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datalad install(1) General Commands Manual datalad install(1)


datalad install - install a dataset from a (remote) source.


datalad install [-h] [-s SOURCE] [-d DATASET] [-g] [-D DESCRIPTION] [-r] [-R LEVELS] [--reckless [auto|ephemeral|shared-...]] [-J NJOBS] [PATH ...]


This command creates a local sibling of an existing dataset from a (remote) location identified via a URL or path. Optional recursion into potential subdatasets, and download of all referenced data is supported. The new dataset can be optionally registered in an existing superdataset by identifying it via the DATASET argument (the new dataset's path needs to be located within the superdataset for that).

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.

When only partial dataset content shall be obtained, it is recommended to use this command without the GET-DATA flag, followed by a `get` operation to obtain the desired data.

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


Install a dataset from Github into the current directory::

% datalad install

Install a dataset as a subdataset into the current dataset::

% datalad install -d . --source=''

Install a dataset, and get all content right away::

% datalad install --get-data -s

Install a dataset with all its subdatasets::

% datalad install -r


path/name of the installation target. If no PATH is provided a destination path will be derived from a source URL similar to git clone.

show this help message. --help-np forcefully disables the use of a pager for displaying the help message
URL or local path of the installation source. Constraints: value must be a string
specify the dataset to perform the install operation on. If no dataset is given, an attempt is made to identify the dataset in a parent directory of the current working directory and/or the PATH given. Constraints: Value must be a Dataset or a valid identifier of a Dataset (e.g. a path)
if given, obtain all data content too.
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
if set, recurse into potential subdataset.
limit recursion into subdataset to the given number of levels. Constraints: value must be convertible to type 'int'
set up the dataset in a potentially unsafe way for performance, or access reasons -- use with care, any dataset is marked as 'untrusted'. The reckless mode is stored in a dataset's local configuration under 'datalad.clone.reckless', and will be inherited to any of its subdatasets. Supported modes are: ['auto']: hard-link files between local clones. In-place modification in any clone will alter original annex content. ['ephemeral']: symlink annex to origin's annex and discard local availability info via git-annex-dead 'here'. Shares an annex between origin and clone w/o git-annex being aware of it. In case of a change in origin you need to update the clone before you're able to save new content on your end. Alternative to 'auto' when hardlinks are not an option, or number of consumed inodes needs to be minimized. Please note, that this is meant to be used with either non-bare repositories or a RIA store as origin! Do not come up with your own usecase unless you are absolutely sure you know your git-annex internals very well! ['shared-<mode>']: set up repository and annex permission to enable multi-user access. This disables the standard write protection of annex'ed files. <mode> can be any value support by 'git init --shared=', such as 'group', or 'all'. Constraints: value must be one of (None, True, False, 'auto', 'ephemeral'), or value must start with 'shared-'
how many parallel jobs (where possible) to use. "auto" corresponds to the number defined by 'datalad.runtime.max-annex-jobs' configuration item. Constraints: value must be convertible to type 'int', or value must be one of ('auto',) [Default: 'auto']


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

2021-07-23 datalad install 0.14.6