datalad-next 1.3.0

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 convenience method is provided that implements a standard workflow for obtaining a credential.
• 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.
• New modular framework for URL operations. This framework directly supports operation on http(s), ssh, and file URLs, and can be extended with custom functionality for additional protocols or even interaction with specific individual servers. The basic operations download, upload, delete, and stat are recognized, and can be implemented. The framework offers uniform progress reporting and simultaneous content has computation. This framework is meant to replace and extend the downloader/provide framework in the DataLad core package. In contrast to its predecessor it is integrated with the new credential framework, and operations beyond downloading.
• git-annex-remote-uncurl is a special remote that exposes the new URL operations framework via git-annex. It provides flexible means to compose and rewrite URLs (e.g., to compensate for storage infrastructure changes) without having to modify individual URLs recorded in datasets. It enables seamless transitions between any services and protocols supported by the framework. This special remote can replace the datalad special remote provided by the DataLad core package.
• A download command is provided as a front-end for the new modular URL operations framework.
• A python-requests compatible authentication handler (DataladAuth) that interfaces DataLad's credential system.
• Boosted throughput of DataLad's runner component for command execution.
• Substantially more comprehensive replacement for DataLad's constraints system for type conversion and parameter validation.

Summary of additional features for DataLad extension development

• Framework for uniform command parameter validation. Regardless of the used API (Python, CLI, or GUI), command parameters are uniformly validated. This facilitates a stricter separation of parameter specification (and validation) from the actual implementation of a command. The latter can now focus on a command's logic only, while the former enables more uniform and more comprehensive validation and error reporting. Beyond per-parameter validation and type-conversion also inter-parameter dependency validation and value transformations are supported.
• Improved composition of importable functionality. Key components for commands, annexremotes, datasets (etc) are collected in topical top-level modules that provide "all" necessary pieces in a single place.
• webdav_server fixture that automatically deploys a local WebDAV server.
• 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
• Helper for runtime-patching other datalad code (datalad_next.utils.patch)
• Base class for implementing custom git-annex backends.
• A set of pytest fixtures to:
  • check that no global configuration side-effects are left behind by a test
  • check that no secrets are left behind by a test
  • provide a temporary configuration that is isolated from a user environment and from other tests
  • provide a temporary secret store that is isolated from a user environment and from other tests
  • provide a temporary credential manager to perform credential deployment and manipulation isolated from a user environment and from other tests

Patching the DataLad core package.

Some of the features described above rely on a modification of the DataLad core package itself, rather than coming in the form of additional commands. Loading this extension causes a range of patches to be applied to the datalad package to enable them. A comprehensive description of the current set of patch is available at http://docs.datalad.org/projects/next/en/latest/#datalad-patches

Developing with DataLad NEXT

This extension package moves fast in comparison to the core package. Nevertheless, attention is paid to API stability, adequate semantic versioning, and informative changelogs.

Public vs internal API

Anything that can be imported directly from any of the sub-packages in datalad_next is considered to be part of the public API. Changes to this API determine the versioning, and development is done with the aim to keep this API as stable as possible. This includes signatures and return value behavior.

As an example: from datalad_next.runners import iter_git_subproc imports a part of the public API, but from datalad_next.runners.git import iter_git_subproc does not.

Use of the internal API

Developers can obviously use parts of the non-public API. However, this should only be done with the understanding that these components may change from one release to another, with no guarantee of transition periods, deprecation warnings, etc.

Developers are advised to never reuse any components with names starting with _ (underscore). Their use should be limited to their individual subpackage.

Acknowledgements

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

Contributors

Michael Hanke 🐛 💻 🖋 🎨 📖 💵 🔍 🤔 🚇 🚧 🧑‍🏫 📦 📆 👀 📢 ⚠️ 🔧 📓	catetrai 💻 🎨 📖 🤔 ⚠️	Chris Markiewicz 🚧 💻	Michał Szczepanik 🐛 💻 🖋 📖 💡 🤔 🚇 🚧 👀 📢 ⚠️ ✅ 📓	Stephan Heunis 🐛 💻 📖 🤔 🚧 📢 📓	Benjamin Poldrack 🐛 💻	Yaroslav Halchenko 🐛 💻 🚇 🚧 🔧
Christian Mönch 💻 🎨 📖 🤔 👀 ⚠️ 📓	Adina Wagner ️️️️♿️ 🐛 💻 📖 💡 🚧 📆 👀 📢 ⚠️ ✅ 📓	John T. Wodder II 💻 🚇 ⚠️