Renku CLI and SDK for Python¶
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-pythonis 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.
Installation¶
The latest release is available on PyPI and can be installed using
pip:
$ pip install renku
The latest development versions are available on PyPI or from the Git repository:
$ pip install --pre renku
# - OR -
$ 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.
Homebrew¶
The recommended way of installing Renku on MacOS and Linux is via Homebrew.
$ brew tap swissdatasciencecenter/renku
$ brew install renku
Isolated environments using pipx¶
Install and execute Renku in an isolated environment using pipx.
It will guarantee that there are no version conflicts with dependencies
you are using for your work and research.
Install pipx
and make sure that the $PATH is correctly configured.
$ python3 -m pip install --user pipx
$ pipx ensurepath
Once pipx is installed use following command to install renku.
$ pipx install renku
$ which renku
~/.local/bin/renku
Prevously we have recommended to use pipsi. You can still use it or
migrate to **pipx**.
Docker¶
The containerized version of the CLI can be launched using Docker command.
$ docker run -it -v "$PWD":"$PWD" -w="$PWD" renku/renku-python renku
It makes sure your current directory is mounted to the same place in the container.
Getting Started¶
Interaction with the platform can take place via the command-line interface (CLI).
Start by creating for folder where you want to keep your 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.
For more information about using renku, refer to the renku –help.