""" RDFLib defines the following kinds of Graphs: * [`Graph`][rdflib.graph.Graph] * [`QuotedGraph`][rdflib.graph.QuotedGraph] * [`ConjunctiveGraph`][rdflib.graph.ConjunctiveGraph] * [`Dataset`][rdflib.graph.Dataset] ## Graph An RDF graph is a set of RDF triples. Graphs support the python `in` operator, as well as iteration and some operations like union, difference and intersection. See [`Graph`][rdflib.graph.Graph] ## Conjunctive Graph !!! warning "Deprecation notice" `ConjunctiveGraph` is deprecated, use [`Dataset`][rdflib.graph.Dataset] instead. A Conjunctive Graph is the most relevant collection of graphs that are considered to be the boundary for closed world assumptions. This boundary is equivalent to that of the store instance (which is itself uniquely identified and distinct from other instances of [`Store`][rdflib.store.Store] that signify other Conjunctive Graphs). It is equivalent to all the named graphs within it and associated with a `_default_` graph which is automatically assigned a [`BNode`][rdflib.term.BNode] for an identifier - if one isn't given. See [`ConjunctiveGraph`][rdflib.graph.ConjunctiveGraph] ## Quoted graph The notion of an RDF graph [14] is extended to include the concept of a formula node. A formula node may occur wherever any other kind of node can appear. Associated with a formula node is an RDF graph that is completely disjoint from all other graphs; i.e. has no nodes in common with any other graph. (It may contain the same labels as other RDF graphs; because this is, by definition, a separate graph, considerations of tidiness do not apply between the graph at a formula node and any other graph.) This is intended to map the idea of "{ N3-expression }" that is used by N3 into an RDF graph upon which RDF semantics is defined. See [`QuotedGraph`][rdflib.graph.QuotedGraph] ## Dataset The RDF 1.1 Dataset, a small extension to the Conjunctive Graph. The primary term is "graphs in the datasets" and not "contexts with quads" so there is a separate method to set/retrieve a graph in a dataset and to operate with dataset graphs. As a consequence of this approach, dataset graphs cannot be identified with blank nodes, a name is always required (RDFLib will automatically add a name if one is not provided at creation time). This implementation includes a convenience method to directly add a single quad to a dataset graph. See [`Dataset`][rdflib.graph.Dataset] ## Working with graphs Instantiating Graphs with default store (Memory) and default identifier (a BNode): ```python >>> g = Graph() >>> g.store.__class__ >>> g.identifier.__class__ ``` Instantiating Graphs with a Memory store and an identifier - : ```python >>> g = Graph('Memory', URIRef("https://rdflib.github.io")) >>> g.identifier rdflib.term.URIRef('https://rdflib.github.io') >>> str(g) # doctest: +NORMALIZE_WHITESPACE " a rdfg:Graph;rdflib:storage [a rdflib:Store;rdfs:label 'Memory']." ``` Creating a ConjunctiveGraph - The top level container for all named Graphs in a "database": ```python >>> g = ConjunctiveGraph() >>> str(g.default_context) "[a rdfg:Graph;rdflib:storage [a rdflib:Store;rdfs:label 'Memory']]." ``` Adding / removing reified triples to Graph and iterating over it directly or via triple pattern: ```python >>> g = Graph() >>> statementId = BNode() >>> print(len(g)) 0 >>> g.add((statementId, RDF.type, RDF.Statement)) # doctest: +ELLIPSIS )> >>> g.add((statementId, RDF.subject, ... URIRef("https://rdflib.github.io/store/ConjunctiveGraph"))) # doctest: +ELLIPSIS )> >>> g.add((statementId, RDF.predicate, namespace.RDFS.label)) # doctest: +ELLIPSIS )> >>> g.add((statementId, RDF.object, Literal("Conjunctive Graph"))) # doctest: +ELLIPSIS )> >>> print(len(g)) 4 >>> for s, p, o in g: ... print(type(s)) ... >>> for s, p, o in g.triples((None, RDF.object, None)): ... print(o) ... Conjunctive Graph >>> g.remove((statementId, RDF.type, RDF.Statement)) # doctest: +ELLIPSIS )> >>> print(len(g)) 3 ``` `None` terms in calls to [`triples()`][rdflib.graph.Graph.triples] can be thought of as "open variables". Graph support set-theoretic operators, you can add/subtract graphs, as well as intersection (with multiplication operator g1*g2) and xor (g1 ^ g2). Note that BNode IDs are kept when doing set-theoretic operations, this may or may not be what you want. Two named graphs within the same application probably want share BNode IDs, two graphs with data from different sources probably not. If your BNode IDs are all generated by RDFLib they are UUIDs and unique. ```python >>> g1 = Graph() >>> g2 = Graph() >>> u = URIRef("http://example.com/foo") >>> g1.add([u, namespace.RDFS.label, Literal("foo")]) # doctest: +ELLIPSIS )> >>> g1.add([u, namespace.RDFS.label, Literal("bar")]) # doctest: +ELLIPSIS )> >>> g2.add([u, namespace.RDFS.label, Literal("foo")]) # doctest: +ELLIPSIS )> >>> g2.add([u, namespace.RDFS.label, Literal("bing")]) # doctest: +ELLIPSIS )> >>> len(g1 + g2) # adds bing as label 3 >>> len(g1 - g2) # removes foo 1 >>> len(g1 * g2) # only foo 1 >>> g1 += g2 # now g1 contains everything ``` Graph Aggregation - ConjunctiveGraphs and ReadOnlyGraphAggregate within the same store: ```python >>> store = plugin.get("Memory", Store)() >>> g1 = Graph(store) >>> g2 = Graph(store) >>> g3 = Graph(store) >>> stmt1 = BNode() >>> stmt2 = BNode() >>> stmt3 = BNode() >>> g1.add((stmt1, RDF.type, RDF.Statement)) # doctest: +ELLIPSIS )> >>> g1.add((stmt1, RDF.subject, ... URIRef('https://rdflib.github.io/store/ConjunctiveGraph'))) # doctest: +ELLIPSIS )> >>> g1.add((stmt1, RDF.predicate, namespace.RDFS.label)) # doctest: +ELLIPSIS )> >>> g1.add((stmt1, RDF.object, Literal('Conjunctive Graph'))) # doctest: +ELLIPSIS )> >>> g2.add((stmt2, RDF.type, RDF.Statement)) # doctest: +ELLIPSIS )> >>> g2.add((stmt2, RDF.subject, ... URIRef('https://rdflib.github.io/store/ConjunctiveGraph'))) # doctest: +ELLIPSIS )> >>> g2.add((stmt2, RDF.predicate, RDF.type)) # doctest: +ELLIPSIS )> >>> g2.add((stmt2, RDF.object, namespace.RDFS.Class)) # doctest: +ELLIPSIS )> >>> g3.add((stmt3, RDF.type, RDF.Statement)) # doctest: +ELLIPSIS )> >>> g3.add((stmt3, RDF.subject, ... URIRef('https://rdflib.github.io/store/ConjunctiveGraph'))) # doctest: +ELLIPSIS )> >>> g3.add((stmt3, RDF.predicate, namespace.RDFS.comment)) # doctest: +ELLIPSIS )> >>> g3.add((stmt3, RDF.object, Literal( ... 'The top-level aggregate graph - The sum ' + ... 'of all named graphs within a Store'))) # doctest: +ELLIPSIS )> >>> len(list(ConjunctiveGraph(store).subjects(RDF.type, RDF.Statement))) 3 >>> len(list(ReadOnlyGraphAggregate([g1,g2]).subjects( ... RDF.type, RDF.Statement))) 2 ``` ConjunctiveGraphs have a [`quads()`][rdflib.graph.ConjunctiveGraph.quads] method which returns quads instead of triples, where the fourth item is the Graph (or subclass thereof) instance in which the triple was asserted: ```python >>> uniqueGraphNames = set( ... [graph.identifier for s, p, o, graph in ConjunctiveGraph(store ... ).quads((None, RDF.predicate, None))]) >>> len(uniqueGraphNames) 3 >>> unionGraph = ReadOnlyGraphAggregate([g1, g2]) >>> uniqueGraphNames = set( ... [graph.identifier for s, p, o, graph in unionGraph.quads( ... (None, RDF.predicate, None))]) >>> len(uniqueGraphNames) 2 ``` Parsing N3 from a string: ```python >>> g2 = Graph() >>> src = ''' ... @prefix rdf: . ... @prefix rdfs: . ... [ a rdf:Statement ; ... rdf:subject ; ... rdf:predicate rdfs:label; ... rdf:object "Conjunctive Graph" ] . ... ''' >>> g2 = g2.parse(data=src, format="n3") >>> print(len(g2)) 4 ``` Using Namespace class: ```python >>> RDFLib = Namespace("https://rdflib.github.io/") >>> RDFLib.ConjunctiveGraph rdflib.term.URIRef('https://rdflib.github.io/ConjunctiveGraph') >>> RDFLib["Graph"] rdflib.term.URIRef('https://rdflib.github.io/Graph') ``` """ from __future__ import annotations import logging import pathlib import random import warnings from io import BytesIO from typing import ( IO, TYPE_CHECKING, Any, BinaryIO, Callable, Dict, Generator, Iterable, List, Mapping, NoReturn, Optional, Set, TextIO, Tuple, Type, TypeVar, Union, cast, overload, ) from urllib.parse import urlparse from urllib.request import url2pathname import rdflib.exceptions as exceptions import rdflib.namespace as namespace # noqa: F401 # This is here because it is used in a docstring. import rdflib.plugin as plugin import rdflib.query as query import rdflib.util # avoid circular dependency from rdflib.collection import Collection from rdflib.exceptions import ParserError from rdflib.namespace import RDF, Namespace, NamespaceManager from rdflib.parser import InputSource, Parser, create_input_source from rdflib.paths import Path from rdflib.resource import Resource from rdflib.serializer import Serializer from rdflib.store import Store from rdflib.term import ( BNode, Genid, IdentifiedNode, Identifier, Literal, Node, RDFLibGenid, URIRef, ) if TYPE_CHECKING: import typing_extensions as te import rdflib.query from rdflib.plugins.sparql.sparql import Query, Update _SubjectType = Node _PredicateType = Node _ObjectType = Node _ContextIdentifierType = IdentifiedNode _TripleType = Tuple["_SubjectType", "_PredicateType", "_ObjectType"] _QuadType = Tuple["_SubjectType", "_PredicateType", "_ObjectType", "_ContextType"] _OptionalQuadType = Tuple[ "_SubjectType", "_PredicateType", "_ObjectType", Optional["_ContextType"] ] _TripleOrOptionalQuadType = Union["_TripleType", "_OptionalQuadType"] _OptionalIdentifiedQuadType = Tuple[ "_SubjectType", "_PredicateType", "_ObjectType", Optional["_ContextIdentifierType"] ] _TriplePatternType = Tuple[ Optional["_SubjectType"], Optional["_PredicateType"], Optional["_ObjectType"] ] _TriplePathPatternType = Tuple[Optional["_SubjectType"], Path, Optional["_ObjectType"]] _QuadPatternType = Tuple[ Optional["_SubjectType"], Optional["_PredicateType"], Optional["_ObjectType"], Optional["_ContextType"], ] _QuadPathPatternType = Tuple[ Optional["_SubjectType"], Path, Optional["_ObjectType"], Optional["_ContextType"], ] _TripleOrQuadPatternType = Union["_TriplePatternType", "_QuadPatternType"] _TripleOrQuadPathPatternType = Union["_TriplePathPatternType", "_QuadPathPatternType"] _TripleSelectorType = Tuple[ Optional["_SubjectType"], Optional[Union["Path", "_PredicateType"]], Optional["_ObjectType"], ] _QuadSelectorType = Tuple[ Optional["_SubjectType"], Optional[Union["Path", "_PredicateType"]], Optional["_ObjectType"], Optional["_ContextType"], ] _TripleOrQuadSelectorType = Union["_TripleSelectorType", "_QuadSelectorType"] _TriplePathType = Tuple["_SubjectType", Path, "_ObjectType"] _TripleOrTriplePathType = Union["_TripleType", "_TriplePathType"] _TripleChoiceType = Union[ Tuple[List[_SubjectType], Optional[_PredicateType], Optional[_ObjectType]], Tuple[Optional[_SubjectType], List[_PredicateType], Optional[_ObjectType]], Tuple[Optional[_SubjectType], Optional[_PredicateType], List[_ObjectType]], ] _GraphT = TypeVar("_GraphT", bound="Graph") _ConjunctiveGraphT = TypeVar("_ConjunctiveGraphT", bound="ConjunctiveGraph") _DatasetT = TypeVar("_DatasetT", bound="Dataset") # type error: Function "Type[Literal]" could always be true in boolean contex assert Literal # type: ignore[truthy-function] # avoid warning # type error: Function "Type[Namespace]" could always be true in boolean context assert Namespace # type: ignore[truthy-function] # avoid warning if TYPE_CHECKING: from rdflib._type_checking import _NamespaceSetString logger = logging.getLogger(__name__) __all__ = [ "Graph", "ConjunctiveGraph", "QuotedGraph", "Seq", "ModificationException", "Dataset", "UnSupportedAggregateOperation", "ReadOnlyGraphAggregate", "BatchAddGraph", "_ConjunctiveGraphT", "_ContextIdentifierType", "_DatasetT", "_GraphT", "_ObjectType", "_OptionalIdentifiedQuadType", "_OptionalQuadType", "_PredicateType", "_QuadPathPatternType", "_QuadPatternType", "_QuadSelectorType", "_QuadType", "_SubjectType", "_TripleOrOptionalQuadType", "_TripleOrTriplePathType", "_TripleOrQuadPathPatternType", "_TripleOrQuadPatternType", "_TripleOrQuadSelectorType", "_TriplePathPatternType", "_TriplePathType", "_TriplePatternType", "_TripleSelectorType", "_TripleType", ] # : Transitive closure arg type. _TCArgT = TypeVar("_TCArgT") # Graph is a node because technically a formula-aware graph # take a Graph as subject or object, but we usually use QuotedGraph for that. class Graph(Node): """An RDF Graph: a Python object containing nodes and relations between them as RDF 'triples'. This is the central RDFLib object class and Graph objects are almost always present in all uses of RDFLib. Example: The basic use is to create a Graph and iterate through or query its content: ```python >>> from rdflib import Graph, URIRef >>> g = Graph() >>> g.add(( ... URIRef("http://example.com/s1"), # subject ... URIRef("http://example.com/p1"), # predicate ... URIRef("http://example.com/o1"), # object ... )) # doctest: +ELLIPSIS )> >>> g.add(( ... URIRef("http://example.com/s2"), # subject ... URIRef("http://example.com/p2"), # predicate ... URIRef("http://example.com/o2"), # object ... )) # doctest: +ELLIPSIS )> >>> for triple in sorted(g): # simple looping ... print(triple) (rdflib.term.URIRef('http://example.com/s1'), rdflib.term.URIRef('http://example.com/p1'), rdflib.term.URIRef('http://example.com/o1')) (rdflib.term.URIRef('http://example.com/s2'), rdflib.term.URIRef('http://example.com/p2'), rdflib.term.URIRef('http://example.com/o2')) >>> # get the object of the triple with subject s1 and predicate p1 >>> o = g.value( ... subject=URIRef("http://example.com/s1"), ... predicate=URIRef("http://example.com/p1") ... ) ``` Args: store: The constructor accepts one argument, the "store" that will be used to store the graph data with the default being the [`Memory`][rdflib.plugins.stores.memory.Memory] (in memory) Store. Other Stores that persist content to disk using various file databases or Stores that use remote servers (SPARQL systems) are supported. All [builtin storetypes][rdflib.plugins.stores] can be accessed via their registered names. Other Stores not shipped with RDFLib can be added as plugins, such as [HDT](https://github.com/rdflib/rdflib-hdt/). Registration of external plugins is described in [`rdflib.plugin`][rdflib.plugin]. Stores can be context-aware or unaware. Unaware stores take up (some) less space but cannot support features that require context, such as true merging/demerging of sub-graphs and provenance. Even if used with a context-aware store, Graph will only expose the quads which belong to the default graph. To access the rest of the data the `Dataset` class can be used instead. The Graph constructor can take an identifier which identifies the Graph by name. If none is given, the graph is assigned a BNode for its identifier. For more on Named Graphs, see the RDFLib `Dataset` class and the TriG Specification, . identifier: identifier of the graph itself namespace_manager: Used namespace manager. Create with bind_namespaces if `None`. base: Base used for [URIs][rdflib.term.URIRef] bind_namespaces: Used bind_namespaces for namespace_manager Is only used, when no namespace_manager is provided. """ context_aware: bool formula_aware: bool default_union: bool base: Optional[str] def __init__( self, store: Union[Store, str] = "default", identifier: Optional[Union[_ContextIdentifierType, str]] = None, namespace_manager: Optional[NamespaceManager] = None, base: Optional[str] = None, bind_namespaces: _NamespaceSetString = "rdflib", ): super(Graph, self).__init__() self.base = base self.__identifier: _ContextIdentifierType self.__identifier = identifier or BNode() # type: ignore[assignment] if not isinstance(self.