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Jupyter (formerly IPython Notebook) is an open-source project that lets you easily combine Markdown text and executable Python source code on one canvas called a notebook. Visual Studio Code supports working with Jupyter Notebooks natively, as well as through Python code files. This topic covers the native support available for Jupyter Notebooks and demonstrates how to:

• Create, open, and save Jupyter Notebooks
• Work with Jupyter code cells
• View, inspect, and filter variables using the Variable explorer and Data viewer
• Connect to a remote Jupyter server
• Debug a Jupyter notebook

Setting up your environment

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To work with Jupyter notebooks, you must activate an Anaconda environment in VS Code, or another Python environment in which you've installed the Jupyter package. To select an environment, use the Python: Select Interpreter command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).

Once the appropriate environment is activated, you can create and open a Jupyter Notebook, connect to a remote Jupyter server for running code cells, and export a Jupyter Notebook as a Python file.

Note: By default, the Visual Studio Code Python extension will open a Jupyter Notebook (.ipynb) in the Notebook Editor. If you want to disable this behavior you can turn it off in settings. (Python > Data Science: Use Notebook Editor).

Create or open a Jupyter Notebook

You can create a Jupyter Notebook by running the Jupyter: Create Blank New Jupyter Notebook command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) or by creating a new .ipynb file in your workspace. When you select the file, the Notebook Editor is launched allowing you to edit and run code cells.

If you have an existing Jupyter Notebook, you can open it in the Notebook Editor by double-clicking on the file and opening with Visual Studio Code, through the Visual Studio Code, or using the Command Palette Jupyter: Open in Notebook Editor command.

Once you have a Notebook created, you can run a code cell using the green run icon above the cell and the output will appear directly below the code cell.

Trusted Notebooks

It's possible for malicious source code to be contained in a Jupyter Notebook. With that in mind, to help protect you, any Notebook that's not created with VS Code on your local machine (or explicitly set to Trusted by you) is considered Not Trusted. When a Notebook is Not Trusted, VS Code will not render Markdown cells or display the output of code cells within the Notebook. Instead, just the source of Markdown and code cells will be shown. The Notebook is essentially in read-only mode, with toolbars disabled and no ability to edit the file, until you set it as Trusted.

Note: Before setting a Notebook as Trusted, it is up to you to verify that the source code and Markdown are safe to run. VS Code does not perform any sanitizing of Markdown, it merely prevents it from being rendered until a Notebook is marked as Trusted to help protect you from malicious code.

When you first open a Notebook that's Not Trusted, the following notification prompt is displayed.

If you select Trust, the Notebook will be trusted going forward. If you opt not to trust the Notebook, then Not Trusted will be displayed in the toolbar and the Notebook will remain in a read-only state as described previously. If you select Trust all notebooks, you will be taken to settings, where you can specify that all Notebooks opened in VS Code be trusted. That means you will no longer be prompted to trust individual notebooks and harmful code could automatically run.

You can relaunch the trust notification prompt after reviewing the Notebook by clicking on the Not Trusted status.

Save your Jupyter Notebook

You can save your Jupyter Notebook using the keyboard combo Ctrl+S or through the save icon on the Notebook Editor toolbar.

Note: At present, you must use the methods discussed above to save your Notebook. The File>Save menu does not save your Notebook, just the toolbar icon or keyboard command.

Export your Jupyter Notebook

You can export a Jupyter Notebook as a Python file (.py), a PDF, or an HTML file. To export, just click the convert icon on the main toolbar. You'll then be presented with file options from the Command Palette.

Note: For PDF export, you must have TeX installed. If you don't, you will be notified that you need to install it when you select the PDF option. Also, be aware that if you have SVG-only output in your Notebook, they will not be displayed in the PDF. To have SVG graphics in a PDF, either ensure that your output includes a non-SVG image format or else you can first export to HTML and then save as PDF using your browser.

Work with code cells in the Notebook Editor

The Notebook Editor makes it easy to create, edit, and run code cells within your Jupyter Notebook.

Create a code cell

By default, a blank Notebook will have an empty code cell for you to start with and an existing Notebook will place one at the bottom. Add your code to the empty code cell to get started.

Code cell modes

While working with code cells a cell can be in three states, unselected, command mode, and edit mode. The current state of a cell is indicated by a vertical bar to the left of a code cell. When no bar is visible, the cell is unselected.

