Orchest can be run on Linux, macOS and Windows (using the exact same steps!).
If you do not yet have Docker installed, please visit https://docs.docker.com/get-docker/.
Linux, macOS and Windows¶
Simply follow the steps below to install Orchest. For Windows, please read the note at the bottom first.
git clone https://github.com/orchest/orchest.git && cd orchest ./orchest install # The previous command will only install language dependencies for # Python. Orchest supports Python, R, and Julia. # To specify other dependencies you can, for example, use: # ./orchest install --lang=all # Valid options for the lang flag are: python, r, julia, all, none # Verify the installation. ./orchest --help
On Windows, Docker has to be configured to use WSL 2. Make sure to clone Orchest inside the Linux environment. For more info and installation steps for Docker with WSL 2 backend, please visit https://docs.docker.com/docker-for-windows/wsl/.
Add Orchest to your
PATH to gain the ability to invoke the
orchest script from anywhere,
e.g. from your home directory:
orchest status. Depending on your shell add
PATH="$HOME/<orchest-install-directory-path>:$PATH" to the corresponding
.profile file. You
need to logout and login again for the changes to take effect.
Build from source¶
You should expect the build to finish in roughly 15 minutes.
git clone https://github.com/orchest/orchest.git && cd orchest # Check out the version you would like to build. git checkout v0.3.0 # Build all Docker containers from source (in parallel). scripts/build_container.sh # Verify the installation. ./orchest --help
We recommend building a tagged commit indicating a release. Other commits cannot be considered stable.
For GPU images the host on which Orchest is running is required to have a GPU driver that is compatible with the CUDA version installed in the image. Compatible version pairs can be found here.
The GPU supported image
orchest/base-kernel-py-gpu includes CUDA Toolkit 10.1. Which
requires the NVIDIA driver on the host to be
To find out which version of the NVIDIA driver you have installed on your host run
nvidia-smi is also available from within the GPU enabled image. Please note that when run from
within the container it reports the CUDA Toolkit version installed on the host. To find out the
CUDA Toolkit version installed in the container image run
Additionally, we require the
nvidia-container package to make sure Docker is able to provide GPU
enabled containers. Installation of the nvidia-container is done using
- Docker GPU documentation
- Most up to date instructions on installing Docker with NVIDIA GPU passthrough support.
Windows WSL 2 (supported)
For WSL 2 follow the CUDA on WSL User Guide provided by NVIDIA.
Please note that the “Docker Desktop WSL 2 backend” (meaning, you’ve installed Docker not directly in the WSL 2 environment but on the Windows host itself) does not support CUDA yet.
macOS (not supported)
nvidia-docker does not support GPU enabled images on macOS (see FAQ on
Make sure you have installed our GPU images for the programming language you want to use.
./orchest install --lang=python --gpu
Run Orchest on the cloud¶
Running Orchest on a cloud hosted VM (such as EC2) does not require a special installation. Simply follow the regular installation process.
To enable SSL run
scripts/letsencrypt-nginx.sh <domain> <email> and restart Orchest
Please refer to the authentication section to enable the authentication server, giving you a login screen requiring a username and password before you can access Orchest.