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

In Visual Studio Code, select the Teams icon from the activity bar on the left side of the window. Select Import app package from the command menu. Choose your existing Teams app package zip file. Choose the Select publishing package button. The configuration tab of the toolkit should now be populated with your app's details.

1. Visual Studio Code is a code editor redefined and optimized for building and debugging modern web and cloud applications. Visual Studio Code is free and available on your favorite platform.
2. The Visual Studio Code C# extension can generate the assets you need to build and debug. If you missed the prompt when you first opened a new C# project, you can still perform this operation through the Command Palette ( View Command Palette) by typing '.NET', and running.NET: Generate Assets for Build and Debug.
3. Visual Studio Code will make you more productive in developing these types of applications by providing great code editing and navigation experiences. Open the file app.js and hover over the Node.js global object dirname. Notice how VS Code understands that dirname is a string. Even more interesting, you can get full IntelliSense against the Node.js framework.

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

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

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

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

Prerequisites

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

• VS Code
• VS Code Python extension
• Python 3

Install Visual Studio Code and the Python Extension

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

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

Install a Python interpreter

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

Windows

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

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

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

macOS

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

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

Linux

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

Other options

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

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

Verify the Python installation

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

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

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

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

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

Start VS Code in a project (workspace) folder

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

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

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

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

Select a Python interpreter

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

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

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

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

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

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

Create a Python Hello World source code file

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

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

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

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

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

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

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

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

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

Run Hello World

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

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

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

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

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

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

Configure and run the debugger

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Install and use packages

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

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

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

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

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

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

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

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

1. Create and activate the virtual environment

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

   For Windows

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

   For macOS/Linux

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

3. Install the packages

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

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

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

Next steps

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

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

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

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

• Editing code - Learn about autocomplete, IntelliSense, formatting, and refactoring for Python.
• Linting - Enable, configure, and apply a variety of Python linters.
• Debugging - Learn to debug Python both locally and remotely.
• Testing - Configure test environments and discover, run, and debug tests.
• Settings reference - Explore the full range of Python-related settings in VS Code.

Node.js is a platform for building fast and scalable server applications using JavaScript. Node.js is the runtime and npm is the Package Manager for Node.js modules.

Visual Studio Code has support for the JavaScript and TypeScript languages out-of-the-box as well as Node.js debugging. However, to run a Node.js application, you will need to install the Node.js runtime on your machine.

To get started in this walkthrough, install Node.js for your platform. The Node Package Manager is included in the Node.js distribution. You'll need to open a new terminal (command prompt) for the node and npm command-line tools to be on your PATH.

Linux: There are specific Node.js packages available for the various flavors of Linux. See Installing Node.js via package manager to find the Node.js package and installation instructions tailored to your version of Linux.

Tip: To test that you've got Node.js correctly installed on your computer, open a new terminal and type node --help and you should see the usage documentation.

Hello World

Let's get started by creating the simplest Node.js application, 'Hello World'.

Create an empty folder called 'hello', navigate into and open VS Code:

Tip: You can open files or folders directly from the command line. The period '.' refers to the current folder, therefore VS Code will start and open the Hello folder.

From the File Explorer toolbar, press the New File button:

and name the file app.js:

By using the .js file extension, VS Code interprets this file as JavaScript and will evaluate the contents with the JavaScript language service. Refer to the VS Code JavaScript language topic to learn more about JavaScript support.

Create a simple string variable in app.js and send the contents of the string to the console:

Note that when you typed console.IntelliSense on the console object was automatically presented to you.

Also notice that VS Code knows that msg is a string based on the initialization to 'Hello World'. If you type msg. you'll see IntelliSense showing all of the string functions available on msg.

After experimenting with IntelliSense, revert any extra changes from the source code example above and save the file (⌘S (Windows, Linux Ctrl+S)).

Running Hello World

It's simple to run app.js with Node.js. From a terminal, just type:

You should see 'Hello World' output to the terminal and then Node.js returns.

Integrated Terminal

VS Code has an integrated terminal which you can use to run shell commands. You can run Node.js directly from there and avoid switching out of VS Code while running command-line tools.

View > Terminal (⌃` (Windows, Linux Ctrl+`) with the backtick character) will open the integrated terminal and you can run node app.js there:

For this walkthrough, you can use either an external terminal or the VS Code integrated terminal for running the command-line tools.

Debugging Hello World

As mentioned in the introduction, VS Code ships with a debugger for Node.js applications. Let's try debugging our simple Hello World application.