__identifier, IdentifiedNode): self.__identifier = URIRef(self.__identifier) # type: ignore[unreachable] self.__store: Store if not isinstance(store, Store): # TODO: error handling self.__store = store = plugin.get(store, Store)() else: self.__store = store self.__namespace_manager = namespace_manager self._bind_namespaces = bind_namespaces self.context_aware = False self.formula_aware = False self.default_union = False @property def store(self) -> Store: return self.__store @property def identifier(self) -> _ContextIdentifierType: return self.__identifier @property def namespace_manager(self) -> NamespaceManager: """ this graph's namespace-manager """ if self.__namespace_manager is None: self.__namespace_manager = NamespaceManager(self, self._bind_namespaces) return self.__namespace_manager @namespace_manager.setter def namespace_manager(self, nm: NamespaceManager) -> None: self.__namespace_manager = nm def __repr__(self) -> str: return "" % (self.identifier, type(self)) def __str__(self) -> str: if isinstance(self.identifier, URIRef): return ( "%s a rdfg:Graph;rdflib:storage " + "[a rdflib:Store;rdfs:label '%s']." ) % (self.identifier.n3(), self.store.__class__.__name__) else: return ( "[a rdfg:Graph;rdflib:storage " + "[a rdflib:Store;rdfs:label '%s']]." ) % self.store.__class__.__name__ def toPython(self: _GraphT) -> _GraphT: # noqa: N802 return self def destroy(self: _GraphT, configuration: str) -> _GraphT: """Destroy the store identified by `configuration` if supported""" self.__store.destroy(configuration) return self # Transactional interfaces (optional) def commit(self: _GraphT) -> _GraphT: """Commits active transactions""" self.__store.commit() return self def rollback(self: _GraphT) -> _GraphT: """Rollback active transactions""" self.__store.rollback() return self def open( self, configuration: Union[str, tuple[str, str]], create: bool = False ) -> Optional[int]: """Open the graph store Might be necessary for stores that require opening a connection to a database or acquiring some resource. """ return self.__store.open(configuration, create) def close(self, commit_pending_transaction: bool = False) -> None: """Close the graph store Might be necessary for stores that require closing a connection to a database or releasing some resource. """ return self.__store.close(commit_pending_transaction=commit_pending_transaction) def add(self: _GraphT, triple: _TripleType) -> _GraphT: """Add a triple with self as context. Args: triple: The triple to add to the graph. Returns: The graph instance. """ s, p, o = triple assert isinstance(s, Node), "Subject %s must be an rdflib term" % (s,) assert isinstance(p, Node), "Predicate %s must be an rdflib term" % (p,) assert isinstance(o, Node), "Object %s must be an rdflib term" % (o,) self.__store.add((s, p, o), self, quoted=False) return self def addN(self: _GraphT, quads: Iterable[_QuadType]) -> _GraphT: # noqa: N802 """Add a sequence of triple with context""" self.__store.addN( (s, p, o, c) for s, p, o, c in quads if isinstance(c, Graph) and c.identifier is self.identifier and _assertnode(s, p, o) ) return self def remove(self: _GraphT, triple: _TriplePatternType) -> _GraphT: """Remove a triple from the graph If the triple does not provide a context attribute, removes the triple from all contexts. """ self.__store.remove(triple, context=self) return self @overload def triples( self, triple: _TriplePatternType, ) -> Generator[_TripleType, None, None]: ... @overload def triples( self, triple: _TriplePathPatternType, ) -> Generator[_TriplePathType, None, None]: ... @overload def triples( self, triple: _TripleSelectorType, ) -> Generator[_TripleOrTriplePathType, None, None]: ... def triples( self, triple: _TripleSelectorType, ) -> Generator[_TripleOrTriplePathType, None, None]: """Generator over the triple store. Returns triples that match the given triple pattern. If the triple pattern does not provide a context, all contexts will be searched. Args: triple: A triple pattern where each component can be a specific value or None as a wildcard. The predicate can also be a path expression. Yields: Triples matching the given pattern. """ s, p, o = triple if isinstance(p, Path): for _s, _o in p.eval(self, s, o): yield _s, p, _o else: for (_s, _p, _o), cg in self.