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Microsoft Visual Studio Python | Prerequisites

How to Setup Python on Microsoft Visual Studio 2022 | Amit Thinks

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.

Add Git source control

Now that you’ve created an app, you might want to add it to a Git repository. Visual Studio makes that process easy with Git tools you can use directly from the IDE.

Tip

Git is the most widely used modern version control system, so whether you’re a professional developer or you’re learning how to code, Git can be very useful. If you’re new to Git, the https://git-scm.com/ website is a good place to start. There, you can find cheat sheets, a popular online book, and Git Basics videos.

To associate your code with Git, start by creating a new Git repository where your code is located:

  1. In the status bar at the bottom-right corner of Visual Studio, select Add to Source Control, and then select Git.

  2. In the Create a Git repository dialog box, sign in to GitHub.

    The repository name auto-populates based on your folder location. Your new repository is private by default, which means you’re the only one who can access it.

    Tip

    Whether your repository is public or private, it’s best to have a remote backup of your code stored securely on GitHub. Even if you aren’t working with a team, a remote repository makes your code available to you from any computer.

  3. Select Create and Push.

    After you create your repository, you see status details in the status bar.

    The first icon with the arrows shows how many outgoing/incoming commits are in your current branch. You can use this icon to pull any incoming commits or push any outgoing commits. You can also choose to view these commits first. To do so, select the icon, and then select View Outgoing/Incoming.

    The second icon with the pencil shows the number of uncommitted changes to your code. You can select this icon to view those changes in the Git Changes window.

To learn more about how to use Git with your app, see the Visual Studio version control documentation.

How to Setup Python on Microsoft Visual Studio 2022 | Amit Thinks
How to Setup Python on Microsoft Visual Studio 2022 | Amit Thinks

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.

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.

Visual Studio 2022 (Python Getting Started)
Visual Studio 2022 (Python Getting Started)

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.

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.

Getting Started with Python in Visual Studio Code | Python with VSCode
Getting Started with Python in Visual Studio Code | Python with VSCode

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:

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.

First Python App in Visual Studio 2022 | Getting Started
First Python App in Visual Studio 2022 | Getting Started

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:

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.
Getting Started with Python in Visual Studio Code
Getting Started with Python in Visual Studio Code

Install Python and the Python extension

The tutorial guides you through installing Python and using the extension. You must install a Python interpreter yourself separately from the extension. For a quick install, use Python from python.org and install the extension from the VS Code Marketplace.

Note: To help get you started with Python development, you can use the Python profile template that includes useful extensions, settings, and Python code snippets.

Once you have a version of Python installed, select it using the Python: Select Interpreter command. If VS Code doesn’t automatically locate the interpreter you’re looking for, refer to Environments – Manually specify an interpreter.

You can configure the Python extension through settings. Learn more in the Python Settings reference.

Windows Subsystem for Linux: If you are on Windows, WSL is a great way to do Python development. You can run Linux distributions on Windows and Python is often already installed. When coupled with the WSL extension, you get full VS Code editing and debugging support while running in the context of WSL. To learn more, go to Developing in WSL or try the Working in WSL tutorial.

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

Python support in Visual Studio on Windows

Python is a popular programming language that’s reliable, flexible, easy to learn, free to use on all operating systems, and supported by both a strong developer community and many free libraries. Python supports all manner of development, including web applications, web services, desktop apps, scripting, and scientific computing. Scientists, casual developers, professional developers, and many universities alike use Python for programming. You can learn more about the language on python.org and Python for Beginners.

Visual Studio is a powerful Python IDE on Windows. Visual Studio provides open-source support for the Python language through the Python Development and Data Science workloads (Visual Studio 2017 and later) and the free Python Tools for Visual Studio extension (Visual Studio 2015 and earlier). Tour the Visual Studio IDE to familiarize yourself with the IDE features for writing and editing Python code.

Visual Studio Code is available on Mac and Linux. For more information, see questions and answers.

To get started:

  • Follow the installation instructions to set up the Python workload.

  • Familiarize yourself with the Python capabilities of Visual Studio through the sections in this article.

  • Go through one or more of the Quickstarts to create a project. If you’re unsure, start with Quickstart: Open and run Python code in a folder or Create a web app with Flask.

  • Follow the Work with Python in Visual Studio tutorial for a full end-to-end experience.

