Website — Docs — Quickstart
Orchest is a web based tool for creating data science pipelines. Under the hood Orchest runs a collection of containers to provide a scalable platform that can run on your laptop as well as on a large scale cloud cluster.
A preview of running pipelines in the pipeline editor of Orchest. Watch the quickstart video to learn more.
Orchest lets you:
- Visually construct pipelines.
- Write code using JupyterLab.
- Write code using any other editor of choice.
- Run any subset of a pipeline.
- Skip certain cells when executing a notebook top-to-bottom.
- Parametrize your data science pipelines to experiment with different modeling ideas.
- Integrate commonly used data-sources.
- Easily define your custom runtime environment.
- Version your pipelines through Git.
In our docs you can find a comprehensive quickstart tutorial!
NOTE: Orchest is in alpha.
For GPU support, language dependencies other than Python, and other installation methods, such as building from source, refer to our installation docs.
- Docker
If you do not yet have Docker installed, please visit https://docs.docker.com/get-docker/.
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
# Verify the installation.
./orchest --help
NOTE: 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/.
# Make sure to be in the cloned "orchest" directory.
./orchest startGet started with our quickstart tutorial or check out pipelines made by your fellow users.
The software in this repository is licensed as follows:
- All content residing under the "orchest-sdk/" directory of this repository is licensed under the "Apache-2.0" license as defined in "orchest-sdk/LICENSE".
- Content outside of the above mentioned directory is available under the "AGPL-3.0" license.
Contributions are more than welcome! Please see our contributor guides for more details.
We would love to hear what you think and potentially add features based on your ideas. Come chat with us on our Slack Channel.