No frameworks. No YAML. Just write your data processing code directly in Python, R or Julia.
๐ก Watch the full narrated video to learn more about building data pipelines in Orchest.
NOTE: Orchest is in beta.
- Visually construct pipelines through our user-friendly UI
- Code in Notebooks and scripts (quickstart)
- Run any subset of a pipelines directly or periodically (jobs)
- Easily define your dependencies to run on any machine (environments)
- Spin up services whose lifetime spans across the entire pipeline run (services)
- Version your projects using git (projects)
When to use Orchest? Read it in the docs.
๐ Get started with our quickstart tutorial, check out pipelines made by your fellow users, or have a look at our video tutorials explaining some of Orchest's core concepts.
Want to skip the installation and jump right in? Then try out our managed service by clicking:
For instructions on how to deploy a self-hosted version, check out our installation docs.
The software in this repository is licensed as follows:
- All content residing under the "orchest-sdk/" and "orchest-cli/" directories of this repository are licensed under the "Apache-2.0" license as defined in "orchest-sdk/LICENSE" and "orchest-cli/LICENSE" respectively.
- Content outside of the above mentioned directory is available under the "AGPL-3.0" license.
Join our Slack to chat about Orchest, ask questions, and share tips.
Contributions are more than welcome! Please see our contributor guides for more details.
You could also submit your pipeline to the curated list of examples. Help other users try out your pipeline with one click by adding the following script in the README.md
of your repository (NOTE: you need to replace your-repo-url
with your repo URL).
[![Open in Orchest](https://github.com/orchest/orchest-examples/raw/main/imgs/open_in_orchest.svg)](https://cloud.orchest.io/?import_url=your-repo-url)
An example badge to import our quickstart repo in Orchest: