# Using interactive sessions with Microsoft Visual Studio Code
<a name="interactive-sessions-vscode"></a>

 **Prerequisites** 
+  Install AWS Glue interactive sessions and verify it works with Jupyter Notebook. 
+  Download and install Visual Studio Code with Jupyter. For details, see [Jupyter Notebook in VS Code](https://code.visualstudio.com/docs/datascience/jupyter-notebooks). 

**To get started with interactive sessions with VSCode**

1.  Disable Jupyter AutoStart in VS Code. 

    In Visual Studio Code, Jupyter kernels will auto-start which will prevent your magics from taking effect as the session will already be started. To disable **Auto Start** on Windows, go to **File** > **Preferences** > **Extensions** > **Jupyter** > right-click on Jupyter then choose **Extension Settings**. 

    On MacOS, go to **Code** > **Settings** > **Extensions** > **Jupyter** > right-click on Jupyter then choose **Extension Settings**. 

    Scroll down until you see **Jupyter: Disable Jupyter Auto Start**. Check the box "When true, disables Jupyter from being automatically started for you. You must instead run a cell to start Jupyter."   
![\[The screenshot shows the checkbox enabled in for the Jupyter Extension in VS Code.\]](http://docs.aws.amazon.com/glue/latest/dg/images/IS_vscode_step1.png)

1.  Go to File > New File > Save to save this file with name of your choice as an `.ipynb` extension or select **jupyter** under **select a language** and save the file.   
![\[The screenshot shows the file being saved with a new name.\]](http://docs.aws.amazon.com/glue/latest/dg/images/IS_vscode_step2.gif)

1.  Double-click on the file. The Jupyter shell will display and a notebook will be opened.   
![\[The screenshot shows the open notebook.\]](http://docs.aws.amazon.com/glue/latest/dg/images/IS_vscode_step3.png)

1.  On Windows, when you first create a file, by default no kernel is selected. Click on **Select Kernel** and a list of available kernels is displayed. Choose **Glue PySpark**. 

    On MacOS, If you do not see the **Glue PySpark** kernel, try the following steps: 

   1. Run a local Jupyter session to obtain the URL. 

      For example, run the following command to launch Jupyter Notebook.

      ```
      jupyter notebook
      ```

      When the notebook first runs, you will see a URL that looks like `http://localhost:8888/?token=3398XXXXXXXXXXXXXXXX`.

      Copy the URL.

   1. In VS Code, click the current kernel, then **Select Another Kernel...**, then select **Existing Jupyter Server...**. Paste the URL you copied from the step above.

      If you receive an error message, see the [ VS Code Jupyter wiki ](https://github.com/microsoft/vscode-jupyter/wiki/Connecting-to-a-remote-Jupyter-server-from-vscode.dev). 

   1. If successful, this will set the kernel to **Glue PySpark**.  
![\[The screenshot shows the Select Kernel button highlighted.\]](http://docs.aws.amazon.com/glue/latest/dg/images/IS_vscode_step4a.png)

    Choose the **Glue PySpark** or **Glue Spark** kernel (for Python and Scala respectively).   
![\[The screenshot shows the selection for AWS Glue PySpark.\]](http://docs.aws.amazon.com/glue/latest/dg/images/IS_vscode_step4b.png)

    If you don't see **AWS Glue PySpark** and **AWS Glue Spark** kernels in the drop-down list, please ensure you have installed the AWS Glue kernel in the step above, or that your `python.defaultInterpreterPath` setting in Visual Studio Code is correct. For more information, see [ python.defaultInterpreterPath setting description ](https://github.com/microsoft/vscode-python/wiki/Setting-descriptions#pythondefaultinterpreterpath). 

1.  Create an AWS Glue Interactive Session. Proceed to create a session in the same manner as you did in Jupyter Notebook. Specify any magics at the top of your first cell and run a statement of code.