datalad-uninstall

Synopsis

datalad-uninstall [-h] [-d DATASET] [-r] [--nocheck] [--if-dirty {fail,save-before,ignore}] [PATH [PATH ...]]

Description

Uninstall subdatasets

This command can be used to uninstall any number of installed subdataset. If a to-be-uninstalled subdataset contains presently installed subdatasets itself, their recursive removal has to be enabled explicitly to avoid the command to exit with an error. This command will error if individual files or non-dataset directories are given as input (use the drop or remove command depending in the desired goal), nor will it uninstall top-level datasets (i.e. datasets that or not a subdataset in another dataset; use the remove command for this purpose).

By default, the availability of at least one remote copy for each currently available file in any dataset is verified. 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:

Uninstall a subdataset (undo installation):

~/some/dataset$ datalad uninstall somesubdataset1

Options

PATH

path/name of the component to be uninstalled. Constraints: value must be a string [Default: None]

-h, –help, –help-np

show this help message. –help-np forcefully disables the use of a pager for displaying the help message

-d DATASET, –dataset DATASET

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. Constraints: Value must be a Dataset or a valid identifier of a Dataset (e.g. a path) [Default: None]

-r, –recursive

if set, recurse into potential subdataset. [Default: False]

–nocheck

whether to perform checks to assure the configured minimum number (remote) source for data. Give this option to skip checks. [Default: True]

–if-dirty {fail,save-before,ignore}

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’]

Authors

datalad is developed by The DataLad Team and Contributors <team@datalad.org>.