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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.

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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.

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 3.7 from python.org and install the extension from the VS Code Marketplace.

Once you have a version of Python installed, activate 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 Remote - 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.

Insiders program

The Insiders program allows you to try out and automatically install new versions of the Python extension prior to release, including new features and fixes.

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If you'd like to opt into the program, you can either open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) and select Python: Switch to Insiders Daily/Weekly Channel or else you can open settings (⌘, (Windows, Linux Ctrl+,)) and look for Python: Insiders Channel to set the channel to 'daily' or 'weekly'.

Run Python code

To experience Python, create a file (using the File Explorer) named hello.py and paste in the following code (assuming Python 3):

The Python extension then provides shortcuts to run Python code in the currently selected interpreter (Python: Select Interpreter in the Command Palette):

  • In the text editor: right-click anywhere in the editor and select Run Python File in Terminal. If invoked on a selection, only that selection is run.
  • In Explorer: right-click a Python file and select Run Python File in Terminal.

You can also use the Terminal: Create New Integrated Terminal command to create a terminal in which VS Code automatically activates the currently selected interpreter. See Environments below. The Python: Start REPL activates a terminal with the currently selected interpreter and then runs the Python REPL.

For a more specific walkthrough on running code, see the 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, and you can trigger completions at any time with ⌃Space (Windows, Linux Ctrl+Space). You can also hover over identifiers for more information about them.

Tip: Check out the IntelliCode extension for VS Code (preview). IntelliCode provides a set of AI-assisted capabilities for IntelliSense in Python, such as inferring the most relevant auto-completions based on the current code context.

Linting

Linting analyzes your Python code for potential errors, making it easy to navigate to and correct different problems.

The Python extension can apply a number of different linters including Pylint, pycodestyle, Flake8, mypy, pydocstyle, prospector, and pylama. See Linting.

Debugging

No more print statement debugging! Set breakpoints, inspect data, and use the debug console as you run your program step by step. Debug a number of different types of Python applications, including multi-threaded, web, and remote applications.

For Python-specific details, including setting up your launch.json configuration and remote debugging, see Debugging. General VS Code debugging information is found in the debugging document. The Django and Flask tutorials also demonstrate debugging in the context of those web apps, including debugging Django page templates.

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. You can also use the python.pythonPath setting to point to an interpreter anywhere on your computer.

The current environment is shown on the left 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 other than debugging. It is also activated when you use run Python in a terminal.

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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).

Installing packages

Packages are installed using the Terminal panel and commands like pip install <package_name> (Windows) and pip3 install <package_name> (macOS/Linux). VS Code installs that package into your project along with its dependencies. Examples are given in the Python tutorial as well as the Django and Flask tutorials.

Jupyter notebooks

If you open a Jupyter notebook file (.ipynb) in VS Code, you can use the Jupyter Notebook Editor to directly view, modify, and run code cells.

You can also convert and open the notebook as a Python code file. The notebook's cells are delimited in the Python file with #%% comments, and the Python extension shows Run Cell or Run All Cells CodeLens. Selecting either CodeLens starts the Jupyter server and runs the cell(s) in the Python interactive window:

Opening a notebook as a Python file allows you to use all of VS Code's debugging capabilities. You can then save the notebook file and open it again as a notebook in the Notebook Editor, Jupyter, or even upload it to a service like Azure Notebooks.

Using either method, Notebook Editor or a Python file, you can also connect to a remote Jupyter server for running the code. For more information, see Jupyter support.

Testing

The Python extension supports testing with the unittest, pytest, and nose test frameworks.

To run tests, you enable one of the frameworks in settings. Each framework also has specific settings, such as arguments that identify paths and patterns for test discovery.

Once discovered, VS Code provides a variety of commands (on the Status Bar, the Command Palette, and elsewhere) to run and debug tests, including the ability to run individual test files and individual methods.

Configuration

The Python extension provides a wide variety of settings for its various features. These are described on their relevant topics, such as Editing code, Linting, Debugging, and Testing. The complete list is found in the Settings reference.

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'.
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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.

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.
03/07/2019
-->Code Visual Studio Code

Applies to: SQL Server (all supported versions) - Linux

This article shows how to use the mssql extension for Visual Studio Code to develop SQL Server databases. Because Visual Studio Code is cross-platform, you can use mssql extension on Linux, macOS, and Windows.

Install and start Visual Studio Code

Visual Studio Code is a cross-platform, graphical code editor that supports extensions.

  1. Download and install Visual Studio Code on your machine.

  2. Start Visual Studio Code.

    Note

    If Visual Studio Code does not start when you are connected through an xrdp remote desktop session, see VS Code not working on Ubuntu when connected using XRDP.

Install the mssql extension

The mssql extension for Visual Studio Code lets you connect to a SQL Server, query with Transact-SQL (T-SQL), and view the results.

  1. In Visual Studio Code, select View > Command Palette, or press Ctrl+Shift+P, or press F1 to open the Command Palette.

  2. In the Command Palette, select Extensions: Install Extensions from the dropdown.

  3. In the Extensions pane, type mssql.

  4. Select the SQL Server (mssql) extension, and then select Install.

  5. After the installation completes, select Reload to enable the extension.

Create or open a SQL file

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The mssql extension enables mssql commands and T-SQL IntelliSense in the code editor when the language mode is set to SQL.