An unselected cell isn't editable, but you can hover over it to reveal additional cell specific toolbar options. These additional toolbar options appear directly below and to the left of the cell. You'll also see when hovering over a cell that an empty vertical bar is present to the left.

When a cell is selected, it can be in two different modes. It can be in command mode or in edit mode. When the cell is in command mode, it can be operated on and accept keyboard commands. When the cell is in edit mode, the cell's contents (code or Markdown) can be modified.

When a cell is in command mode, the vertical bar to the left of the cell will be solid to indicate it's selected.

When you're in edit mode, the vertical bar will have diagonal lines.

To move from edit mode to command mode, press the ESC key. To move from command mode to edit mode, press the Enter key. You can also use the mouse to change the mode by clicking the vertical bar to the left of the cell or out of the code/Markdown region in the code cell.

Add additional code cells

Code cells can be added to a Notebook using the main toolbar, a code cell's vertical toolbar, the add code cell icon at the bottom of the Notebook, the add code cell icon at the top of the Notebook (visible with hover), and through keyboard commands.

Using the plus icon in the main toolbar will add a new cell directly below the currently selected cell. Using the add cell icons at the top and bottom of the Jupyter Notebook, will add a code cell at the top and bottom respectively. And using the add icon in the code cell's toolbar, will add a new code cell directly below it.

When a code cell is in command mode, the A key can be used to add a cell above and the B can be used to add a cell below the selected cell.

Select a code cell

The selected code cell can be changed using the mouse, the up/down arrow keys on the keyboard, and the J (down) and K (up) keys. To use the keyboard, the cell must be in command mode.

Run a single code cell

Once your code is added, you can run a cell using the green run arrow and the output will be displayed below the code cell.

You can also use key combos to run a selected code cell.

• Ctrl+Enter runs the currently selected cell
• Shift+Enter runs the currently selected cell and, if a cell is not already present, inserts a new cell immediately below (focus moves to the below cell in command mode)
• Alt+Enter runs the currently selected cell and inserts a new cell immediately below (focus moves to new cell in edit mode).

These keyboard combos can be used in both command and edit modes.

Run multiple code cells

Running multiple code cells can be accomplished in a number of ways. You can use the double arrow in the toolbar of the Notebook Editor to run all cells within the Notebook or the run icons with directional arrows to run all cells above or below the current code cell.

Run code by line

To help diagnose issues with your Notebook code, run-by-line lets you step through the code of a cell in a line-by-line fashion. While stepping through code you can view the state of variables at each step via the variable explorer or hover your mouse over variables to see data tips.

To start a session, just click the run-by-line icon to the right of the run cell icon on the cell's toolbar.

Once in a run-by-line session, you can run the currently highlighted line of code by pressing the icon again. To exit, just click the stop button next to the run-by-line icon in the cell.

Move a code cell

Moving code cells up or down within a Notebook can be accomplished using the vertical arrows beside each code cell. Hover over the code cell and then click the up arrow to move the cell up and the down arrow to move the cell down.

Delete a code cell

Deleting a code cell can be accomplished by hovering over a code cell and using the delete icon in the code cell toolbar or through the keyboard combo dd when the selected code cell is in command mode.

Undo your last change

You can use the z key to undo your previous change, for example, if you've made an accidental edit you can undo it to the previous correct state, or if you've deleted a cell accidentally you can recover it.

Switch between code and Markdown

The Notebook Editor allows you to easily change code cells between Markdown and code. By default a code cell is set for code, but just click the Markdown icon (or the code icon, if Markdown was previously set) in the code cell's toolbar to change it.

Once Markdown is set, you can enter Markdown formatted content to the code cell. Once you select another cell or toggle out of the content selection, the Markdown content is rendered in the Notebook Editor.

You can also use the keyboard to change the cell type. When a cell is selected and in command mode, the M key switches the cell type to Markdown and the Y key switches the cell type to code.

Clear output or restart/interrupt the kernel

If you'd like to clear the code cell output or restart/interrupt the kernel, you can accomplish that using the main Notebook Editor toolbar.

Enable/Disable line numbers

You can enable or disable line numbering within a code cell using the L key.

