Provided by: datalad_0.9.3-1_all 
SYNOPSIS
datalad-drop [-h] [-d DATASET] [-r] [--recursion-limit LEVELS] [--nocheck] [--if-dirty {fail,save-
before,ignore}] [PATH [PATH ...]]
DESCRIPTION
Drop file content from datasets
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 in subdirectories within a
dataset as always 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 all file content in a dataset::
~/some/dataset$ datalad drop
Drop all file content in a dataset and all its subdatasets::
~/some/dataset$ datalad drop --recursive
OPTIONS
PATH path/name of the component to be dropped. 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]
--recursion-limit LEVELS
limit recursion into subdataset to the given number of levels. Constraints: value must be
convertible to type 'int' [Default: None]
--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>.