Visual Studio For Mac Python | Create A Virtual Environment

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.

Debugging

No more

For more specific information on debugging in Python, such as configuring your

launch.json

settings and implementing remote debugging, see Debugging. General VS Code debugging information is found in the debugging document.

Additionally, the Django and Flask tutorials provide examples of how to implement debugging in the context of web applications, including debugging Django templates.

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

Preview vs stable builds of Visual Studio for Mac

There will be no preview builds now that Visual Studio for Mac is on track for retirement on August 31, 2024. The preview channel is also no longer being updated.

We recommend that you switch to a stable build for the latest security and reliability updates. Here’s how:

1. Download the stable Visual Studio for Mac installer.
2. Run the installer.
3. Launch Visual Studio from
   
/Applications/Visual Studio.app

   .
4. You can now delete
   
/Applications/Visual Studio (Preview).app

   .

Modern development with .NET 7

Visual Studio 2022 for Mac includes nearly everything you’ll need for .NET 7 development, from responsive C# web UIs in Blazor to event-driven solutions using Azure Functions.

Advanced IntelliSense

With the power of Roslyn, Visual Studio for Mac brings IntelliSense to your fingertips. IntelliSense describes APIs as you type and uses auto-completion to increase the speed and accuracy of how you write code.

Quick Info tool tips let you inspect API definitions. Squiggly lines in the editor highlight issues in real time as you type.

Intelligent Refactoring

As your project grows, chances are, you’ll find yourself restructuring and refactoring code that you or someone else wrote earlier. That’s a whole lot easier when Visual Studio for Mac takes care of the heavy lifting for you.

Learn more about Xamarin.Essentials

Integrated Version Control

Visual Studio 2022 has built-in support for Git version control to clone, create, and open your own repositories. The Git tool window has everything you need for committing and pushing changes to code.

Powerful Debugging

Integrated debugging is a core part of every Visual Studio product. You can step through your code and look at the values stored in variables, set watches on variables to see when values change, examine the execution path of your code, and just about anything else you need to check out under the hood.

.NET

Build modern solutions for the web and cloud with ASP.NET Core.

Xamarin

Build apps for iOS, Android, macOS, and more with C# and .NET

Unity

Build your next game or real-time 3D Unity application with best-in-class debugging.

Visual Studio 2022 for Mac	Visual Studio 2022
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Web and Cloud development using C#
Desktop development
Mobile and gaming
Other workloads and tools

Python in Visual Studio Code

Working with Python in Visual Studio Code, using the Microsoft Python extension, is simple, fun, and productive. The extension makes VS Code an excellent Python editor, and works on any operating system with a variety of Python interpreters. It leverages all of VS Code’s power to provide auto complete and IntelliSense, linting, debugging, and unit testing, along with the ability to easily switch between Python environments, including virtual and conda environments.

This article provides only an overview of the different capabilities of the Python extension for VS Code. For a walkthrough of editing, running, and debugging code, use the button below.

Python profile template

Profiles let you quickly switch your extensions, settings, and UI layout depending on your current project or task. To help you get started with Python development, you can use the Python profile template, which is a curated profile with useful extensions, settings, and snippets. You can use the profile template as is or use it as a starting point to customize further for you own workflows.

You select a profile template through the Profiles > Create Profile… dropdown:

Once you select a profile template, you can review the settings and extensions, and remove individual items if you don’t want to include them in your new Profile. After creating the new profile based on the template, changes made to settings, extensions, or UI are persisted in your profile.

Feedback

Submit and view feedback for

What’s happening to Visual Studio for Mac?

Visual Studio for Mac is scheduled for retirement by August 31, 2024 in accordance with Microsoft’s Modern Lifecycle Policy. Visual Studio for Mac 17.6 will continue to be supported until August 31, 2024, with servicing updates for security issues and updated platforms from Apple. We recommend that you switch to a stable build for the latest security and reliability updates.

While the decision has been made to retire Visual Studio for Mac, we remain committed to our developers on Mac and .NET MAUI with alternatives like the C# Dev Kit for Visual Studio Code and other extensions you can use to take advantage of our ongoing investments in .NET development.

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.

Alternative options for developing on the Mac

Visual Studio Code is a great place for cloud-native .NET development on the Mac with things like Azure Functions, and more. As of 2023, premier support is available in Visual Studio Code for .NET cloud, .NET MAUI, and Mobile C# development through the C# Dev Kit. Additionally, the C# Dev Kit for .NET MAUI offers support for designing, editing, and debugging Unity scripts as well. These extensions operate natively across all supported platforms, including macOS, and the experience using these are continuously improved as they move from preview to General Availability and beyond. We are continuing to invest in making these a great experience for C#, .NET MAUI and Unity development on Visual Studio Code. We encourage you submit suggestions and report issues for these extensions in the Visual Studio Code GitHub project repository.

Visual Studio continues to be the premier tool of choice for .NET/C# development. If you prefer to use a full-fledged IDE, you can use the same license for Visual Studio for Mac on Visual Studio on Windows in a VM either on a Mac or in the cloud. You can use VM hosts like Parallels to set up Windows and work in Visual Studio (Windows). A cloud-hosted VM from Microsoft Dev Box provides access to the full power of Visual Studio through your Web or native RDP client from a Mac without the overhead of running a virtual machine on your local machine.

