NAME

       datalad drop - drop file content from datasets

SYNOPSIS

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

DESCRIPTION

       This command takes any number of paths of files and/or directories. If a common (super)dataset  is  given
       explicitly, the given paths are interpreted relative to this dataset.

       Recursion  into  subdatasets needs to be explicitly enabled, while recursion into subdirectories within a
       dataset is done automatically. An optional recursion limit is applied relative to each given input path.

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

   Examples
       Drop single file content::

        % datalad drop <path/to/file>

       Drop all file content in the current dataset::

        % datalad drop

       Drop all file content in a dataset and all its subdatasets::

        % datalad drop -d <path/to/dataset> -r

       Disable check to ensure the configured minimum number of remote sources for dropped data::

        % datalad drop <path/to/content> --nocheck

OPTIONS

       PATH   path/name of the component to be dropped. Constraints: value must be a string

       -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 iden‐
              tifier of a Dataset (e.g. a path)

       -r, --recursive
              if set, recurse into potential subdataset.

       -R LEVELS, --recursion-limit LEVELS
              limit recursion into subdataset to the given number of levels. Constraints: value must be convert‐
              ible to type 'int'

       --nocheck
              whether to perform checks to assure the configured minimum number (remote) source for  data.  Give
              this option to skip checks.

       --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; 'ig‐
              nore' let's datalad proceed as if the dataset would not have unsaved changes. [Default:  'save-be‐
              fore']

       --version
              show the module and its version which provides the command

AUTHORS

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

datalad drop 0.15.5                                2022-02-10                                    datalad drop(1)