How to set up Python on Visual Studio Code
How to set up Python on Visual Studio Code

Testing

The Python extension supports testing with Python’s built-in unittest framework and pytest.

In order to run tests, you must enable one of the supported testing frameworks in the settings of your project. Each framework has its own specific settings, such as arguments for identifying the paths and patterns for test discovery.

Once the tests have been discovered, VS Code provides a variety of commands (on the Status Bar, the Command Palette, and elsewhere) to run and debug tests. These commands also allow you to run individual test files and methods

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 (*).

How to Create Python File in Visual Studio (2023)
How to Create Python File in Visual Studio (2023)

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!

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.

Python Desktop Application in Visual Studio 2019 | IronPython Getting Started
Python Desktop Application in Visual Studio 2019 | IronPython Getting Started

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!

Enhance completions with AI

GitHub Copilot is an AI-powered code completion tool that helps you write code faster and smarter. You can use the GitHub Copilot extension in VS Code to generate code, or to learn from the code it generates.

GitHub Copilot provides suggestions for languages beyond Python and a wide variety of frameworks, including JavaScript, TypeScript, Ruby, Go, C# and C++.

You can learn more about how to get started with Copilot in the Copilot documentation.

تعلم فيجول استديو فى 50 دقيقة | visual studio code
تعلم فيجول استديو فى 50 دقيقة | visual studio code

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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.

Environments

The Python extension automatically detects Python interpreters that are installed in standard locations. It also detects conda environments as well as virtual environments in the workspace folder. See Configuring Python environments.

The current environment is shown on the right side of the VS Code Status Bar:

The Status Bar also indicates if no interpreter is selected:

The selected environment is used for IntelliSense, auto-completions, linting, formatting, and any other language-related feature. It is also activated when you run or debug Python in a terminal, or when you create a new terminal with the Terminal: Create New Terminal command.

To change the current interpreter, which includes switching to conda or virtual environments, select the interpreter name on the Status Bar or use the Python: Select Interpreter command.

VS Code prompts you with a list of detected environments as well as any you’ve added manually to your user settings (see Configuring Python environments).

Microsoft FINALLY killed it
Microsoft FINALLY killed it

Support for multiple interpreters

Visual Studio’s Python Environments window gives you a single place to manage all of your global Python environments, conda environments, and virtual environments. Visual Studio automatically detects installations of Python in standard locations, and allows you to configure custom installations. With each environment, you can easily manage packages, open an interactive window for that environment, and access environment folders.

Use the Open interactive window command to run Python interactively within the context of Visual Studio. Use the Open in PowerShell command to open a separate command window in the folder of the selected environment. In that command window, you can run any python script.

For more information:

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.

How To Create & Activate A Virtual Environment In Visual Studio Code (Python 3.12)
How To Create & Activate A Virtual Environment In Visual Studio Code (Python 3.12)

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.

Autocomplete and IntelliSense

The Python extension supports code completion and IntelliSense using the currently selected interpreter. IntelliSense is a general term for a number of features, including intelligent code completion (in-context method and variable suggestions) across all your files and for built-in and third-party modules.

IntelliSense quickly shows methods, class members, and documentation as you type. You can also trigger completions at any time with ⌃Space (Windows, Linux Ctrl+Space). Hovering over identifiers will show more information about them.

How To Install Python Libraries In Visual Studio Code (Windows 11)
How To Install Python Libraries In Visual Studio Code (Windows 11)

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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.

Prerequisites

  • Ability to install programs locally.
  • Basic familiarity with programming concepts.
  • Introduction min
  • Install Python 3 min
  • Knowledge check min
  • Summary min

Step 2: Write and run code

Previous step: Create a new Python project

Although Solution Explorer is where you manage project files, the editor window is typically where you work with the contents of files, like source code. The editor is contextually aware of the type of file you’re editing. The editor also recognizes the programming language (based on the file extension), and offers features appropriate to that language such as syntax coloring and auto-completion using IntelliSense.

  1. When you create a new “Python Application” project, a default empty file named PythonApplication1.py is opened in the Visual Studio editor.

  2. In the editor, start typing


    print("Hello, Visual Studio")

    and notice how Visual Studio IntelliSense displays autocompletion options along the way. The outlined option in the drop-down list is the default completion that’s used when you press the Tab key. Completions are most helpful when longer statements or identifiers are involved.

