Setting up a user environment¶

Please notice that since 2024, the University of Vienna allows using anaconda products (anaconda and miniconda distributions) only for teaching, no research. Please use alternatives: miniforge, micromamba (av. on all department servers), mamba or pip (av. on all department servers)

Topics

• Setup a user environment using micromamba
  • Add user environment to notebook kernels
  • Activate your environment
• Setup a user environment using venv
• Include PATH in Notebook Kernel

Select the default kernel that should have micromamba present, otherwise add micromamba to the file load_modules_into_jupyter.conf or run echo micromamba > ~/load_modules_into_jupyter.conf in a terminal or in a code cell (prepending !).

updated: 2025.06

In [1]:

!module list

!module list

Currently Loaded Modulefiles:
 1) micromamba/2.2.0  

Using conda¶

In [2]:

!micromamba info

!micromamba info

       libmamba version : 2.2.0
     micromamba version : 2.2.0
           curl version : libcurl/8.14.1 OpenSSL/3.5.0 zlib/1.3.1 zstd/1.5.7 libssh2/1.11.1 nghttp2/1.64.0
     libarchive version : libarchive 3.7.7 zlib/1.3.1 bz2lib/1.0.8 libzstd/1.5.7
       envs directories : /jetfs/home/yourusername/micromamba/envs
          package cache : /jetfs/home/yourusername/micromamba/pkgs
                          /jetfs/home/yourusername/.mamba/pkgs
            environment : base
           env location : /jetfs/home/yourusername/micromamba
      user config files : /jetfs/home/yourusername/.mambarc
 populated config files : /jetfs/home/yourusername/.condarc
       virtual packages : __unix=0=0
                          __linux=4.18.0=0
                          __glibc=2.28=0
                          __archspec=1=x86_64_v4
               channels : https://conda.anaconda.org/conda-forge/linux-64
                          https://conda.anaconda.org/conda-forge/noarch
       base environment : /jetfs/home/yourusername/micromamba
               platform : linux-64

In [3]:

# Create a environment with conda
# use -q quiet
# -y yes to all questions
# -c [] use conda-forge FLOSS channel
# -n [] name of the environment
# add packages, e.g.: python at version 3.12 numpy an ipykernel (required for jupyter integration)
!micromamba create -q -y -c conda-forge -n myenv python=3.12 numpy ipykernel

# Create a environment with conda # use -q quiet # -y yes to all questions # -c [] use conda-forge FLOSS channel # -n [] name of the environment # add packages, e.g.: python at version 3.12 numpy an ipykernel (required for jupyter integration) !micromamba create -q -y -c conda-forge -n myenv python=3.12 numpy ipykernel

In [4]:

# show available environment
!micromamba env list

# show available environment !micromamba env list

  Name    Active  Path                                                                                                            
────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────────
  base    *       /jetfs/home/yourusername/micromamba                                                                                
  modern          /jetfs/home/yourusername/micromamba/envs/modern                                                                    
  myenv           /jetfs/home/yourusername/micromamba/envs/myenv                                                                     

Add the new environment to your active kernels¶

This way you can choose the kernel from the Jupyterlab launcher.

In [5]:

!~/micromamba/envs/myenv/bin/python -m ipykernel install --user --name MYENV --display-name "Py3.12"

!~/micromamba/envs/myenv/bin/python -m ipykernel install --user --name MYENV --display-name "Py3.12"

Installed kernelspec MYENV in /jetfs/home/yourusername/.local/share/jupyter/kernels/myenv

Activate your environment¶

Micromamba environments need to be added to the PATH to work well. So there is an activate function for these environments.

