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The most common cause of Jupyter stopping working is conflicts with user-installed python packages.The ASU Supercomputers offers a python-environment manager, mamba, which can help alleviate these issues by keeping python packages properly contained.

This page describes the inner-workings of installing packages via various python methods and the impacts it may have.

Info

The most common cause of Jupyter stopping working with “Bad State” is conflicts with user-installed python packages. See farther below for the fix.

Differences between installation methods

Environment Activated?

Installer

Command

Default Install Location

Note

No mamba/no env

pip

pip install package_name

/usr/local/lib/pythonX.X/site-packages

This location is not user-writable, so python may default to installing to your $HOME. Avoid this route.

pip (with --user)

pip (with --user)

pip install --user package_name

~/.local/lib/pythonX.X/site-packages

This location is user-writable, but installs packages in a location Jupyter Notebook/Lab uses on the Web Portal. Avoid this route.

source activate YYYY

mamba

mamba install package_name

~/.conda/envs/<envname>/lib/pythonX.X/site-packages

This location is user-writable and will be installed properly via mambas safeguards. PREFERRED route.

source activate YYYY

pip

pip install package_name

~/.conda/envs/<envname>/lib/pythonX.X/site-packages

This location is user-writable and will be installed properly via mambas safeguards. This is an ACCEPTABLE route for packages that cannot be installed via mamba.

source activate YYYY

pip (with --user)

pip install --user package_name

~/.local/lib/pythonX.X/site-packages

This location is user-writable, but installs packages in a location Jupyter Notebook/Lab uses on the Web Portal. Avoid this route.

MAIN TAKEAWAYS:

Info
  1. Prefer mamba install everywhere, where possible.

  2. Never use pip --user install

  3. Only use pip install after source activating your environment.

Fixing Jupyter Notebook in a “Bad State”

Fixing Jupyter Notebook that is having trouble starting or reporting “Bad State” can be done by removing (or renaming) the packages located in your ~/.local/lib directory.

By removing files that are universally installed to your $HOME directory, both Jupyter and conda environments will no longer have access to these files.

For packages installed here, they should be installed directly into the environment using the guidance above.

Code Block
[asurite@login01:~]$ cd ~/.local/lib/
[asurite@login01:~/.local/lib]$ ll
total 80
drwxr-x--- 3 asurite grp_usergrp 31 Jan 13 12:20 python3.11/
[asurite@login01:~/.local/lib]$ mv python3.11/ python3.11.old
[asurite@login01:~/.local/lib]$ ll
total 80
drwxr-x--- 3 asurite grp_usergrp 31 Jan 13 12:20 python3.11.old/

  1. Go to the $HOME package installation dir: cd ~/.local/lib/

  2. Identify any python packages directory--you may see multiple versions here, e.g., python3.11 or python2.7

  3. Rename the directories to have a new suffix, making them not get loaded automatically, e.g., .old or .bak.

  4. Install these packages to a mamba environment using the table above.

Technical details

Background about Python Libraries Locations

When running python , python2, or python3, additional libraries are identified and python attempts to load these into the current session from /home/<asurite>/.local/lib/python<version>/site-libraries.

...

However, this default behavior is potentially disruptive when using Jupyter, which fully contains all the necessary packages in a curated, version-locked manner.

Background about Mamba-contained libraries

When using mamba create and mamba install , libraries are placed in to /home/<asurite>/.conda/envs/<envname>. This means you can have multiple environments that are completely independent of eachother which maybe both include the same packages, but do not interfere with eachother and can have different (and potentially conflicting) versions.

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