python
   
   

   where
   
   is 2022 and
   
   is Community, Professional, or Enterprise.
   
   

   %ProgramFiles(x86)%\Microsoft Visual Studio\
   
   \
   
   Common7\IDE\Extensions\Microsoft\Python
   
   

   where
   
   is 2019 or 2017 and
   
   is Community, Professional, or Enterprise.
   
   

Review elements in Solution Explorer

Take some time to familiarize yourself with Solution Explorer, where you can browse files and folders in your project.

• (1) At the top level is the solution, which by default has the same name as your project. A solution, which is shown as an .sln file on disk, is a container for one or more related projects. For example, if you write a C++ extension for your Python application, that C++ project can be in the same solution. The solution might also contain a project for a web service, and projects for dedicated test programs.

• (2) Your project is highlighted in bold and uses the name you entered in the Create a new project dialog. On disk, this project is represented by a .pyproj file in your project folder.

• (3) Under your project you see source files. In this example, you have only a single .py file. Selecting a file displays its properties in the Properties window. If you don’t see the Properties window, select the wrench icon in the Solution Explorer banner. Double-clicking a file opens it in whatever way is appropriate for that file.

• (4) Also under the project is the Python Environments node. Expand the node to show the available Python interpreters.

• (5) Expand an interpreter node to see the libraries installed in that environment.

Right-click any node or item in Solution Explorer to show a context menu of applicable commands. For example, Rename lets you change the name of a node or item, including the project and the solution.

Interactive window

For every Python environment known to Visual Studio, you can easily open the same interactive (REPL) environment for a Python interpreter directly within Visual Studio, rather than using a separate command prompt. You can easily switch between environments as well. To open a separate command prompt, select your desired environment in the Python Environments window, then select the Open in PowerShell command as explained earlier in the Support for multiple interpreters section.

Visual Studio also provides tight integration between the Python code editor and the Interactive window. The Ctrl+Enter keyboard shortcut conveniently sends the current line of code (or code block) in the editor to the Interactive window, then moves to the next line (or block). Ctrl+Enter lets you easily step through code without having to run the debugger. You can also send selected code to the Interactive window with the same keystroke, and easily paste code from the Interactive window into the editor. Together, these capabilities allow you to work out details for a segment of code in the Interactive window and easily save the results in a file in the editor.

Visual Studio also supports IPython/Jupyter in the REPL, including inline plots, .NET, and Windows Presentation Foundation (WPF).

For more information:

Considerations about package installation

When you work with packages in Visual Studio, keep in mind the following considerations:

• Keep in mind that the displayed entries for packages might not be accurate in terms of the most current version or availability. The installation and uninstallation information shown for a package might not be reliable or available.

• Visual Studio uses the pip package manager if available, and downloads and installs it when required. Visual Studio can also use the easy_install package manager. Packages installed by using the

  
pip

  or
  
easy_install

  commands from the command line are also displayed.

• A common situation where pip fails to install a package is when the package includes source code for native components in *.pyd files. Without the required version of Visual Studio installed, pip can’t compile these components. The error message displayed in this situation is error: Unable to find vcvarsall.bat. The

  
easy_install

  command is often able to download precompiled binaries, and you can download a suitable compiler for older versions of Python from https://python.en.uptodown.com/windows/versions. For more information, see How to deal with the pain of “unable to find vcvarsallbat” on the Python tools team blog.

• The conda package manager generally uses

  
https://repo.continuum.io/pkgs/

  as the default channel, but other channels are available. For more information, see Manage Channels (docs.conda.io).

• Visual Studio doesn’t currently support using the

  
conda

  command to install packages into a conda environment. Use the
  
conda

  command from the command line instead.

Questions and answers

Q. Is Python support available with Visual Studio for Mac?

A. Visual Studio for Mac isn’t currently supported. For more information, see What’s happening to Visual Studio for Mac? Visual Studio Code on Windows, Mac, and Linux works well with Python through available extensions.

Q. What can I use to build UI with Python?

A. The main offering in this area is the Qt Project with bindings for Python known as PySide (the official binding) (also see PySide downloads) and PyQt. Python support in Visual Studio doesn’t include any specific tools for UI development.

Q. Can a Python project produce a stand-alone executable?

A. Python is generally an interpreted language, where code is run on demand in a suitable Python-capable environment such as Visual Studio and web servers. Visual Studio doesn’t currently provide the means to create a stand-alone executable, which essentially means a program with an embedded Python interpreter. However, the Python community offers different means to create executables as described on StackOverflow. CPython also supports being embedded within a native application, as described on the blog post, Using CPython’s embeddable zip file.

Create a virtual environment

A best practice among Python developers is to use a project-specific

virtual environment

. Once you activate that environment, any packages you then install are isolated from other environments, including the global interpreter environment, reducing many complications that can arise from conflicting package versions. You can create non-global environments in VS Code using Venv or Anaconda with Python: Create Environment.

Open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)), start typing the Python: Create Environment command to search, and then select the command.

The command presents a list of environment types, Venv or Conda. For this example, select Venv.

The command then presents a list of interpreters that can be used for your project. Select the interpreter you installed at the beginning of the tutorial.

After selecting the interpreter, a notification will show the progress of the environment creation and the environment folder (

/.venv

) will appear in your workspace.

Ensure your new environment is selected by using the Python: Select Interpreter command from the Command Palette.

Note: For additional information about virtual environments, or if you run into an error in the environment creation process, see Environments.

Switch the current project environment

In Visual Studio, you can change the active (current) environment for a Python project in Solution Explorer or from the toolbar by using the Add Environment feature.

1. Start the Add Environment process:

   • In Solution Explorer, right-click the Python Environments node for your project and select Add Environment.
   • Or, on the Python toolbar, select Add Environment from the Environment dropdown menu.

2. In the Add Environment dialog, select the Existing environment tab. Expand the Environment dropdown list and choose your desired environment, then select Add.

Note

If the environment you want to use isn’t listed, you might need to manually identify an existing environment.

Test your install

Quickly check your installation of Python support:

1. Launch Visual Studio.

2. Select Alt + I to open the Python Interactive window.

3. In the window, enter the statement

   
2+2

   .

   The statement output

   displays in the window. If you don’t see the correct output, recheck your steps.

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