Model querying, loading local ontology in memory #351
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This is the parameter ontology, I assume a dummy ontology file would be more appropriate
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Yes, you could keep just a part of the file, not all of it
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I've made the file shorter
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kgforge/specializations/models/rdf/rdf_model_service_from_directory.py
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kgforge/specializations/models/rdf/rdf_model_service_from_store.py
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kgforge/specializations/models/rdf/rdf_model_service_from_store.py
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| @@ -151,12 +159,16 @@ def _load_shape(self, resource_id): | |||
| for dependency in shape.imports: | |||
| self._load_shape(self.context.expand(dependency)) | |||
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| def _type_shape(self, iri: URIRef): | |||
| def _load_and_get_type_shape(self, iri: URIRef) -> ShapeWrapper: | |||
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The actual return type is Shape.
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_shapes_graph is a ShapesGraphWrapper, and the lookup_shape_from_node method is overridden, and the shape is being wrapped in a ShapeWrapper, no?
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## master #351 +/- ##
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+ Coverage 74.36% 74.45% +0.08%
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Files 100 101 +1
Lines 6315 6376 +61
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+ Hits 4696 4747 +51
- Misses 1619 1629 +10
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DKE-1239
Modelarchetype.get_context_prefix_vocababstract method toModelarchetype: the reason for this is that when rewriting sparql queries, you need to use the context. However,BlueBrainNexus(the store) cannot simply just use aContextobject, because it is merging the metadata context's document with the data context's document, and keeping data context's vocab, and the data context's prefixes. As a result, if you want to use theSparqlQueryBuilder(to do sparql queries, which is what we're trying to enable), you need to implement this function that returns prefixes, a context document (as a dict) and prefixes.Contextinto a dict from theReadOnlyStoreto theContextclass: formatting theContextis no longer just aReadOnlyStore's concern, but aModelmay need to as well. In any case, it's the manipulation of aContext, so it makes sense for it to live there.get_modelandget_storeaccessors inKnowledgeGraphForgeRdfModelService:_build_shapes_mapmethod to implement: it returns the shapes into a Graph, a dictionary indicating the source the shape originates from, and a dictionary that says which class is constrained by which shape. By centralizing it in the same method (which was not the case before), it enables knowing which file contained which schema (for the implementation inRdfModelServiceFromDirectory)RdfModelServiceFromDirectory: formerly namedDirectoryService,get_shape_sourcecan now be implemented (formerly namedschema_source_id) due to the change inRdfModelServicebase classspecializations.stores.service: bug with the context cache not being used fixed