IntelliSense support in the Jupyter Notebook Editor

The Python Jupyter Notebook Editor window has full IntelliSense – code completions, member lists, quick info for methods, and parameter hints. You can be just as productive typing in the Notebook Editor window as you are in the code editor.

Variable explorer and data viewer

Within the Python Notebook Editor, it's possible to view, inspect, and filter the variables within your current Jupyter session. By clicking the Variables icon in the top toolbar after running code and cells, you'll see a list of the current variables, which will automatically update as variables are used in code.

For additional information about your variables, you can also double-click on a row or use the Show variable in data viewer button next to the variable to see a more detailed view of a variable in the Data Viewer. Once open, you can filter the values by searching over the rows.

Note: Variable explorer is enabled by default, but can be turned off in settings (Python > Data Science: Show Jupyter Variable Explorer).

Plot viewer

The Plot Viewer gives you the ability to work more deeply with your plots. In the viewer you can pan, zoom, and navigate plots in the current session. You can also export plots to PDF, SVG, and PNG formats.

Within the Notebook Editor window, double-click any plot to open it in the viewer, or select the plot viewer button on the upper left corner of the plot (visible on hover).

Note: There is support for rendering plots created with matplotlib and Altair.

Debug a Jupyter Notebook

If you need additional debug support in order to diagnose an issue in your code cells, you can export it as a Python file. Once exported as a Python file, the Visual Studio Code debugger lets you step through your code, set breakpoints, examine state, and analyze problems. Using the debugger is a helpful way to find and correct issues in notebook code. To debug your Python file:

1. In VS Code, if you haven't already, activate a Python environment in which Jupyter is installed.

2. From your Jupyter Notebook (.ipynb) select the convert button in the main toolbar.

   Once exported, you'll have a .py file with your code that you can use for debugging.

3. After saving the .py file, to start the debugger, use one of the following options:

   • For the whole Notebook, open the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) and run the Jupyter: Debug Current File in Python Interactive Window command.
   • For an individual cell, use the Debug Cell adornment that appears above the cell. The debugger specifically starts on the code in that cell. By default, Debug Cell just steps into user code. If you want to step into non-user code, you need to uncheck Data Science: Debug Just My Code in the Python extension settings (⌘, (Windows, Linux Ctrl+,)).

4. To familiarize yourself with the general debugging features of VS Code, such as inspecting variables, setting breakpoints, and other activities, review VS Code debugging.

5. As you find issues, stop the debugger, correct your code, save the file, and start the debugger again.

6. When you're satisfied that all your code is correct, use the Python Interactive window to export the Python file as a Jupyter Notebook (.ipynb).

Connect to a remote Jupyter server

You can offload intensive computation in a Jupyter Notebook to other computers by connecting to a remote Jupyter server. Once connected, code cells run on the remote server rather than the local computer.

To connect to a remote Jupyter server:

1. Run the Jupyter: Specify local or remote Jupyter server for connections command from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)).

2. When prompted to Pick how to connect to Jupyter, select Existing: Specify the URI of an existing server.

3. When prompted to Enter the URI of a Jupyter server, provide the server's URI (hostname) with the authentication token included with a ?token= URL parameter. (If you start the server in the VS Code terminal with an authentication token enabled, the URL with the token typically appears in the terminal output from where you can copy it.) Alternatively, you can specify a username and password after providing the URI.

Note: For added security, Microsoft recommends configuring your Jupyter server with security precautions such as SSL and token support. This helps ensure that requests sent to the Jupyter server are authenticated and connections to the remoter server are encrypted. For guidance about securing a notebook server, see the Jupyter docs.

Working with Markdown files in Visual Studio Code is simple, straightforward, and fun. Mac os x jaguar download. Besides VS Code's basic editing, there are a number of Markdown specific features that will help you be more productive.

Markdown extensions

In addition to the functionality VS Code provides out of the box, you can install an extension for greater functionality.

Tip: 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.

Markdown preview

VS Code supports Markdown files out of the box. You just start writing Markdown text, save the file with the .md extension and then you can toggle the visualization of the editor between the code and the preview of the Markdown file; obviously, you can also open an existing Markdown file and start working with it. To switch between views, press ⇧⌘V (Windows, Linux Ctrl+Shift+V) in the editor. You can view the preview side-by-side (⌘K V (Windows, Linux Ctrl+K V)) with the file you are editing and see changes reflected in real-time as you edit.