__store.triples((s, p, o), context=self): yield _s, _p, _o def __getitem__(self, item): """ A graph can be "sliced" as a shortcut for the triples method The python slice syntax is (ab)used for specifying triples. A generator over matches is returned, the returned tuples include only the parts not given ```python >>> import rdflib >>> g = rdflib.Graph() >>> g.add((rdflib.URIRef("urn:bob"), namespace.RDFS.label, rdflib.Literal("Bob"))) # doctest: +ELLIPSIS )> >>> list(g[rdflib.URIRef("urn:bob")]) # all triples about bob [(rdflib.term.URIRef('http://www.w3.org/2000/01/rdf-schema#label'), rdflib.term.Literal('Bob'))] >>> list(g[:namespace.RDFS.label]) # all label triples [(rdflib.term.URIRef('urn:bob'), rdflib.term.Literal('Bob'))] >>> list(g[::rdflib.Literal("Bob")]) # all triples with bob as object [(rdflib.term.URIRef('urn:bob'), rdflib.term.URIRef('http://www.w3.org/2000/01/rdf-schema#label'))] ``` Combined with SPARQL paths, more complex queries can be written concisely: - Name of all Bobs friends: `g[bob : FOAF.knows/FOAF.name ]` - Some label for Bob: `g[bob : DC.title|FOAF.name|RDFS.label]` - All friends and friends of friends of Bob: `g[bob : FOAF.knows * "+"]` - etc. !!! example "New in version 4.0" """ if isinstance(item, slice): s, p, o = item.start, item.stop, item.step if s is None and p is None and o is None: return self.triples((s, p, o)) elif s is None and p is None: # type error: Argument 1 to "subject_predicates" of "Graph" has incompatible type "Union[int, Any]"; expected "Optional[Node]" return self.subject_predicates(o) # type: ignore[arg-type] elif s is None and o is None: # type error: Argument 1 to "subject_objects" of "Graph" has incompatible type "Union[int, Any]"; expected "Union[Path, Node, None]" return self.subject_objects(p) # type: ignore[arg-type] elif p is None and o is None: # type error: Argument 1 to "predicate_objects" of "Graph" has incompatible type "Union[int, Any]"; expected "Optional[Node]" return self.predicate_objects(s) # type: ignore[arg-type] elif s is None: # type error: Argument 1 to "subjects" of "Graph" has incompatible type "Union[int, Any]"; expected "Union[Path, Node, None]" # Argument 2 to "subjects" of "Graph" has incompatible type "Union[int, Any]"; expected "Union[Node, List[Node], None]" return self.subjects(p, o) # type: ignore[arg-type] elif p is None: # type error: Argument 1 to "predicates" of "Graph" has incompatible type "Union[int, Any]"; expected "Optional[Node]" # Argument 2 to "predicates" of "Graph" has incompatible type "Union[int, Any]"; expected "Optional[Node]" return self.predicates(s, o) # type: ignore[arg-type] elif o is None: # type error: Argument 1 to "objects" of "Graph" has incompatible type "Union[int, Any]"; expected "Union[Node, List[Node], None]" # Argument 2 to "objects" of "Graph" has incompatible type "Union[int, Any]"; expected "Union[Path, Node, None]" return self.objects(s, p) # type: ignore[arg-type] else: # type error: Unsupported operand types for in ("Tuple[Union[int, Any], Union[int, Any], Union[int, Any]]" and "Graph") # all given return (s, p, o) in self # type: ignore[operator] elif isinstance(item, (Path, Node)): # type error: Argument 1 to "predicate_objects" of "Graph" has incompatible type "Union[Path, Node]"; expected "Optional[Node]" return self.predicate_objects(item) # type: ignore[arg-type] else: raise TypeError( "You can only index a graph by a single rdflib term or path, or a slice of rdflib terms." ) def __len__(self) -> int: """Returns the number of triples in the graph. If context is specified then the number of triples in the context is returned instead. Returns: The number of triples in the graph. """ # type error: Unexpected keyword argument "context" for "__len__" of "Store" return self.