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 (*).

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.
   
   

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.

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!

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.

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

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.

Jupyter notebooks

To enable Python support for Jupyter notebook files (

.ipynb

) in VS Code, you can install the Jupyter extension. The Python and Jupyter extensions work together to give you a great Notebook experience in VS Code, providing you the ability to directly view and modify code cells with IntelliSense support, as well as run and debug them.

You can also convert and open the notebook as a Python code file through the Jupyter: Export to Python Script command. The notebook’s cells are delimited in the Python file with

#%%

comments, and the Jupyter extension shows Run Cell or Run Below CodeLens. Selecting either CodeLens starts the Jupyter server and runs the cell(s) in the Python interactive window:

You can also connect to a remote Jupyter server to run your notebooks. For more information, see Jupyter support.

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Submit and view feedback for

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.

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.

Run Python code

To experience Python, create a file (using the File Explorer) named

hello.py

and paste in the following code:


print("Hello World")


The Python extension then provides shortcuts to run Python code using the currently selected interpreter (Python: Select Interpreter in the Command Palette). To run the active Python file, click the Run Python File in Terminal play button in the top-right side of the editor.

You can also run individual lines or a selection of code with the Python: Run Selection/Line in Python Terminal command (Shift+Enter). If there isn’t a selection, the line with your cursor will be run in the Python Terminal. An identical Run Selection/Line in Python Terminal command is available on the context menu for a selection in the editor. The same terminal will be used every time you run a selection or a line in the terminal/REPL, until that terminal is closed. The same terminal is also used for Run Python File in Terminal. If that terminal is still running the REPL, you should exit the REPL (

exit()

) or switch to a different terminal before running a Python file.

The Python extension automatically removes indents based on the first non-empty line of the selection, shifting all other lines left as needed.

The command opens the Python Terminal if necessary; you can also open the interactive REPL environment directly using the Python: Start REPL command that activates a terminal with the currently selected interpreter and then runs the Python REPL.

For a more specific walkthrough and other ways of running code, see the run code tutorial.

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.

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!

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.

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!

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.

Other popular Python extensions

The Microsoft Python extension provides all of the features described previously in this article. Additional Python language support can be added to VS Code by installing other popular Python extensions.

1. Open the Extensions view (⇧⌘X (Windows, Linux Ctrl+Shift+X)).
2. Filter the extension list by typing ‘python’.

The extensions shown above are dynamically queried. Click on an extension tile above to read the description and reviews to decide which extension is best for you. See more in the Marketplace.

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!

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

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.
   
   

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Cài đặt và cấu hình Python3 cho Visual Studio Code hệ điều hành MacOS

Bài đăng này đã không được cập nhật trong 4 năm

Trước khi cài đặt Visual Studio Code bạn cần phải cài đặt Python. Xem bài viết hướng dẫn dưới đây:

Visual Studio Code: là mã nguồn mở, là công cụ đắc lực cho việc lập trình với ưu điểm là nhẹ và hỗ trợ nhiều ngôn ngữ: Python, ReactJS, Node,…

Chúng ta sẽ sử dụng Homebrew để cài đặt Visual Studio Code.

Homebrew là công cụ quản lý package phổ biến, được sử dụng để cài đặt phần mềm mã nguồn mở như là: Node.

Cài đặt HomeBrew

Mở ứng dụng terminal (/Applications/Utilities/Terminal) và chạy lệnh sau:


ruby -e "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/master/install)"


Trong lúc cài đặt sẽ yêu cầu bạn nhập mật khẩu, bạn nhập mật khẩu máy tính vào, và đợi cài đặt trong 1-2 phút, tuỳ theo tốc độ mạng.

Cài đặt Visual Studio Code

Trước khi cài đặt Visual Studio Code, chúng ta cập nhập HomeBrew bằng lệnh sau:


brew update brew tap caskroom/cask


Sau đó cài đặt Visual Studio Code bằng cách nhập lệnh dưới đây:


brew cask install visual-studio-code


Mở Visual Studio Code (/Applications/Visual Studio Code). Tại màn hình welcome chọn

Add workspace folder...

tạo thư mục với tên là

hello


Click phải vào thư mục, chọn

New File

đặt tên file là

hello_world.py

.

Nhập đoạn code sau vào file

hello_world.py

.


print("Hello to Python world!")


Click vào góc dưới bên trái màn hình chọn phiên bản Python mới nhất, ở đây mình chọn 3.8.1

Click phải vào khung soạn thảo văn bản, chọn

Run Python File in Terminal


Kết quả sẽ xuất ra là

Hello to Python world!


Tổng kết

Homebrew là công cụ quản lý package phổ biến, được sử dụng để cài đặt phần mềm mã nguồn mở. Sử dụng Homebrew giúp cho chúng ta cài đặt Visual Studio Code trong thời gian ngắn.

Trong lúc cài đặt. Nếu có vấn đề khi cài đặt, bạn hãy comment bên dưới, mình sẽ hỗ trợ trong thời gian sớm nhất!

Cảm ơn các bạn đã quan tâm bài viết này.

Tham khảo Cài đặt Homebrew.

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