renku 0.3.3

Python SDK and CLI for the Renku platform.

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.

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 --dev 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.

MacOS

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

$ brew tap swissdatasciencecenter/renku
$ brew install renku

Pip Script Installer (pipsi)

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

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.

Usage

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/

Changes

v0.3.3

(released 2018-12-07)

• Fixes generated Homebrew formula.

• Renames renku pull path to renku storage pull with deprecation warning.

v0.3.2

(released 2018-11-29)

• Fixes display of workflows in renku log.

v0.3.1

(released 2018-11-29)

• Fixes issues with parsing remote Git URLs.

v0.3.0

(released 2018-11-26)

• Adds JSON-LD context to objects extracted from the Git repository (see renku show context --list).

• Uses PROV-O and WFPROV as provenance vocabularies and generates “stable” object identifiers (@id) for RDF and JSON-LD output formats.

• Refactors the log output to allow linking files and directories.

• Adds support for aliasing tools and workflows.

• Adds option to install shell completion (renku --install-completion).

• Fixes initialization of Git submodules.

• Uses relative submodule paths when appropriate.

• Simplifies external storage configuration.

v0.2.0

(released 2018-09-25)

• Refactored version using Git and Common Workflow Language.

v0.1.0

(released 2017-09-06)

• Initial public release as Renga.