  1. Select File > New File or press Ctrl+N. Visual Studio Code opens a new Plain Text file by default.

  2. Select Plain Text on the lower status bar, or press Ctrl+K > M, and select SQL from the languages dropdown.

    Note

    If this is the first time you have used the extension, the extension installs supporting SQL Server tools.

If you open an existing file that has a .sql file extension, the language mode is automatically set to SQL.

Connect to SQL Server

Follow these steps to create a connection profile and connect to a SQL Server.

  1. Press Ctrl+Shift+P or F1 to open the Command Palette.

  2. Type sql to display the mssql commands, or type sqlcon, and then select MS SQL: Connect from the dropdown.

    Note

    A SQL file, such as the empty SQL file you created, must have focus in the code editor before you can execute the mssql commands.

  3. Select the MS SQL: Manage Connection Profiles command.

  4. Then select Create to create a new connection profile for your SQL Server.

  5. Follow the prompts to specify the properties for the new connection profile. After specifying each value, press Enter to continue.

    Connection propertyDescription
    Server name or ADO connection stringSpecify the SQL Server instance name. Use localhost to connect to a SQL Server instance on your local machine. To connect to a remote SQL Server, enter the name of the target SQL Server, or its IP address. To connect to a SQL Server container, specify the IP address of the container's host machine. If you need to specify a port, use a comma to separate it from the name. For example, for a server listening on port 1401, enter <servername or IP>,1401.
    As an alternative, you can enter the ADO connection string for your database here.
    Database name (optional)The database that you want to use. To connect to the default database, don't specify a database name here.
    Authentication TypeChoose either Integrated or SQL Login.
    User nameIf you selected SQL Login, enter the name of a user with access to a database on the server.
    PasswordEnter the password for the specified user.
    Save PasswordPress Enter to select Yes and save the password. Select No to be prompted for the password each time the connection profile is used.
    Profile Name (optional)Type a name for the connection profile, such as localhost profile.

    After you enter all values and select Enter, Visual Studio Code creates the connection profile and connects to the SQL Server.

    Tip

    If the connection fails, try to diagnose the problem from the error message in the Output panel in Visual Studio Code. To open the Output panel, select View > Output. Also review the connection troubleshooting recommendations.

  6. Verify your connection in the lower status bar.

As an alternative to the previous steps, you can also create and edit connection profiles in the User Settings file (settings.json). To open the settings file, select File > Preferences > Settings. For more information, see Manage connection profiles.

Create a SQL database

  1. In the new SQL file that you started earlier, type sql to display a list of editable code snippets.

  2. Select sqlCreateDatabase.

  3. In the snippet, type TutorialDB to replace 'DatabaseName':

  4. Press Ctrl+Shift+E to execute the Transact-SQL commands. View the results in the query window.

    Tip

    You can customize the shortcut keys for the mssql commands. See Customize shortcuts.

Create a table

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  1. Delete the contents of the code editor window.

  2. Press Ctrl+Shift+P or F1 to open the Command Palette.

  3. Type sql to display the mssql commands, or type sqluse, and then select the MS SQL: Use Database command.

  4. Select the new TutorialDB database.

  5. In the code editor, type sql to display the snippets, select sqlCreateTable, and then press Enter.

  6. In the snippet, type Employees for the table name.

  7. Press Tab to get to the next field, and then type dbo for the schema name.

  8. Replace the column definitions with the following columns:

  9. Press Ctrl+Shift+E to create the table.

Insert and query

  1. Add the following statements to insert four rows into the Employees table.

    While you type, T-SQL IntelliSense helps you to complete the statements:

    Tip

    The mssql extension also has commands to help create INSERT and SELECT statements. These were not used in the previous example.

  2. Press Ctrl+Shift+E to execute the commands. The two result sets display in the Results window.

View and save the result

  1. Select View > Editor Layout > Flip Layout to switch to a vertical or horizontal split layout.

  2. Select the Results and Messages panel headers to collapse and expand the panels.

    Tip

    You can customize the default behavior of the mssql extension. See Customize extension options.

  3. Select the maximize grid icon on the second result grid to zoom in to those results.

    Note

    The maximize icon displays when your T-SQL script produces two or more result grids.

  4. Open the grid context menu by right-clicking on the grid.

  5. Select Select All.

  6. Open the grid context menu again and select Save as JSON to save the result to a .json file.

  7. Specify a file name for the JSON file.

  8. Verify that the JSON file saves and opens in Visual Studio Code.

If you need to save and run SQL scripts later, for administration or a larger development project, save the scripts with a .sql extension.

Next steps

If you're new to T-SQL, see Tutorial: Write Transact-SQL statements and the Transact-SQL Reference (Database Engine).

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For more information on using or contributing to the mssql extension, see the mssql extension project wiki.

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For more information on using Visual Studio Code, see the Visual Studio Code documentation.