TODO#
Important things that are not implemented yet!
nwb_linkml.adapters.classes.ClassAdapter.handle_dtype()does not yet handle compound dtypes, leaving them asAnyTypeinstead. This is fine for a first draft since they are used rarely within NWB, but we will need to handle them by making slots for each of the dtypes since they typically represent table-like data.
Docs TODOs#
Todo
Implement reading, skipping arrays - they are fast to read with the ArrayProxy class
and dask, but there are times when we might want to leave them out of the read entirely.
This might be better implemented as a filter on model_dump , but to investigate further
how best to support reading just metadata, or even some specific field value, or if
we should leave that to other implementations like eg. after we do SQL export then
not rig up a whole query system ourselves.
Todo
Implement HDF5 writing.
Need to create inverse mappings that can take pydantic models to
hdf5 groups and datasets. If more metadata about the generation process
needs to be preserved (eg. explicitly notating that something is an attribute,
dataset, group, then we can make use of the LinkML_Meta
model. If the model to edit has been loaded from an HDF5 file (rather than
freshly created), then the hdf5_path should be populated making
mapping straightforward, but we probably want to generalize that to deterministically
get hdf5_path from position in the NWBFile object – I think that might
require us to explicitly annotate when something is supposed to be a reference
vs. the original in the model representation, or else it’s ambiguous.
Otherwise, it should be a matter of detecting changes from file if it exists already, and then write them.
Todo
Test find_references() !
Todo
Document Pydantic model generation
Todo
Document provider usage