The recommended approach is to build your own constructor-based installer. How can I cache my installation? I don't want to wait every time I start Colab. Since we need to re-read LD_LIBRARY_PATH, a kernel restart is needed. Finally, we wrap the Python executable to redirect and inject some environment variables needed to load the new libraries. We install the Miniconda distribution on top of the existing one at /usr/local, add a few configuration files so we stay with Python 3.7 ( conda auto updates by default) and the newly installed packages are available.

You can only use the base environment, so do not try to create more environments with conda create.

If you are wondering why you are seeing a message saying 'Your session crashed for an unknown reason', this is why.

The Python kernel needs to be restarted for changes to be applied.

# or, faster: !mamba env update -n base -f environment.yml Shortcomings !conda env update -n base -f environment.yml Once the installation is done, you can use conda and/or mamba to install the needed packages: If you want to build your own constructor-based installer, check the FAQ below! It expects a URL pointing to a constructor-like installer, so you can prebuild a Python 3.7 distribution that fulfills your own needs. The Mambaforge distribution is officially provided by conda-forge but I forked and patched it so it's built for Python 3.7.įor advanced users, install_from_url() is also available.

install_mambaforge(): Like Miniforge, but with mamba included.

The Miniforge distribution is officially provided by conda-forge but I forked and patched it so it's built for Python 3.7.

install_miniforge(): Like Miniconda, but built off conda-forge packages.

Unlike Anaconda, this distribution only contains python and conda.

install_miniconda(): This will install the Miniconda 4.12.0 distribution, using a version built for Python 3.7.

This contains plenty of data science packages (link to current version docs).

install_anaconda(): This will install the Anaconda 2022.05 distribution, the most recent version built for Python 3.7 at the time of update.The default condacolab.install() provides Mambaforge, but there are other conda distributions to choose from: It is important that you perform the installation first thing in the notebook because it will require a kernel restart, thus resetting the variables set up to that point.

Conda python version pinned