A Python library for the Renku collaborative data science platform. It allows the user to create projects, manage datasets, and capture data provenance while performing analysis tasks.

NOTE:

renku-python is the python library for Renku that provides an SDK and a command-line interface (CLI). It does not start the Renku platform itself - for that, refer to the Renku docs on running the platform.

The latest release is available on PyPI and can be installed using pip:

$ pip install renku

The latest code can be installed directly from the Git repository:

$ pip install -e git+https://github.com/SwissDataScienceCenter/renku-python.git#egg=renku

Use following installation steps based on your operating system and preferences if you would like to work with the command line interface and you do not need the Python library to be importable.

The recommended way of installing Renku on MacOS is via Homebrew.

$ brew tap swissdatasciencecenter/renku
$ brew install renku

You can use pipsi to isolate dependencies and to guarantee that there are no version conflicts. Make sure you have the pipsi command correctly installed and ~/.local/bin is in your $PATH.

$ pipsi install renku
$ which renku
~/.local/bin/renku

Initialize a renku project:

$ mkdir -p ~/temp/my-renku-project
$ cd ~/temp/my-renku-project
$ renku init

Create a dataset and add data to it:

$ renku dataset create my-dataset
$ renku dataset add my-dataset https://raw.githubusercontent.com/SwissDataScienceCenter/renku-python/master/README.rst

Run an analysis:

$ renku run wc < data/my-dataset/README.rst > wc_readme

Trace the data provenance:

$ renku log wc_readme

These are the basics, but there is much more that Renku allows you to do with your data analysis workflows. The full documentation will soon be available at: https://renku-python.readthedocs.io/