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/