Investigate a method to create or suggest a virtual environment with `ipykernel` + needed packages for a given notebook

[greazer]

[IanMatthewHuff]

Here is a summary of the customer flow from the PPT slides on getting started env setup.

• Trigger: run code cell without selecting a kernel, select kernel -> create new​
• Ask: Select which Python version you want to use or install​
• Ask: Name your new conda environment (defaulting to “vscode-default”)​
• Create a conda environment from ^ and activate it​
• Look for an environment.yml or requirements.txt in the project​
• Ask: Install packages from (which, if multiple) existing environment definition file?​
• Install packages from ^​
• Select the created env as kernel for the notebook​
• While all this is happening, open “output”

[IanMatthewHuff]

Options (in progress):

• Trigger - When do we suggest this new kernel?
  • User attempts to run code without selecting a kernel
  • User attempts to run code against a global python install
  • User attempts to run code in a new workspace where code has not been run before
  • Instead of running code, if the user has a global python selected for a controller
• Entry Point - What is the UI affordance for creating this new kernel?
  • In the kernel controller selection dialog have a "create new kernel" option
  • When user runs without a kernel selected, instead of popping up kernel selection first offer to create new kernel
  • Lightbulb from unfulfilled imports in an open notebook document
• Python Selection - How to select the python to create the environment with?
  • Quick pick python interpreters (must have one available that we know how to install from, Conda / Pip)
  • Install Python for user
  • Ship micromamba, use that to set up env
• Installing The Kernel - Where to make this new kernel accessible
  • Create a .venv for the kernel relative to the local workspace, install kernel there
  • Install the kernel into the Jupyter global kernel location
• Post Installation - How do we handle the kernel after installation?
  • Nothing special
  • Use as default kernel for the workspace that created it
  • Use as suggested kernel globally when we are not sure

[IanMatthewHuff]

MVP Plan (in progress):

What can we hash out in a few days of work that move us forward here and answer some questions.

Trigger - None
Entry Point - Command Palette command
Python Selection - Pick from Python Extension interpreters
Installing the Kernel - Conda / Pip to create environment. Install ipykernel into env.
Post Installation - Select created kernel

[greazer]

Consider adding a revisitation of whether we install ipykernel without asking to the work here.

One idea that is an alternative to just installing would be to create a cell within the notebook that installs ipykernel for the user. That way they can see what needs to happen and allow it or not. Of course, this would need to be some sort of special case cell. The point is that we have been concerned that users won't like the idea of just having an environment get updated with a package they may not understand the need for and rather than prompting them, is there a more subtle way to ensure the right thing AND right education happens.