Installation¶
Install the latest release from PyPI:
To upgrade later:
Note
oryxflow is Python 3 only. If Python 3 is not your default, use pip3 install oryxflow.
Behind an enterprise firewall you can clone the repository and run pip install . from its
root instead.
Development version¶
To install the latest unreleased code straight from GitHub:
Or upgrade in place without touching dependencies:
Optional extras¶
The core install keeps dependencies light. Enable the pieces you need with pip extras:
| Extra | Install | Adds |
|---|---|---|
| Cloud storage (GCS) | pip install "oryxflow[gcs]" |
Read/write task outputs on Google Cloud Storage |
| Cloud storage (S3) | pip install "oryxflow[s3]" |
Read/write task outputs on Amazon S3 |
| Cloud storage (base) | pip install "oryxflow[cloud-base]" |
fsspec/universal_pathlib backend without a specific provider |
| Flow export | pip install "oryxflow[export]" |
FlowExport / FlowImport standalone task files (needs Jinja2) |
| Dask | pip install "oryxflow[dask]" |
Dask DataFrame task types |
After installing a cloud extra, point the engine at remote storage with
oryxflow.enable_gcs(bucket, prefix=None) or the generic
oryxflow.enable_cloud_storage(protocol, bucket, prefix=None). See
Collaborate & share flows for the full workflow.
Build with an AI assistant¶
If you use Claude Code, the official plugin can scaffold your project and wire task dependencies for you:
See Build with Claude Code for what it sets up.
Next steps¶
- Quickstart — build your first self-caching pipeline.
- Transition from scripts — convert an existing analysis script.