__store.__len__(context=self) # type: ignore[call-arg] def __iter__(self) -> Generator[_TripleType, None, None]: """Iterates over all triples in the store. Returns: A generator yielding all triples in the store. """ return self.triples((None, None, None)) def __contains__(self, triple: _TripleSelectorType) -> bool: """Support for 'triple in graph' syntax. Args: triple: The triple pattern to check for. Returns: True if the triple pattern exists in the graph, False otherwise. """ for triple in self.triples(triple): return True return False def __hash__(self) -> int: return hash(self.identifier) def __cmp__(self, other) -> int: if other is None: return -1 elif isinstance(other, Graph): return (self.identifier > other.identifier) - ( self.identifier < other.identifier ) else: # Note if None is considered equivalent to owl:Nothing # Then perhaps a graph with length 0 should be considered # equivalent to None (if compared to it)? return 1 def __eq__(self, other) -> bool: return isinstance(other, Graph) and self.identifier == other.identifier def __lt__(self, other) -> bool: return (other is None) or ( isinstance(other, Graph) and self.identifier < other.identifier ) def __le__(self, other: Graph) -> bool: return self < other or self == other def __gt__(self, other) -> bool: return (isinstance(other, Graph) and self.identifier > other.identifier) or ( other is not None ) def __ge__(self, other: Graph) -> bool: return self > other or self == other def __iadd__(self: _GraphT, other: Iterable[_TripleType]) -> _GraphT: """Add all triples in Graph other to Graph. BNode IDs are not changed.""" self.addN((s, p, o, self) for s, p, o in other) return self def __isub__(self: _GraphT, other: Iterable[_TripleType]) -> _GraphT: """Subtract all triples in Graph other from Graph. BNode IDs are not changed.""" for triple in other: self.remove(triple) return self def __add__(self, other: Graph) -> Graph: """Set-theoretic union BNode IDs are not changed.""" try: retval = type(self)() except TypeError: retval = Graph() for prefix, uri in set(list(self.namespaces()) + list(other.namespaces())): retval.bind(prefix, uri) for x in self: retval.add(x) for y in other: retval.add(y) return retval def __mul__(self, other: Graph) -> Graph: """Set-theoretic intersection. BNode IDs are not changed.""" try: retval = type(self)() except TypeError: retval = Graph() for x in other: if x in self: retval.add(x) return retval def __sub__(self, other: Graph) -> Graph: """Set-theoretic difference. BNode IDs are not changed.""" try: retval = type(self)() except TypeError: retval = Graph() for x in self: if x not in other: retval.add(x) return retval def __xor__(self, other: Graph) -> Graph: """Set-theoretic XOR. BNode IDs are not changed.""" return (self - other) + (other - self) __or__ = __add__ __and__ = __mul__ # Conv. methods def set( self: _GraphT, triple: Tuple[_SubjectType, _PredicateType, _ObjectType] ) -> _GraphT: """Convenience method to update the value of object Remove any existing triples for subject and predicate before adding (subject, predicate, object). """ (subject, predicate, object_) = triple assert ( subject is not None ), "s can't be None in .set([s,p,o]), as it would remove (*, p, *)" assert ( predicate is not None ), "p can't be None in .set([s,p,o]), as it would remove (s, *, *)" self.remove((subject, predicate, None)) self.add((subject, predicate, object_)) return self def subjects( self, predicate: Union[None, Path, _PredicateType] = None, object: Optional[Union[_ObjectType, List[_ObjectType]]] = None, unique: bool = False, ) -> Generator[_SubjectType, None, None]: """A generator of (optionally unique) subjects with the given