Reading and Writing Files

Note

This page builds on the information given in xarray’s main page on reading and writing files, so it is suggested that you are familiar with those first.

netCDF

Groups

Whilst netCDF groups can only be loaded individually as Dataset objects, a whole file of many nested groups can be loaded as a single DataTree object. To open a whole netCDF file as a tree of groups use the open_datatree() function. To save a DataTree object as a netCDF file containing many groups, use the DataTree.to_netcdf() method.

Warning

DataTree objects do not follow the exact same data model as netCDF files, which means that perfect round-tripping is not always possible.

In particular in the netCDF data model dimensions are entities that can exist regardless of whether any variable possesses them. This is in contrast to xarray’s data model (and hence datatree’s data model) in which the dimensions of a (Dataset/Tree) object are simply the set of dimensions present across all variables in that dataset.

This means that if a netCDF file contains dimensions but no variables which possess those dimensions, these dimensions will not be present when that file is opened as a DataTree object. Saving this DataTree object to file will therefore not preserve these “unused” dimensions.

Zarr

Groups

Nested groups in zarr stores can be represented by loading the store as a DataTree object, similarly to netCDF. To open a whole zarr store as a tree of groups use the open_datatree() function. To save a DataTree object as a zarr store containing many groups, use the DataTree.to_zarr() method.

Note

Note that perfect round-tripping should always be possible with a zarr store (unlike for netCDF files), as zarr does not support “unused” dimensions.