Installation

Requirements:

Python 3.6+ (built using python:3.6)
Git
Optional: Java 11+ to use d2s sparql upload
Optional: oc command line tool for deploying to the DSRI OpenShift cluster (for Maastricht University academics and students)

Install the d2s client#

Install the d2s client with pip on Linux, MacOS and Windows:

pip install d2s

Use your favorite pip tool

We recommend to use pipx if you just want to execute d2s. You can also install with pip or pip3 depending on your system preferences.

Additional documentation

See the Install requirements page for additional documentation to install requirements.

Enable autocompletion#

Optional

Enabling commandline autocompletion in the terminal provides a better experience using the d2s client.

ZSH: add the import autocomplete line to the ~/.zshrc file. Then restart the terminal.

echo 'eval "$(_D2S_COMPLETE=source_zsh d2s)"' >> ~/.zshrc

Use ZSH by default

Set your terminal to use ZSH by default:

chsh -s /bin/zsh

Custom theme

An oh-my-zsh theme can be easily chosen for a personalized experience. See the zsh-theme-biradate to easily install a simple theme and configure your terminal in a few minutes.

To be tested

Bash: add the import autocomplete line to the ~/.bashrc file.

echo 'eval "$(_D2S_COMPLETE=source d2s)"' >> ~/.bashrc

Try the client#

d2s

Autocomplete

Use Tab after a d2s command in the terminal to see all the available options (it will adapt to the command and dynamically retrieve your datasets and workflows!).

Initialize a project folder#

d2s can be used to create datasets mappings in any project folder.

But we also provide a command to help you getting started by generating all required files in your project folder (readme, license. gitignore, etc).

This command will initialize the current folder with all necessary files to start converting datasets:

d2s init

Use Git

We automatically initialize this repository with git init. We recommend you to keep track of changes with git and publish this repository to a remove repository.