  3. IntelliSense shows different information based on the statement you’re using, the function you’re calling, and so on. With the

    after

  4. Complete the statement so it matches the code below:


    print("Hello, Visual Studio")

  5. Notice the syntax coloration that differentiates the statement


    "Hello Visual Studio"

    . You can, temporarily delete the laston the string and notice how Visual Studio shows a red underline for code that contains syntax errors. Finally replace theto correct the code.

    Tip

    Because one’s development environment is a very personal matter, Visual Studio gives you complete control over Visual Studio’s appearance and behavior. Select the Tools > Options menu command and explore the settings under the Environment and Text Editor tabs. By default you see only a limited number of options; to see every option for every programming language, select Show all settings at the bottom of the dialog.

  6. Run the code you’ve written to this point by pressing Ctrl+F5 or selecting Debug > Start without Debugging menu item. Visual Studio warns you if you still have errors in your code.

  7. When you run the program, a console window will display the results. It’s similar to running a Python interpreter with PythonApplication1.py from the command line. Press any key to close the window and return to the Visual Studio editor.

  8. In addition to completions for statements and functions, IntelliSense provide completions for Python


    import

    and

    from

    statements. These completions help you easily discover what modules are available in your environment and the members of those modules. In the editor, delete the

    import

    . A list of modules appears when you type the space:

  9. Complete the line by typing or selecting


    sys

    .

  10. On the next line, type


    from

    to again see a list of modules:

  11. Select or type


    math

    , then continue typing with a space and

    import

    , which displays the module members:

  12. Finish by importing the


    cos

    and

    radians

    members, noticing the autocompletions available for each. When you’re done, your code should appear as follows:

    import sys from math import cos, radians

    Tip

    Completions work with substrings as you type, matching parts of words, letters at the beginning of words, and even skipped characters. See Edit code – Completions for details.

  13. Add a little more code to print the cosine values for 360 degrees:


    for i in range(360): print(cos(radians(i)))

  14. Run the program again with Ctrl+F5 or Debug > Start without Debugging. Close the output window when you’re done.

How to create Virtual Environment for Python in Visual Studio Code (2023)
How to create Virtual Environment for Python in Visual Studio Code (2023)

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

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
Beginners Guide to Run DhanHQ APIs for API Trading | What is Algo Trading? | EP-02 | Dhan
Beginners Guide to Run DhanHQ APIs for API Trading | What is Algo Trading? | EP-02 | Dhan

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.

Tutorial review

Congratulations on completing this tutorial on Python in Visual Studio. In this tutorial you’ve learned how to:

  • Create projects and view a project’s contents.
  • Use the code editor and run a project.
  • Use the Interactive window to develop new code and easily copy that code into the editor.
  • Run a completed program in the Visual Studio debugger.
  • Install packages and manage Python environments.
  • Work with code in a Git repository.

From here, explore the Concepts and How-to guides, including the following articles:

How To Setup A Virtual Environment For Python In Visual Studio Code In 2023
How To Setup A Virtual Environment For Python In Visual Studio Code In 2023

Next steps

  • Python Hello World tutorial – Get started with Python in VS Code.
  • Editing Python – Learn about auto-completion, formatting, and refactoring for Python.
  • Basic Editing – Learn about the powerful VS Code editor.
  • Code Navigation – Move quickly through your source code.
  • Django tutorial
  • Flask tutorial

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.

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
Best Python IDE: Vim, Emacs, PyCharm, or Visual Studio Code? | Guido van Rossum and Lex Fridman
Best Python IDE: Vim, Emacs, PyCharm, or Visual Studio Code? | Guido van Rossum and Lex Fridman

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.

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.

How to Run Python 3.12 in Visual Studio Code on Windows 10 [2023]| Run Sample Python Program
How to Run Python 3.12 in Visual Studio Code on Windows 10 [2023]| Run Sample Python Program

Open source

Fork us on Github

Python Tools for Visual Studio is a completely free extension, developed and supported by Microsoft with contributions from the community. Visit our Github page to see or participate in PTVS development.

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.

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.

Learn Visual Studio 2022 in 45 minutes | Amit Thinks
Learn Visual Studio 2022 in 45 minutes | Amit Thinks

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