DataLad’s extensions¶
The commands DataLad provides cover a broad range of domain-agnostic use cases. However, there are extension packages that can add (domain-specific) functionality and new commands.
Such extensions are shipped as separate Python packages, and are not included in DataLad itself. Instead, users with the need for a particular extension can install the extension package – either on top of DataLad if DataLad is already installed, or on its own (the extension will then pull in DataLad core automatically, with no need to first or simultaneously install DataLad itself explicitly). The installation is done with standard Python package managers, such as pip, and beyond installation of the package, no additional setup is required.
Among others (a full list can be found on PyPi), the following DataLad extensions are available:
Extension name |
Description |
|---|---|
Equips DataLad’s run/rerun functionality with the ability to transparently execute commands in containerized computational environments. The section Computational reproducibility with software containers demonstrates how this extension can be used, as well as the usecase An automatically reproducible analysis of public neuroimaging data. |
|
Metadata extraction support for a range of standards common to neuroimaging data. The usecase An automatically reproducible analysis of public neuroimaging data demonstrates how this extension can be used. |
|
Equips DataLad with an alternative command suite and advanced tooling for metadata handling (extraction, aggregation, reporting). Todo once section on metadata is done, link it here |
To install a DataLad extension, use
$ pip install <extension-name>
such as in
$ pip install datalad-container
Afterwards, the new DataLad functionality the extension provides is readily available.