Test Python Environment Kernel Picker

[DonJayamanne]

Testing the Python Environment Kernel Picker

Refs: #11904

• anyOS @aiday-mar
• WSL @Tyriar
• Windows @devinvalenciano

Complexity: 3

Authors: @DonJayamanne

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Requirements

• Have a python environments installed
• Have Conda installed

Setup pre-requisites

• Familiar with setting up of Conda or Virtual environments
• Create at least 5-10 Virtual environments in the workspace folder (optionally create 5-10 conda environments, see below)
• Create at least 5-10 conda environments using the following command
  • First install conda, for someone new to conda, please install miniconda from here https://docs.conda.io/en/latest/miniconda.html
  • Open a terminal and ensure conda has been activated and setup, see instructions here https://conda.io/projects/conda/en/stable/user-guide/install/download.html#cryptographic-hash-verification
  • Create a few conda envioronments with python in it using the command conda create -n <EnvName> python=3
    For each new conda env, ensure the value <EnvName> is different

Steps

• Open VS Code Insiders
• Open a notebook
• from the command palette select the command Jupyter: Show Output
• Verify the user belongs to the experiment group FastKernelPicker
  To verify this, look for the line FastkernelPicker in the output (see below as an example)

Visual Studio Code - Insiders (1.80.0-insider, undefined, desktop)
Jupyter Extension Version: 2023.6.100.
Python Extension Version: 2023.11.11741005.
Platform: darwin (arm64).
Workspace folder ~/Desktop/development/vsc/vscode-jupyter, Home = /Users/donjayamanne
17:07:17.470 [info] User belongs to experiment group 'FastKernelPicker'

• Open the kernel picker top right hand corner
• Click Select Another Kernel -> Python Environments
• Verify the Kernel picker is displayed immediately and at least one python environments is displayed immediately
• From the command palette select the command Python: Select Interpreter
• Verify the list of Python environments displayed in the Kernel picker is displayed as quickly as the items displayed in the Python Interpreter picker (there should not be any noticeable difference)