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System and JupyterHub server Python versions

As of January 2024, the (single) Python kernel version in all JupyterHub servers is Python 3.9, and recent versions of many popular Python pacakges are available (e.g. pandas, numpy, scipy, etc.)

Warning

Users cannot install additional packages in JupyterHub, and any Python packages installed by the user on the command line are not available in the JupyterHub server environment.

This is because JupyterHub server packages are installed in a global anaconda environment that is only accessible to admin users. Thus JupyterHub packages must be installed by us, so contact us (rctf-support@utexas.edu) if there is a package you'd like to see installed.

There are three There are two versions of Python available on the command line ("system" Python) on BRCF compute servers. In Ubuntu 20.04, these versions and the command to invoke them are:

  • 2.7 - python, python2
  • 3.8 - python3, python3.8
  • 3.9 - python3.9

(Note that the Python 3.x python version on Ubuntu 18.04 was 3.6.)8 is the default version when you invoke python3. To use Python 3.9, call python3.9.

There are corresponding versions of pip that should be used to install 3rd party packages:

  • for Python 2 - pip, pip2
  • for Python 3.8 - pip3, pip3.8
  • for Python 3.9 - pip3.9

Understanding Python add-on packages

Globally installed Python packages are available to any Python command-line environment of a compatible version. To see which Python packages are installed, along with their versions, use pip2 listpip3.8 list or pip3.9 list. Similarly, user-installed packages can be viewed using pip2 list --user, pip3.8 list --user or pip3 list user.

In addition to the many Python packages available in all the versions, users can their own install command-line-accessible packages using an appropriate version of pip install with the --user option. These user-installed packages are installed by default in the user's Home directory, in a directory with a name like ~/.local/lib/pythonN.N/site-packages, where N.N is the Python version.Unlike the R environment, where user-installed packages are automatically visible to the RStudio Server running a compatible R version (see R and RStudio Server R versions), user-installed Python packages

Warning

Users cannot install additional packages in JupyterHub, and any Python packages installed by the user on the command line are not available in the JupyterHub server environment.

This is because JupyterHub server packages are installed in a global anaconda environment that is only accessible to admin users. Thus JupyterHub packages must be installed by us, so contact us (rctf-support@utexas.edu) if there is a package you'd like to see installed. (This is different from the R environment, where user-installed packages are automatically visible to the RStudio Server running a compatible R version. See R and RStudio Server R versions.)

Local/Global package installation conflicts

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To troubleshoot this possibility, move your local Python installation area out of the way. For example, for Python 3.89:

Code Block
mv ~/.local/lib/python3.89 ~/.local/lib/python3.89.bak

If this produces a different error indicating that one or more locally installed packages are missing, the user can re-install them then see if the problem is resolved. Check the now-named  ~/.local/lib/pythonN.N.bak/site-packages directory, where N.N is the Python version being used to see the packages that were locally installed previously. Even if this resolves the immediate issue, the user may later find that they need to re-install other packages that were previously installed locally. 

Finally, if renaming the local Python installation directory does not resolve the issue, it may be an issue with the globally installed packages, so Contact Uscontact us at rctf-support@utexas.edu.

Troubleshooting

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JupyterHub server issues

In addition to the Local/Global package conflict issue described above, other issues Issues can arise involving JupyterHub server (or less commonly, command-line Python). These browser and disk quota issues are similar to those seen for R, so see Troubleshooting R/RStudio server issues. If all else fails, submit a help request to our rctf-support@utexas.edu support email.

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