Installing OGGM#


Did you know that you can try OGGM in your browser before installing it on your computer? Visit Try OGGM online for more information.

OGGM itself is a pure python package, but it has several dependencies which are not trivial to install. The instructions below provide all the required details and should work on Linux and Mac OS. See Installation troubleshooting if something goes wrong.

OGGM is fully tested with Python versions 3.9 to 3.11 on Linux. We do not test OGGM automatically on Mac OSX, but it should probably run fine there as well.


OGGM does not work on Windows. If you are using Windows 10, we recommend to install the free Windows subsystem for Linux and install and run OGGM from there.

For most users we recommend to install Python and the package dependencies with the conda package manager, in particular with mamba and conda-forge.


Here is a list of all dependencies of the OGGM model. If you want to use OGGM’s numerical models only (i.e. no GIS or preprocessing tools), refer to Install a minimal OGGM environment below.

Standard SciPy stack:
  • numpy

  • scipy

  • scikit-image

  • pillow

  • matplotlib

  • pandas

  • xarray

  • dask

  • joblib

Configuration file parsing tool:
  • configobj

  • netcdf4

  • pytables

GIS tools:
  • shapely

  • pyproj

  • rasterio

  • rioxarray

  • geopandas

  • pytest

  • pytest-mpl (for image tests only: OGGM fork required)

Other libraries:
  • progressbar2 (displays the download progress)

  • bottleneck (might speed up some xarray operations)

Install with conda (all platforms)#

This is the recommended way to install OGGM for most users.


If you are not familiar with Python and its way too many package management systems, you might find all of this quite confusing and overwhelming. Be patient, read the docs and stay hydrated.


You should have a recent version of the conda package manager. Our recommendation is to install mambaforge. If you are completely new to these things, check out this page which explains how to install mambaforge and this one for installing packages.

We recommend to use mamba over conda as an installation command. Mamba is a drop-in replacement for all conda commands. If you feel like it, install mamba in your conda environment (conda install -c conda-forge mamba) and replace all occurrences of conda with mamba in the instructions below.


Do not install mambaforge on top of an existing conda installation! See this issue for context. If you have conda installed and want to switch to mamba + conda-forge, follow the instructions on the respective platforms.

The simplest way: with an environment file#

Copy the content of the file below into a file called environment.yml on your system (alternatively, right-click -> “save as” on this link).

name: oggm_env
  - conda-forge
  - numpy
  - scipy
  - pandas
  - shapely
  - matplotlib
  - Pillow
  - netcdf4
  - scikit-image
  - configobj
  - xarray
  - pytest
  - dask
  - bottleneck
  - pyproj
  - cartopy
  - geopandas
  - rasterio
  - rioxarray
  - seaborn
  - pytables
  - salem
  - motionless
  - pip
  - pip:
    - joblib
    - progressbar2
    - oggm

From the folder where you saved the file, run mamba env create -f environment.yml.

This will create a new environment called oggm_env in your conda installation. For more information about conda environments, visit the conda documentation on the topic. Similarly, visit conda documentation on environment files for more information about how to create an environment from a yml file.

Don’t forget to Test OGGM before using it!

Install OGGM itself#

First, choose which version of OGGM you would like to install:

  • stable: this is the latest version officially released and has a fixed version number (e.g. v1.5.3).

  • dev: this is the development version. It might contain new features and bug fixes, but is also likely to continue to change until a new release is made. This is the recommended way if you want to use the latest changes to the code.

  • dev+code: this is the recommended way if you plan to contribute to the model, and/or if you want to use the most recent model updates.

‣ install the stable version:


If you installed OGGM with the environment file above, OGGM will be installed already in the latest stable version.

In your conda environment, use pip:

pip install oggm

‣ install the dev version:

For this to work you’ll need to have the git software installed on your system. In your conda environment, simply do:

pip install --upgrade git+

With this command you can also update an already installed OGGM version to the latest version.

‣ install the dev version + get access to the OGGM code:

For this to work you’ll need to have the git software installed on your system. Then, clone the latest repository version:

git clone

Then go to the project root directory:

cd oggm

And install OGGM in development mode (this is valid for both pip and conda environments):

pip install -e .


Installing OGGM in development mode means that subsequent changes to this code repository will be taken into account the next time you will import oggm. You can also update OGGM with a simple git pull from the root of the cloned repository.

