Install Conda and friends on Google Colab, easily
Install Conda and friends on Google Colab, easily.
TLDR: Check the example notebook here!
On your Colab notebook, run the following code as the first executable cell:
!pip install -q condacolab import condacolab condacolab.install()
After the kernel restart, you can optionally add a new cell to check that everything is in place:
import condacolab condacolab.check()
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.
condacolab.install() provides Mambaforge, but there are other
conda distributions to choose from:
install_miniconda(): This will install the Miniconda distribution, using a version built for Python 3.10. Unlike Anaconda, this distribution only contains
install_miniforge(): Like Miniconda, but built off
conda-forgepackages. The Miniforge distribution is officially provided by conda-forge.
install_mambaforge(): Like Miniforge, but with
mambaincluded. The Mambaforge distribution is officially provided by conda-forge.
For advanced users,
install_from_url() is also available. It expects a URL pointing to a
constructor-like installer, so you can prebuild a Python 3.10 distribution that fulfills your own needs.
If you want to build your own
constructor-based installer, check the FAQ below!
Once the installation is done, you can use
mamba to install the needed packages:
!conda install openmm # or, faster: !mamba install openmm
If you have a environment file (e.g.
environment.yml), you can use it like this:
!conda env update -n base -f environment.yml # or, faster: !mamba env update -n base -f environment.yml
- The Python kernel needs to be restarted for changes to be applied. This happens automatically. If you are wondering why you are seeing a message saying "Your session crashed for an unknown reason", this is why. You can safely ignore this message!
- You can only use the
baseenvironment, so do not try to create more environments with
conda create. If you have an environment file, use
conda env update -n base -f <your-file.yml>.
How does it work?
Google Colab runs on Python 3.10. We install the Miniconda distribution on top of the existing one at
/usr/local, add a few configuration files so we stay with Python 3.10 and the newly installed packages are available. Finally, we wrap the Python executable to redirect and inject some environment variables needed to load the new libraries. Since we need to re-read
LD_LIBRARY_PATH, a kernel restart is needed.
How can I cache my installation? I don't want to wait every time I start Colab.
The recommended approach is to build your own
constructor-based installer. We have provided an example in
You can generate a
constructorinstaller on Colab too! Follow this tutorial.
Locally, follow these steps:
- In your local computer:
conda create -n constructor -c conda-forge constructor conda activate constructor mkdir my-installer cd my-installer curl -sLO https://raw.githubusercontent.com/jaimergp/condacolab/main/constructor-example/construct.yaml curl -sLO https://raw.githubusercontent.com/jaimergp/condacolab/main/constructor-example/pip-dependencies.sh
- Add your
specssection. Read the comments to respect the constrains already present! You can also adapt the metadata to your liking.
- If you do need to install
piprequirements, uncomment the
post_installline and edit
constructor --platform linux-64 .
- Upload the resulting
.shto an online location with a permanent URL. GitHub Releases is great for this!
- In Colab, run:
!pip install -q condacolab import condacolab condacolab.install_from_url(URL_TO_YOUR_CUSTOM_CONSTRUCTOR_INSTALLER)
Can I install R packages?
Yes, as long as you make sure you also install
rpy2 to overwrite Colab's installation.
See issue #26 for more details.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Hashes for condacolab-0.1.7-py3-none-any.whl