h5rdmtoolbox.ld.shacl.validate_hdf#
- h5rdmtoolbox.ld.shacl.validate_hdf(*, hdf_data=None, hdf_source=None, shacl_data=None, shacl_source=None, hdf_file_uri='https://example.org/hdf5file#', shacl_format='turtle', hdf_data_format='turtle', ont_graph=None, ont_graph_format='turtle', merge_ont_graph_into_data=True, **pyshacl_kwargs)[source]#
Validate an HDF5 file against SHACL shapes.
- Parameters:
hdf_data (
Union[str,rdflib.Graph], optional) – The HDF5 data as a string or rdflib.Graph. If is string is provided it is assumed to be in Turtle format (you may overwrite this by passing hdf_data_format).hdf_source (
Union[h5py.File,pathlib.Path], optional) – The path to the HDF5 file.hdf_file_uri (
str, optional) – The base URI to use for the HDF5 file when generating RDF. Default is “shacl_data (
Union[str,rdflib.Graph], optional) – The SHACL shapes as a string or rdflib.Graph. If is string is provided it is assumed to be in Turtle format.shacl_source (
Union[str,pathlib.Path], optional) – The path to the SHACL shapes file.shacl_format (
str, optional) – The format of the SHACL shapes string. Default is ‘turtle’.hdf_data_format (
str, optional) – The format of the HDF5 data string. Default is ‘turtle’.ont_graph (
Union[str,rdflib.Graph,pathlib.Path], optional) – Ontology graph to use during validation. If merge_ont_graph_into_data is True, it is merged into the generated HDF RDF data graph before validation. Otherwise it is passed to pySHACL as ont_graph.ont_graph_format (
str, optional) – The format of the ontology graph string. Default is ‘turtle’.merge_ont_graph_into_data (
bool, optional) – If True, the ontology graph is merged into the generated HDF RDF data graph before validation. This is useful for making ontology triples visible to SHACL constraints.**pyshacl_kwargs – Additional keyword arguments to pass to pyshacl.validate().
- Returns:
ValidationResult– The result of the validation containing:conforms: bool
results_graph: rdflib.Graph
results_text: str
messages: List[str]