Provided by: datalad_0.11.6-1ubuntu2_all bug


       datalad drop - drop file content from datasets


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


       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

       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.


       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


       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]

       -R LEVELS, --recursion-limit LEVELS
              limit recursion into subdataset to the given number of levels.  Constraints:  value
              must be convertible to type 'int' [Default: None]

              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']


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

                                            2019-08-19                            datalad drop(1)