Skip to main content

Using Visual Studio (VS) Code

Using VS Code as your development environment

VS Code can be used as an IDE (integrated development environment) which provides helpful tooling (including debugging) to assist developers in writing code. It also has many other functions which non-developers may also find useful such a text editing and markdown rendering.

Getting started

VS Code comes built-in with every installation of Nebari. To start, log in to Nebari and spin up a JupyterLab instance.

Next, bring up the New Launcher window by clicking the + in the top left of the screen. Now click on the VS Code logo on the Launcher window.

JupyterLab Launcher window with VS Code

You will now have been redirected to a new web browser page showing the VS Code platform. If you're starting VS Code for the first time, you'll see a Welcome Page with some helpful links and tips.

Feel free to explore!

VS Code Welcome screen

VS Code components

On the far left, you'll see the Activity Bar in black. Also, on the left is the Explorer. As you click on the items in the Activity Bar, the Explorer items will update.

Let's review some of the most useful features.

The Activity Bar components

The Activity Bar is where you'll go to switch between the main tools available in VS Code. Below is a brief overview of the icons on the Activity Bar (adding extensions may add additional icons to your menu).

IconNameDescription
VS Code hamburger buttonFile MenuLike every other file menu - create files, run files, edit preferences...
VS Code files buttonFile ExplorerView list of files, navigate folder structures
VS Code search buttonSearchSearch for words in the contents of files
VS Code source control buttonSource ControlSource Control Management (SCM) features (e.g. git)
VS Code debug buttonDebugRun code using the debugger
VS Code extensions buttonExtensionsAdd plugins to extend VS Code functionality

File editing

Now that we have that out of the way, let's explore!

We'll start by clicking on the File Explorer icon. The Explorer sidebar now is updated with our file system. In our case, this is our Nebari user root directory.

One of the first things you'll notice here is that there are a lot of files starting with the . character. This is particularly handy because JupyterLab hides these files in its Explorer view.

Let's click on a file we all have, .bashrc. This file was created by Nebari for us.

VS Code bashrc file

We now have an Editor window in which we can modify the file. The default VS Code preferences include an auto-save feature which will continually save the files as soon as you stop typing edits.

Adding extensions

Using the Activity Bar, navigate to the Extensions. The Explorer sidebar now shows lists of Extensions, grouped by those installed by your admin, those installed by you, and a list of "Popular" extensions you may want to try. Through this interface we can also search the Marketplace for a particular extension.

VS Code extensions list

The Python extension is at the top of the list in our example (rightly so!), but if you don't see it here, you can search for it.

If you click on the Python extension, you'll see additional information about this extension in the main window. This extension provides some extra tooling around Python. It will allow us to select a Python environment and run and debug code right inside of VS Code. Go ahead and click Install. It should only take a few seconds to install.

Now let's run some code!

Running Python code

In the Explorer pane, selected the New File icon:

VS Code select new file

You can name it anything you'd like, here we've named it example.py. The *.py extension let's VS Code know that it's a Python file, and you can set up some automatic linting tasks through Preferences if you'd like.

Add some sample code to your file:

VS Code new file contents

We also see the VS Code Terminal in the previous image. This can be opened with File -> Terminal -> New Terminal.

Before we run our file, we need to select what Conda environment it should run inside.

VS Code select conda env

Now we can run our code through the VS Code UI by selecting either Run Python File or Debug Python File in the top right.

VS Code run or debug env

We can see output in the terminal:

VS Code view output

As another alternative, we could run code directly from the terminal as well.

Conclusion

We've covered the basic setup and run some arbitrary code. If you're curious about more advanced features or have specific questions, you can always refer back to the VS Code Documentation.