Don’t forget to Test OGGM before using it!

Test OGGM#

You can test your OGGM installation by running the following command from anywhere (don’t forget to activate your environment first):

pytest.oggm  --disable-warnings

The tests should run for 5 to 10 minutes. If everything worked fine, you should see something like:

=================================== test session starts ====================================
platform linux -- Python 3.10.6, pytest-7.1.3, pluggy-1.0.0
Matplotlib: 3.5.3
Freetype: 2.12.1
rootdir: /home/mowglie/disk/Dropbox/HomeDocs/git/oggm-fork, configfile: pytest.ini
plugins: anyio-3.6.1, mpl-0.150.0
collected 373 items

disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/            [  1%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ..........s...s....s [  7%]
ss                                                                                   [  7%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ...                   [  8%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ...................... [ 14%]       [ 35%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ [ 40%]
ss.sss.sss.s                                                                         [ 43%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ..................s... [ 49%]                     [ 67%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ss..........s.           [ 70%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ....................... [ 76%]     [ 98%]
disk/Dropbox/HomeDocs/git/oggm-fork/oggm/tests/ ssssss               [100%]

======================= 224 passed, 149 skipped in 217.03s (0:03:37) ======================


The tests (without the --run-slow option) should run in 5 to 15 minutes. If this takes too long, this may be an indication that something’s wrong

This runs a comprehensive suite of tests. If you want to run the entire test suite (including graphics and slow running tests), type:

pytest.oggm --run-slow --mpl

Congrats, you are now set-up for the Getting started section!

Installation troubleshooting#

We try to do our best to avoid issues, but experience shows that the installation of the necessary packages can be difficult. Typical errors are often related to the pyproj, fiona and GDAL packages, which are heavy and (for pyproj) have changed a lot in the recent past and are prone to platform specific errors.

If the tests don’t pass, a diagnostic of which package creates the errors might be necessary. Errors like segmentation fault or Proj Error are frequent and point to errors in upstream packages, rarely in OGGM itself.

If you encounter issues, please get in touch with us on github.

Install a minimal OGGM environment#

If you plan to use only the numerical core of OGGM (that is, for idealized simulations or teaching), you can skip many dependencies and only install this shorter list:

name: oggm_minimal
  - conda-forge
  - numpy
  - scipy
  - pandas
  - matplotlib
  - shapely
  - requests
  - configobj
  - netcdf4
  - xarray
  - pytables
  - pytest
  # For oggm-edu
  - seaborn
    - oggm

Installing them with pip or conda should be much easier. Install OGGM itself then as above.

Running the tests in this minimal environment works the same. Simply run from a terminal:


The number of tests will be much smaller!

Install with pyenv (Linux)#


We recommend our users to use conda instead of pip, because of the ease of installation with conda. If you are familiar with pip and pyenv, the instructions below work as well: as of Sept 2022 (and thanks to pip wheels), a pyenv installation is possible without major issue on Debian/Ubuntu/Mint systems.

Linux packages#

Run the following commands to install the required linux packages.

For building python and stuff:

$ sudo apt-get install --no-install-recommends make build-essential git \
    libssl-dev zlib1g-dev libbz2-dev libreadline-dev libsqlite3-dev wget \
    curl llvm libncurses5-dev xz-utils tk-dev libxml2-dev libxmlsec1-dev \
    libffi-dev liblzma-dev

For NetCDF and HDF:

$ sudo apt-get install netcdf-bin ncview hdf5-tools libhdf5-dev

Pyenv and pyenv-virtualenv#


If you are not familiar with pyenv, you can visit their documentation (especially the installing pyenv section).

Install pyenv and create a new virtual environment with a recent python version (3.7+) using pyenv-virtualenv.

Python packages#

Be sure to be on the working environment:

$ pyenv activate oggm_env

Update pip (important!):

$ pip install --upgrade pip

Install some packages one by one:

$ pip install numpy scipy pandas shapely matplotlib pyproj \
    rasterio Pillow geopandas netcdf4 scikit-image configobj joblib \
    xarray progressbar2 pytest motionless dask bottleneck toolz \
    tables rioxarray pytables

A pinning of the NetCDF4 package to 1.3.1 might be necessary on some systems (related issue).

Finally, install the pytest-mpl OGGM fork and salem libraries:

$ pip install git+
$ pip install salem

Install OGGM and run the tests#

Refer to Install OGGM itself above.