datalad.api.clone

datalad.api.clone(source, path=None, dataset=None, description=None, reckless=False, alt_sources=None)

Obtain a dataset copy from a URL or local source (path)

The purpose of this command is to obtain a new clone (copy) of a dataset and place it into a not-yet-existing or empty directory. As such clone provides a strict subset of the functionality offered by install. Only a single dataset can be obtained, recursion is not supported. However, once installed, arbitrary dataset components can be obtained via a subsequent get command.

Primary differences over a direct git clone call are 1) the automatic initialization of a dataset annex (pure Git repositories are equally supported); 2) automatic registration of the newly obtained dataset as a subdataset (submodule), if a parent dataset is specified; 3) support for datalad’s resource identifiers and automatic generation of alternative access URL for common cases (such as appending ‘.git’ to the URL in case the accessing the base URL failed); and 4) ability to take additional alternative source locations as an argument.

Parameters:
  • source (str or None) – URL, DataLad resource identifier, local path or instance of dataset to be cloned.
  • path – path to clone into. If no path is provided a destination path will be derived from a source URL similar to git clone. [Default: None]
  • dataset (Dataset or None, optional) – (parent) dataset to clone into. If given, the newly cloned dataset is registered as a subdataset of the parent. Also, if given, relative paths are interpreted as being relative to the parent dataset, and not relative to the working directory. [Default: None]
  • description (str or None, optional) – short description to use for a dataset location. Its primary purpose is to help humans to identify a dataset copy (e.g., “mike’s dataset on lab server”). Note that when a dataset is published, this information becomes available on the remote side. [Default: None]
  • reckless (bool, optional) – Set up the dataset to be able to obtain content in the cheapest/fastest possible way, even if this poses a potential risk the data integrity (e.g. hardlink files from a local clone of the dataset). Use with care, and limit to “read-only” use cases. With this flag the installed dataset will be marked as untrusted. [Default: False]
  • alt_sources (non-empty sequence of str or None, optional) – Alternative sources to be tried if a dataset cannot be obtained from the main source. [Default: None]
  • on_failure ({'ignore', 'continue', 'stop'}, optional) – behavior to perform on failure: ‘ignore’ any failure is reported, but does not cause an exception; ‘continue’ if any failure occurs an exception will be raised at the end, but processing other actions will continue for as long as possible; ‘stop’: processing will stop on first failure and an exception is raised. A failure is any result with status ‘impossible’ or ‘error’. Raised exception is an IncompleteResultsError that carries the result dictionaries of the failures in its failed attribute. [Default: ‘continue’]
  • proc_post – Like proc_pre, but procedures are executed after the main command has finished. [Default: None]
  • proc_pre – DataLad procedure to run prior to the main command. The argument a list of lists with procedure names and optional arguments. Procedures are called in the order their are given in this list. It is important to provide the respective target dataset to run a procedure on as the dataset argument of the main command. [Default: None]
  • result_filter (callable or None, optional) – if given, each to-be-returned status dictionary is passed to this callable, and is only returned if the callable’s return value does not evaluate to False or a ValueError exception is raised. If the given callable supports **kwargs it will additionally be passed the keyword arguments of the original API call. [Default: None]
  • result_renderer ({'default', 'json', 'json_pp', 'tailored'} or None, optional) – format of return value rendering on stdout. [Default: None]
  • result_xfm ({'paths', 'relpaths', 'datasets', 'successdatasets-or-none', 'metadata'} or callable or None, optional) – if given, each to-be-returned result status dictionary is passed to this callable, and its return value becomes the result instead. This is different from result_filter, as it can perform arbitrary transformation of the result value. This is mostly useful for top- level command invocations that need to provide the results in a particular format. Instead of a callable, a label for a pre-crafted result transformation can be given. [Default: None]
  • return_type ({'generator', 'list', 'item-or-list'}, optional) – return value behavior switch. If ‘item-or-list’ a single value is returned instead of a one-item return value list, or a list in case of multiple return values. None is return in case of an empty list. [Default: ‘list’]