datalad.api.remove

datalad.api.remove(path=None, dataset=None, recursive=False, check=True, save=True, message=None, if_dirty='save-before')

Remove components from datasets

This command can remove any components (subdatasets, and (directories with) files) from datasets. Removing a component implies any present content to be dropped, and any associated subdatasets to be uninstalled. Subsequently, the component is “unregistered” from the respective dataset. This means that the respective component is no longer present on the file system.

By default, the availability of at least one remote copy is verified, by default, before file content is dropped. As these checks could lead to slow operation (network latencies, etc), they can be disabled.

Any number of paths to process can be given as input. Recursion into subdatasets needs to be explicitly enabled, while recursion in subdirectories within a dataset as always done automatically. An optional recursion limit is applied relative to each given input path.

Examples

Permanently remove a subdataset from a dataset and wipe out the subdataset association too:

~/some/dataset$ datalad remove somesubdataset1
Parameters:
  • path (sequence of str or None, optional) – path/name of the component to be removed. [Default: None]
  • dataset (Dataset or None, optional) – specify the dataset to perform the operation on. If no dataset is given, an attempt is made to identify a dataset based on the path given. [Default: None]
  • recursive (bool, optional) – if set, recurse into potential subdataset. [Default: False]
  • check (bool, optional) – whether to perform checks to assure the configured minimum number (remote) source for data. [Default: True]
  • save (bool, optional) – by default all modifications to a dataset are immediately saved. Given this option will disable this behavior. [Default: True]
  • message (str or None, optional) – a description of the state or the changes made to a dataset. [Default: None]
  • if_dirty – desired behavior if a dataset with unsaved changes is discovered: ‘fail’ will trigger an error and further processing is aborted; ‘save-before’ will save all changes prior any further action; ‘ignore’ let’s datalad proceed as if the dataset would not have unsaved changes. [Default: ‘save-before’]
  • 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’]
  • 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'} 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’]
  • run_after – Like run_before, but plugins are executed after the main command has finished. [Default: None]
  • run_before – DataLad plugin to run before the command. PLUGINSPEC is a list comprised of a plugin name plus optional 2-tuples of key-value pairs with arguments for the plugin call (see plugin command documentation for details). PLUGINSPECs must be wrapped in list where each item configures one plugin call. Plugins are called in the order defined by this list. For running plugins that require a dataset argument it is important to provide the respective dataset as the dataset argument of the main command, if it is not in the list of plugin arguments. [Default: None]