Provided by: datalad_0.11.2-2_all bug

NAME

       datalad create - create a new dataset from scratch.

SYNOPSIS

       datalad  create  [-h]  [-f]  [-D  DESCRIPTION] [-d PATH] [--no-annex] [--nosave] [--annex-
              version   ANNEX_VERSION]   [--annex-backend   ANNEX_BACKEND]    [--native-metadata-
              type  LABEL]  [--shared-access  MODE]  [--git-opts  STRING]  [--annex-opts  STRING]
              [--annex-init-opts STRING] [--text-no-annex] [--fake-dates] [PATH]

DESCRIPTION

       This command initializes a new dataset at a given location, or the current directory.  The
       new  dataset  can  optionally be registered in an existing superdataset (the new dataset's
       path needs to be located within the superdataset for that, and the superdataset  needs  to
       be  given  explicitly).  It  is  recommended  to  provide a brief description to label the
       dataset's nature *and* location, e.g. "Michael's music on black laptop". This helps humans
       to  identify  data locations in distributed scenarios.  By default an identifier comprised
       of user and machine name, plus path will be generated.

       This command only creates a new dataset, it does not add any content to it,  even  if  the
       target directory already contains additional files or directories.

       Plain  Git  repositories can be created via the --no-annex flag.  However, the result will
       not be a full  dataset,  and,  consequently,  not  all  features  are  supported  (e.g.  a
       description).

       To create a local version of a remote dataset use the `install` command instead.

       NOTE   Power-user  info:  This command uses git init and git annex init to prepare the new
              dataset. Registering to a  superdataset  is  performed  via  a  git  submodule  add
              operation in the discovered superdataset.

OPTIONS

       PATH   path  where the dataset shall be created, directories will be created as necessary.
              If no location is provided, a dataset  will  be  created  in  the  current  working
              directory.  Either way the command will error if the target directory is not empty.
              Use FORCE to create a dataset in a non-empty directory. Constraints: value must  be
              a  string,  or  Value  must be a Dataset or a valid identifier of a Dataset (e.g. a
              path) [Default: None]

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

       -f, --force
              enforce creation of a dataset in a non-empty directory. [Default: False]

       -D DESCRIPTION, --description DESCRIPTION
              short  description  to  use  for a dataset location. Its primary purpose is to help
              humans to identify a dataset copy (e.g., "mike's dataset on lab server"). Note that
              when a dataset is published, this information becomes available on the remote side.
              Constraints: value must be a string [Default: None]

       -d PATH, --dataset PATH
              specify the dataset to perform the create operation on. If a dataset  is  given,  a
              new  subdataset  will  be  created in it. Constraints: Value must be a Dataset or a
              valid identifier of a Dataset (e.g. a path) [Default: None]

       --no-annex
              if set, a plain Git repository will be created without any annex. [Default: False]

       --nosave
              by default all modifications to a dataset are immediately saved. Giving this option
              will disable this behavior. [Default: True]

       --annex-version ANNEX_VERSION
              select  a  particular  annex  repository  version.  The  list of supported versions
              depends on the available git-annex version. This should be left  untouched,  unless
              you  know  what you are doing. Constraints: value must be convertible to type 'int'
              [Default: None]

       --annex-backend ANNEX_BACKEND
              set default hashing backend used by the  new  dataset.  For  a  list  of  supported
              backends  see  the  git-annex  documentation.  The default is optimized for maximum
              compatibility of datasets across platforms  (especially  those  with  limited  path
              lengths). Constraints: value must be a string [Default: 'MD5E']

       --native-metadata-type LABEL
              Metadata type label. Must match the name of the respective parser implementation in
              DataLad (e.g. "xmp"). This option can be given multiple times.  Constraints:  value
              must be a string [Default: None]

       --shared-access MODE
              configure  shared  access  to  a dataset, see `git init --shared` documentation for
              complete details on the supported  scenarios.  Possible  values  include:  'false',
              'true', 'group', and 'all'. [Default: None]

       --git-opts STRING
              option  string  to  be  passed  to  git  calls. Constraints: value must be a string
              [Default: None]

       --annex-opts STRING
              option string to be passed to git annex calls. Constraints: value must be a  string
              [Default: None]

       --annex-init-opts STRING
              option  string  to  be passed to git annex init calls. Constraints: value must be a
              string [Default: None]

       --text-no-annex
              if set, all text files in the future would be added to Git, not annex. Achieved  by
              adding     an     entry     to     .GITATTRIBUTES     file.     See     http://git-
              annex.branchable.com/tips/largefiles/ and NO_ANNEX DataLad plugin to establish even
              more  detailed  control  over which files are placed under annex control. [Default:
              None]

       --fake-dates
              Configure the repository to use fake dates. The date for a new commit will  be  set
              to  one  second later than the latest commit in the repository. This can be used to
              anonymize dates. [Default: False]

AUTHORS

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

                                            2019-02-09                          datalad create(1)