Here is an example with a very simple file.

Tip: You can also right-click on the editor Tab and select Open Preview (⇧⌘V (Windows, Linux Ctrl+Shift+V)) or use the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)) to run the Markdown: Open Preview to the Side command (⌘K V (Windows, Linux Ctrl+K V)).

Dynamic previews and preview locking

By default, Markdown previews automatically update to preview the currently active Markdown file:

You can lock a Markdown preview using the Markdown: Toggle Preview Locking command to keep it locked to its current Markdown document. Locked previews are indicated by [Preview] in the title:

Editor and preview synchronization

VS Code automatically synchronizes the Markdown editor and the preview panes. Scroll the Markdown preview and the editor is scrolled to match the preview's viewport. Scroll the Markdown editor and the preview is scrolled to match its viewport:

You can disable scroll synchronization using the markdown.preview.scrollPreviewWithEditor and markdown.preview.scrollEditorWithPreviewsettings.

The currently selected line in the editor is indicated in the Markdown preview by a light gray bar in the left margin:

Additionally, double clicking an element in the Markdown preview will automatically open the editor for the file and scroll to the line nearest the clicked element.

Outline view

The Outline view is a separate section in the bottom of the File Explorer. When expanded, it will show the symbol tree of the currently active editor. For Markdown files, the symbol tree is the Markdown file's header hierarchy.

The Outline view is a great way to review your document's header structure and outline.

Extending the Markdown preview

Extensions can contribute custom styles and scripts to the Markdown preview to change its appearance and add new functionality. Here's a set of example extensions that customize the preview:

Using your own CSS

You can also use your own CSS in the Markdown preview with the 'markdown.styles': []setting. This lists URLs for style sheets to load in the Markdown preview. These stylesheets can either be https URLs, or relative paths to local files in the current workspace.

For example, to load a stylesheet called Style.css at the root of your current workspace, use File > Preferences > Settings to bring up the workspace settings.json file and make this update:

Keep trailing whitespace in order to create line breaks

To create hard line breaks, Markdown requires two or more spaces at the end of a line. Depending on your user or workspace settings, VS Code may be configured to remove trailing whitespace. In order to keep trailing whitespace in Markdown files only, you can add these lines to your settings.json:

Markdown preview security

For security reasons, VS Code restricts the content displayed in the Markdown preview. This includes disabling script execution and only allowing resources to be loaded over https.

When the Markdown preview blocks content on a page, an alert popup is shown in the top right corner of the preview window:

You can change what content is allowed in the Markdown preview by clicking on this popup or running the Markdown: Change preview security settings command in any Markdown file:

The Markdown preview security settings apply to all files in the workspace.

Here are the details about each of these security levels:

Strict

This is the default setting. Only loads trusted content and disables script execution. Blocks http images.

It is strongly recommended that you keep Strict security enabled unless you have a very good reason to change it AND you trust all markdown files in the workspace.

Allow insecure content

Keeps scripts disabled but allows content to be loaded over http.

Disable

Vscode Markdown Syntax

Disables additional security in the preview window. This allows script execution and also allows content to be loaded over http.

Snippets for Markdown

There are several built-in Markdown snippets included in VS Code - press ⌃Space (Windows, Linux Ctrl+Space) (Trigger Suggest) and you get a context specific list of suggestions.

Tip: You can add in your own User Defined Snippets for Markdown. Take a look at User Defined Snippets to find out how.

Compiling Markdown into HTML

VS Code integrates with Markdown compilers through the integrated task runner. We can use this to compile .md files into .html files. Let's walk through compiling a simple Markdown document.

Step 1: Install a Markdown compiler

For this walkthrough, we use the popular Node.js module, markdown-it.

Note: There are many Markdown compilers to choose from beyond markdown-it. Pick the one that best suits your needs and environment.

VScode: Word Wrap For Markdown Not Working - Stack Overflow

Step 2: Create a simple MD file

Open VS Code on an empty folder and create a sample.md file.

Note: You can open a folder with VS Code by either selecting the folder with File > Open Folder or navigating to the folder and typing 'code .' at the command line.

