datalad-next 0.6.3

What is next in DataLad

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.

Installation

# create and enter a new virtual environment (optional)
$ virtualenv --python=python3 ~/env/dl-next
$ . ~/env/dl-next/bin/activate
# install from PyPi
$ python -m pip install datalad-next

How to use

Additional commands provided by this extension are immediately available after installation. However, in order to fully benefit from all improvements, the extension has to be enabled for auto-loading by executing:

git config --global --add datalad.extensions.load next

Doing so will enable the extension to also alter the behavior the core DataLad package and its commands.

Summary of functionality provided by this extension

• A replacement sub-system for credential handling that is able to handle arbitrary properties for annotating a secret, and facilitates determining suitable credentials while minimizing avoidable user interaction, without compromising configurability.
• A user-facing credentials command to set, remove, and query credentials.
• The create-sibling-... commands for the platforms GitHub, GIN, GOGS, Gitea are equipped with improved credential handling that, for example, only stores entered credentials after they were confirmed to work, or auto-selects the most recently used, matching credentials, when none are specified.
• A create-sibling-webdav command for hosting datasets on a WebDAV server via a sibling tandem for Git history and file storage. Datasets hosted on WebDAV in this fashion are cloneable with datalad-clone. A full annex setup for storing complete datasets with historical file content version, and an additional mode for depositing single-version dataset snapshot are supported. The latter enables convenient collaboration with audiences that are not using DataLad, because all files are browsable via a WebDAV server's point-and-click user interface.
• Enhance datalad-push to automatically export files to git-annex special remotes configured with exporttree=yes.
• Speed-up datalad-push when processing non-git special remotes. This particularly benefits less efficient hosting scenarios like WebDAV.
• Enhance datalad-siblings enable (AnnexRepo.enable_remote() to automatically deploy credentials for git-annex special remotes that require them.
• git-remote-datalad-annex is a Git remote helper to push/fetch to any location accessible by any git-annex special remote.
• git-annex-backend-XDLRA (originally available from the mihextras extension) is a custom external git-annex backend used by git-remote-datalad-annex. A base class to facilitate development of external backends in Python is also provided.
• Enhance datalad-configuration to support getting configuration from "global" scope without a dataset being present.

Summary of additional features for DataLad extension development

• serve_path_via_webdav test decorator that automatically deploys a local WebDAV server.
• with_credential test decorator that temporarily deploys a credential to the local credential system.
• Utilities for HTTP handling
  • probe_url() discovers redirects and authentication requirements for an HTTP URL
  • get_auth_realm() returns a label for an authentication realm that can be used to query for matching credentials
• Utilities for special remote credential management:
  • get_specialremote_credential_properties() inspects a special remote and returns properties for querying a credential store for matching credentials
  • update_specialremote_credential() updates a credential in a store after successful use
  • get_specialremote_credential_envpatch() returns a suitable environment "patch" from a credential for a particular special remote type

Acknowledgements

This DataLad extension was developed with funding from the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under grant SFB 1451 (431549029, INF project).