Open the kernel picker by clicking on Select Kernel on the upper right-hand corner of your notebook, select Connect to Codespace. Go to the Command Palette ( ⇧⌘P (Windows, Linux Ctrl+Shift+P)), select Codespaces: Sign In and follow the steps to sign into Codespaces. Also ensure that the Jupyter extension is also installed. Note: If you're on VS Code for the Web ( v or v), this extension is already installed for you. The Connect to Codespace category contains a special type of Jupyter server where you can use remote Jupyter servers powered by GitHub Codespaces, a cloud resource that you get up to 60 hours free each month. Running the Notebook: Select Notebook Kernel command.You can create a new session from the server's kernelspec by: Once connected, all active Jupyter sessions will appear on this list. Set the notebook to listen on all IPs ( -NotebookApp.ip='0.0.0.0').Allow all origins (for example -NotebookApp.allow_origin='*') to allow your servers to be accessed externally.When you're starting your remote server, be sure to: Note: In the previous versions of VS Code (version :/?token= and paste it in the Enter the URL of the running Jupyter server option to connect to the remote server and execute code against your notebook using that server. Once you open the Kernel Picker, VS Code shows the most recently used (MRU) kernel(s): You can open the kernel picker by clicking on Select Kernel on the upper right-hand corner of your notebook or through the Command Palette with the Notebook: Select Notebook Kernel command. The Visual Studio Code notebooks' kernel picker helps you to pick specific kernels for your notebooks. Configure IntelliSense for cross-compiling.
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