Place the following source code in that file:

Step 3: Create tasks.json

The next step is to set up the task configuration file tasks.json. To do this, run Terminal > Configure Tasks and click Create tasks.json file from templates. VS Code then presents a list of possible tasks.json templates to choose from. Select Others since we want to run an external command.

This generates a tasks.json file in your workspace .vscode folder with the following content:

To use markdown-it to compile the Markdown file, change the contents as follows:

Tip: While the sample is there to help with common configuration settings, IntelliSense is available for the tasks.json file as well to help you along. Use ⌃Space (Windows, Linux Ctrl+Space) to see the available settings.

Step 4: Run the Build Task

Since in more complex environments there can be more than one build task we prompt you to pick the task to execute after pressing ⇧⌘B (Windows, Linux Ctrl+Shift+B) (Run Build Task). In addition, we allow you to scan the output for compile problems. Since we only want to convert the Markdown file to HTML select Never scan the build output from the presented list.

At this point, you should see an additional file show up in the file list sample.html.

If you want to make the Compile Markdown task the default build task to run execute Configure Default Build Task from the global Terminal menu and select Compile Markdown from the presented list. The final tasks.json file will then look like this:

GitHub - Svsool/vscode-memo: Markdown Knowledge Base With ..

Automating Markdown compilation

Let's take things a little further and automate Markdown compilation with VS Code. We can do so with the same task runner integration as before, but with a few modifications.

Step 1: Install Gulp and some plug-ins

We use Gulp to create a task that automates Markdown compilation. We also use the gulp-markdown plug-in to make things a little easier.

We need to install gulp both globally (-g switch) and locally:

Note: gulp-markdown-it is a Gulp plug-in for the markdown-it module we were using before. There are many other Gulp Markdown plug-ins you can use, as well as plug-ins for Grunt.

You can test that your gulp installation was successful by typing gulp -v. You should see a version displayed for both the global (CLI) and local installations.

Step 2: Create a simple Gulp task

Open VS Code on the same folder from before (contains sample.md and tasks.json under the .vscode folder), and create gulpfile.js at the root.

Place the following source code in that file:

What is happening here?

1. We are watching for changes to any Markdown file in our workspace, i.e. the current folder open in VS Code.
2. We take the set of Markdown files that have changed, and run them through our Markdown compiler, i.e. gulp-markdown-it.
3. We now have a set of HTML files, each named respectively after their original Markdown file. We then put these files in the same directory.

Step 3: Run the gulp default Task

To complete the tasks integration with VS Code, we will need to modify the task configuration from before to run the default Gulp task we just created. You can either delete the tasks.json file or empty it only keeping the 'version': '2.0.0' property. Now execute Run Task from the global Terminal menu. Observe that you are presented with a picker listing the tasks defined in the gulp file. Select gulp: default to start the task. We allow you to scan the output for compile problems. Since we only want to convert the Markdown file to HTML select Never scan the build output from the presented list. At this point, if you create and/or modify other Markdown files, you see the respective HTML files generated and/or changes reflected on save. You can also enable Auto Save to make things even more streamlined.

If you want to make the gulp: default task the default build task executed when pressing ⇧⌘B (Windows, Linux Ctrl+Shift+B) run Configure Default Build Task from the global Terminal menu and select gulp: default from the presented list. The final tasks.json file will then look like this:

Step 4: Terminate the gulp default Task

The gulp: default task runs in the background and watches for file changes to Markdown files. If you want to stop the task, you can use the Terminate Task from the global Terminal menu.

Next steps

Read on to find out about:

• CSS, SCSS, and Less - Want to edit your CSS? VS Code has great support for CSS, SCSS, and Less editing.

Common questions

Is there spell checking?

Not installed with VS Code but there are spell checking extensions. Check the VS Code Marketplace to look for useful extensions to help with your workflow.

Does VS Code support GitHub Flavored Markdown?

No, VS Code targets the CommonMark Markdown specification using the markdown-it library. GitHub is moving toward the CommonMark specification which you can read about in this update.

In the walkthrough above, I didn't find the Configure Task command in the Command Palette?

How To Include Image As Markdown In Visual Studio Code ..

You may have opened a file in VS Code rather than a folder. You can open a folder by either selecting the folder with File > Open Folder or navigating to the folder and typing 'code .' at the command line.