Graph

class Graph(*, id: str | None = None, meta: Meta | None = None, nodes: List[Node] = None, edges: List[Edge] = None, equivalentNodesSets: List[Any] = None, logicalDefinitionAxioms: List[Any] = None, domainRangeAxioms: List[Any] = None, propertyChainAxioms: List[Any] = None, prefix: str | None = None, standardized: bool = False)[source]

Bases: BaseModel, StandardizeMixin

A graph corresponds to an ontology.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Attributes Summary

`default_namespace`	Get the version of the ontology.
`description`	Get the license of the ontology.
`license`	Get the license of the ontology.
`model_computed_fields`	A dictionary of computed field names and their corresponding ComputedFieldInfo objects.
`model_config`	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
`model_fields`	Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].
`roots`	Get the ontology root terms.
`title`	Get the title of the ontology.
`version`	Get the version of the ontology.
`version_iri`	Get the version of the ontology.

Methods Summary

`get_alternative_ids`()	Get a mapping of primary identifiers to secondary identifiers.
`get_curie_to_name`()	Get a mapping from CURIEs to names.
`get_edges_df`(*[, require_labels])	Get all triples as a dataframe.
`get_incoming_xrefs`(prefix)	Get incoming xrefs.
`get_networkx`()	Get a networkx multi-directional graph.
`get_nodes_df`([sep])	Get a nodes dataframe appropriate for serialization.
`get_sssom_df`()	Get a SSSOM dataframe of mappings.
`get_xrefs`()	Get all database cross-references from the ontology.
`nodes_from`(prefix)	Iterate non-deprecated nodes whose identifiers start with the given prefix.
`standardize`([keep_invalid, use_tqdm, nodes, ...])	Standardize the OBO graph.

Attributes Documentation

default_namespace: Get the version of the ontology.

description: Get the license of the ontology.

license: Get the license of the ontology.

model_computed_fields: ClassVar[dict[str, ComputedFieldInfo]] = {}: A dictionary of computed field names and their corresponding ComputedFieldInfo objects.

model_config: ClassVar[ConfigDict] = {}: Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].

model_fields: ClassVar[dict[str, FieldInfo]] = {'domainRangeAxioms': FieldInfo(annotation=List[Any], required=False, default_factory=list), 'edges': FieldInfo(annotation=List[bioontologies.obograph.Edge], required=False, default_factory=list), 'equivalentNodesSets': FieldInfo(annotation=List[Any], required=False, default_factory=list), 'id': FieldInfo(annotation=Union[str, NoneType], required=False), 'logicalDefinitionAxioms': FieldInfo(annotation=List[Any], required=False, default_factory=list), 'meta': FieldInfo(annotation=Union[Meta, NoneType], required=False), 'nodes': FieldInfo(annotation=List[bioontologies.obograph.Node], required=False, default_factory=list), 'prefix': FieldInfo(annotation=Union[str, NoneType], required=False), 'propertyChainAxioms': FieldInfo(annotation=List[Any], required=False, default_factory=list), 'standardized': FieldInfo(annotation=bool, required=False, default=False, exclude=True)}

Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo].

This replaces Model.__fields__ from Pydantic V1.

roots: Get the ontology root terms.

title: Get the title of the ontology.

version: Get the version of the ontology.

version_iri: Get the version of the ontology.

Methods Documentation

get_alternative_ids() → Mapping[str, List[str]][source]: Get a mapping of primary identifiers to secondary identifiers.

get_curie_to_name() → Mapping[str, str][source]: Get a mapping from CURIEs to names.

get_edges_df(*, require_labels: bool = False) → DataFrame[source]: Get all triples as a dataframe.

get_incoming_xrefs(prefix: str) → Mapping[str, str][source]

Get incoming xrefs.

Parameters:: prefix – An external prefix.
Returns:: A dictionary of external local unique identifiers to local unique identifiers in this ontology

get_networkx()[source]: Get a networkx multi-directional graph.

get_nodes_df(sep: str = ';') → DataFrame[source]: Get a nodes dataframe appropriate for serialization.

get_sssom_df() → DataFrame[source]: Get a SSSOM dataframe of mappings.

get_xrefs() → List[Tuple[Reference, Reference, Reference]][source]: Get all database cross-references from the ontology.

nodes_from(prefix: str) → Iterable[Node][source]: Iterate non-deprecated nodes whose identifiers start with the given prefix.

standardize(keep_invalid: bool = False, use_tqdm: bool = True, nodes: bool = True, edges: bool = True, tqdm_kwargs: Mapping[str, Any] | None = None, prefix: str | None = None) → Self[source]

Standardize the OBO graph.

Parameters:

keep_invalid – Should CURIEs/IRIs that aren’t handled by the Bioregistry be kept? Defaults to false.
use_tqdm – Should a progress bar be used?
tqdm_kwargs – Arguments to pass to tqdm if used
prefix – The prefix this graph came from (used for logging purposes)
nodes – Should nodes be standardized?
edges – Should edges be standardized?

Returns:

This OBO graph, modified in place as follows:

Convert IRIs to CURIEs (in many places) using bioregistry
Add alternative identifiers to Node objects