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Miniconda3 Homepage

Available Modules

module load Miniconda3/23.10.0-1

module load Miniconda3/22.11.1-1

module load Miniconda3/23.10.0-1

The Miniconda3 environment module provides the Conda package and environment manager. Conda lets you install packages and their dependencies in dedicated environment, giving you more freedom to install software yourself at the expense of possibly less optimized packages and no curation by the NeSI team.


  • If you want a more reproducible and isolated environment, we recommend using the Singularity containers.
  • If you only need access to Python and standard numerical libraries (numpy, scipy, matplotlib, etc.), you can use the Python environment module.

Māui Ancillary Nodes

On Māui Ancillary Nodes, you can also use the Anaconda3 module, which provides a default environment pre-installed with a set of numerical libraries (numpy, scipy, matplotlib, etc.).

Module loading and conda environments isolation

When using the Miniconda3 module, we recommend using the following snippet to ensure that your conda environments can be activated and are isolated as possible from the rest of the system:

module purge && module load Miniconda3
source $(conda info --base)/etc/profile.d/

Here are the explanations for each line of this snippet:

  • module purge && module load Miniconda3 ensures that no other environment module can affect your conda environments. In particular, the Python environment module change the PYTHONPATH variable, breaking the isolation of the conda environments. If you need other environment modules, make sure to load them after this line.
  • source $(conda info --base)/etc/profile.d/ ensures that you can use the conda activate command.
  • export PYTHONNOUSERSITE=1 makes sure that local packages installed in your home folder ~/.local/lib/pythonX.Y/site-packages/ (where X.Y is the Python version, e.g. 3.8) by pip install --user are excluded from your conda environments.


We strongly recommend against using conda init. It inserts a snippet in your ~/.bashrc file that will freeze the version of conda used, bypassing the environment module system.

Māui Ancillary Nodes

On Māui Ancillary Nodes, you need to (re)load the NeSI module after using module purge:

module purge && module load NeSI Miniconda3
source $(conda info --base)/etc/profile.d/

Prevent conda from using /home storage

Conda environments and the conda packages cache can take a lot of storage space. By default, Conda use /home storage, which is restricted to 20GB on NeSI. Here are some techniques to avoid running out of space when using Conda.

First, we recommend that you move the cache folder used for downloaded packages on the nobackup folder of your project:

conda config --add pkgs_dirs /nesi/nobackup/<project_code>/$USER/conda_pkgs

where <project_code> should be replace with your project code. This setting is saved in your ~/.condarc configuration file.


Your package cache will be subject to the nobackup autodelete process (details available in the Nobackup autodelete support page). The package cache folder is for temporary storage so it is safe if files within the cache folder are removed.

Next, we recommend using the -p or --prefix options when creating new conda environments, instead of -n or --name options. Using -p or --prefix, you can specify the conda environment folder location, ideally in your project folder. For example:

conda create --prefix /nesi/project/<project_code>/my_conda_env python=3.8

Then use the path of the conda environment to activate it:

conda activate /nesi/project/<project_code>/my_conda_env

Note that -p and --prefix options can also be used when creating an environment from an environment.yml file:

conda env create -f environment.yml -p /nesi/project/<project_code>/my_conda_env

Reduce prompt prefix

By default, when activating a conda environment created with -p or --prefix, the entire path of the environment is be added to the prompt. To remove this long prefix in your shell prompt, use the following configuration:

conda config --set env_prompt '({name})'

Faster solver mamba (experimental feature)

If you are using the module Miniconda3/22.11.1-1, you can accelerate conda environments creation and package installation using the new libmamba solver. To use it, append the option --solver=libmamba to your command.

For example, to create an environment from an environment.yml file, use:

conda env create --solver=libmamba -f environment.yml -p venv

or to install a package in an activate environment, use:

conda install --solver=libmamba CONDA_PACKAGE

where CONDA_PACKAGE is the package of interest.