You just need to run this once

# initialize bash shell
$ micromamba shell init -s bash
Running `shell init`, which:
 - modifies RC file: "/jetfs/home/yourusername/.bashrc"
 - generates config for root prefix: "/jetfs/home/yourusername/micromamba"
 - sets mamba executable to: "/jetfs/manual/micromamba/2.2.0/bin/micromamba"
The following has been added in your "/jetfs/home/yourusername/.bashrc" file

# >>> mamba initialize >>>
# !! Contents within this block are managed by 'micromamba shell init' !!
export MAMBA_EXE='/jetfs/manual/micromamba/2.2.0/bin/micromamba';
export MAMBA_ROOT_PREFIX='/jetfs/home/yourusername/micromamba';
__mamba_setup="$("$MAMBA_EXE" shell hook --shell bash --root-prefix "$MAMBA_ROOT_PREFIX" 2> /dev/null)"
if [ $? -eq 0 ]; then
    eval "$__mamba_setup"
else
    alias micromamba="$MAMBA_EXE"  # Fallback on help from micromamba activate
fi
unset __mamba_setup
# <<< mamba initialize <<<

will edit your .bashrc. After some time you might have to do this again, when the micromamba version changed a lot (e.g.: micromamba shell reinit -s bash)

In [6]:

# List available Kernels
!jupyter kernelspec list

# List available Kernels !jupyter kernelspec list

Available kernels:
  myenv                                      /jetfs/home/yourusername/.local/share/jupyter/kernels/myenv
  rttovv13.2                                 /jetfs/home/yourusername/.local/share/jupyter/kernels/rttovv13.2
  enstoolsv2021.11                           /jetfs/jupyterhub/alpha/share/jupyter/kernels/enstoolsv2021.11
  ir                                         /jetfs/jupyterhub/alpha/share/jupyter/kernels/ir
  modelling                                  /jetfs/jupyterhub/alpha/share/jupyter/kernels/modelling
  python3                                    /jetfs/jupyterhub/alpha/share/jupyter/kernels/python3

Using virtual environment¶

In [6]:

# Setup a virtual Environment for your Python in the directoy: myfancyenv
!python -m venv myfancyenv 

# Setup a virtual Environment for your Python in the directoy: myfancyenv !python -m venv myfancyenv

In [7]:

# Creates a directory with new environment
!ls myfancyenv/

# Creates a directory with new environment !ls myfancyenv/

bin  include  lib  lib64  pyvenv.cfg

In [8]:

# Install some package into that environment
# important is ipykernel to use it within jupyterlab/notebook
!./myfancyenv/bin/pip -q install numpy scipy pandas ipykernel

# Install some package into that environment # important is ipykernel to use it within jupyterlab/notebook !./myfancyenv/bin/pip -q install numpy scipy pandas ipykernel

WARNING: You are using pip version 19.2.3, however version 20.2.4 is available.
You should consider upgrading via the 'pip install --upgrade pip' command.

In [9]:

# Allow this environment to be available on the LAUNCHERS (+) sign on the left
!./myfancyenv/bin/python -m ipykernel install --user --name fancy --display-name "My Python"

# Allow this environment to be available on the LAUNCHERS (+) sign on the left !./myfancyenv/bin/python -m ipykernel install --user --name fancy --display-name "My Python"

Installed kernelspec fancy in /jetfs/home/yourusername/.local/share/jupyter/kernels/fancy

Wait a bit and the new python environment should be available on your launchers.

In [10]:

!jupyter kernelspec list

!jupyter kernelspec list

Available kernels:
  fancy      /jetfs/home/yourusername/.local/share/jupyter/kernels/fancy
  myenv      /jetfs/home/yourusername/.local/share/jupyter/kernels/myenv

Add PATH to your user environment¶

In order to get full access to all tools installed in your local environment, add it to your PATH.

Open your kernel.json file located /jetfs/home/yourusername/.local/share/jupyter/kernels/myenv/kernel.json:

{
    "argv": [
        "/jetfs/home/yourusername/micromamba/envs/myenv/bin/python",
        "-m",
        "ipykernel_launcher",
        "-f",
        "{connection_file}"
    ],
    "env" : {
        "PATH": "/jetfs/home/yourusername/.conda/envs/myenv/bin/:${PATH}",
        "LD_LIBRARY_PATH": "/jetfs/home/yourusername/micromamba/envs/myenv/lib:${LD_LIBRARY_PATH}"
    },
    "display_name": "MYENV",
    "language": "python"
}

Finished¶