To set a breakpoint in app.js, put the editor cursor on the first line and press F9 or click in the editor left gutter next to the line numbers. A red circle will appear in the gutter.

To start debugging, select the Run View in the Activity Bar:

You can now click Debug toolbar green arrow or press F5 to launch and debug 'Hello World'. Your breakpoint will be hit and you can view and step through the simple application. Notice that VS Code displays a different colored Status Bar to indicate it is in Debug mode and the DEBUG CONSOLE is displayed.

Now that you've seen VS Code in action with 'Hello World', the next section shows using VS Code with a full-stack Node.js web app.

Note: We're done with the 'Hello World' example so navigate out of that folder before you create an Express app. You can delete the 'Hello' folder if you wish as it is not required for the rest of the walkthrough.

An Express application

Express is a very popular application framework for building and running Node.js applications. You can scaffold (create) a new Express application using the Express Generator tool. The Express Generator is shipped as an npm module and installed by using the npm command-line tool npm.

Tip: To test that you've got npm correctly installed on your computer, type npm --help from a terminal and you should see the usage documentation.

Install the Express Generator by running the following from a terminal:

The -g switch installs the Express Generator globally on your machine so you can run it from anywhere.

We can now scaffold a new Express application called myExpressApp by running:

This creates a new folder called myExpressApp with the contents of your application. The --view pug parameters tell the generator to use the pug template engine.

To install all of the application's dependencies (again shipped as npm modules), go to the new folder and execute npm install:

At this point, we should test that our application runs. The generated Express application has a package.json file which includes a start script to run node ./bin/www. This will start the Node.js application running.

V Studio Code

From a terminal in the Express application folder, run:

The Node.js web server will start and you can browse to http://localhost:3000 to see the running application.

Great code editing

Close the browser and from a terminal in the myExpressApp folder, stop the Node.js server by pressing CTRL+C.

Now launch VS Code:

Note: If you've been using the VS Code integrated terminal to install the Express generator and scaffold the app, you can open the myExpressApp folder from your running VS Code instance with the File > Open Folder command.

The Node.js and Express documentation does a great job explaining how to build rich applications using the platform and framework. Visual Studio Code will make you more productive in developing these types of applications by providing great code editing and navigation experiences.

Open the file app.js and hover over the Node.js global object __dirname. Notice how VS Code understands that __dirname is a string. Even more interesting, you can get full IntelliSense against the Node.js framework. For example, you can require http and get full IntelliSense against the http class as you type in Visual Studio Code.

VS Code uses TypeScript type declaration (typings) files (for example node.d.ts) to provide metadata to VS Code about the JavaScript based frameworks you are consuming in your application. Type declaration files are written in TypeScript so they can express the data types of parameters and functions, allowing VS Code to provide a rich IntelliSense experience. Thanks to a feature called Automatic Type Acquisition, you do not have to worry about downloading these type declaration files, VS Code will install them automatically for you.

You can also write code that references modules in other files. For example, in app.js we require the ./routes/index module, which exports an Express.Router class. If you bring up IntelliSense on index, you can see the shape of the Router class.

Debug your Express app

You will need to create a debugger configuration file launch.json for your Express application. Click on the Run icon in the Activity Bar and then the Configure gear icon at the top of the Run view to create a default launch.json file. Select the Node.js environment by ensuring that the type property in configurations is set to 'node'. When the file is first created, VS Code will look in package.json for a start script and will use that value as the program (which in this case is '${workspaceFolder}binwww) for the Launch Program configuration.

Save the new file and make sure Launch Program is selected in the configuration dropdown at the top of the Run view. Open app.js and set a breakpoint near the top of the file where the Express app object is created by clicking in the gutter to the left of the line number. Press F5 to start debugging the application. VS Code will start the server in a new terminal and hit the breakpoint we set. From there you can inspect variables, create watches, and step through your code.

Deploy your application

If you'd like to learn how to deploy your web application, check out the Deploying Applications to Azure tutorials where we show how to run your website in Azure.

Next steps

Visual Code Studio

There is much more to explore with Visual Studio Code, please try the following topics:

Studio.code.org/sections/

• Settings - Learn how to customize VS Code for how you like to work.
• Debugging - This is where VS Code really shines.
• Video: Getting started with Node.js debugging - Learn how to attach to a running Node.js process.
• Node.js debugging - Learn more about VS Code's built-in Node.js debugging.
• Debugging recipes - Examples for scenarios like client-side and container debugging.
• Tasks - Running tasks with Gulp, Grunt and Jake. Showing Errors and Warnings.