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DataLad

DataLad extensions

DataLad is not just a single software package. Numerous extension packages can equip the base package with additional functionality, or even tailor and tune the way the base package works.

DataLad extensions are shipped as separate Python packages. The installation is typically done with standard Python package managers, such as pip. For some extensions it may be necessary to perform additional set up steps in order to become fully functional.

Here is a list of available extension packages for the DataLad software:

datalad-container extension

This extension equips DataLad’s run/rerun functionality with the ability to transparently execute commands in containerized computational environments.

datalad-next extension

This DataLad extension can be thought of as a staging area for additional functionality, or for improved performance and user experience. Unlike other topical or more experimental extensions, the focus here is on functionality with broad applicability. This extension is a suitable dependency for other software packages that intend to build on this improved set of functionality.

datalad-xnat extension

This extension packages equips DataLad with a set of commands to track XNAT projects.

XNAT is an open source imaging informatics platform developed by the Neuroinformatics Research Group at Washington University. It facilitates common management, productivity, and quality assurance tasks for imaging and associated data. XNAT can be used to support a wide range of neuro/medical imaging-based projects.

Installer

The DataLad installer is a utility for installing Datalad, git-annex, and related components all in a single invocation. It requires no third-party Python libraries, though it does make heavy use of external packaging commands.

DataSalad

This is a pure-Python library with a collection of utilities for working with data in the vicinity of Git and git-annex. While this is a foundational library from and for the DataLad project, its implementations are standalone, and are meant to be equally well usable outside the DataLad system.

A focus of this library is efficient communication with subprocesses, such as Git or git-annex commands, which read and produce data in some format.