predicate and object(s) Args: predicate: A specific predicate to match or None to match any predicate. object: A specific object or list of objects to match or None to match any object. unique: If True, only yield unique subjects. """ # if the object is a list of Nodes, yield results from subject() call for each if isinstance(object, list): for obj in object: for s in self.subjects(predicate, obj, unique): yield s else: if not unique: for s, p, o in self.triples((None, predicate, object)): yield s else: subs = set() for s, p, o in self.triples((None, predicate, object)): if s not in subs: yield s try: subs.add(s) except MemoryError as e: logger.error( f"{e}. Consider not setting parameter 'unique' to True" ) raise def predicates( self, subject: Optional[_SubjectType] = None, object: Optional[_ObjectType] = None, unique: bool = False, ) -> Generator[_PredicateType, None, None]: """Generate predicates with the given subject and object. Args: subject: A specific subject to match or None to match any subject. object: A specific object to match or None to match any object. unique: If True, only yield unique predicates. Yields: Predicates matching the given subject and object. """ if not unique: for s, p, o in self.triples((subject, None, object)): yield p else: preds = set() for s, p, o in self.triples((subject, None, object)): if p not in preds: yield p try: preds.add(p) except MemoryError as e: logger.error( f"{e}. Consider not setting parameter 'unique' to True" ) raise def objects( self, subject: Optional[Union[_SubjectType, List[_SubjectType]]] = None, predicate: Union[None, Path, _PredicateType] = None, unique: bool = False, ) -> Generator[_ObjectType, None, None]: """A generator of (optionally unique) objects with the given subject(s) and predicate Args: subject: A specific subject or a list of subjects to match or None to match any subject. predicate: A specific predicate to match or None to match any predicate. unique: If True, only yield unique objects. Yields: Objects matching the given subject and predicate. """ if isinstance(subject, list): for subj in subject: for o in self.objects(subj, predicate, unique): yield o else: if not unique: for s, p, o in self.triples((subject, predicate, None)): yield o else: objs = set() for s, p, o in self.triples((subject, predicate, None)): if o not in objs: yield o try: objs.add(o) except MemoryError as e: logger.error( f"{e}. Consider not setting parameter 'unique' to True" ) raise def subject_predicates( self, object: Optional[_ObjectType] = None, unique: bool = False ) -> Generator[Tuple[_SubjectType, _PredicateType], None, None]: """A generator of (optionally unique) (subject, predicate) tuples for the given object""" if not unique: for s, p, o in self.triples((None, None, object)): yield s, p else: subj_preds = set() for s, p, o in self.triples((None, None, object)): if (s, p) not in subj_preds: yield s, p try: subj_preds.add((s, p)) except MemoryError as e: logger.error( f"{e}. Consider not setting parameter 'unique' to True" ) raise def subject_objects( self, predicate: Union[None, Path, _PredicateType] = None, unique: bool = False, ) -> Generator[Tuple[_SubjectType, _ObjectType], None, None]: """A generator of (optionally unique) (subject, object) tuples for the given predicate""" if not unique: for s, p, o in self.triples((None, predicate, None)): yield s, o else: subj_objs = set() for s, p, o in self.triples((None, predicate, None)): if (s, o) not in subj_objs: yield s, o try: subj_objs.add((s, o)) except MemoryError as e: logger.error( f"{e}. Consider not setting parameter 'unique' to True" ) raise def predicate_objects( self, subject: Optional[_SubjectType] = None, unique: bool = False ) -> Generator[Tuple[_PredicateType, _ObjectType], None, None]: """A generator of (optionally unique) (predicate, object) tuples for the given subject""" if not unique: for s, p, o in self.triples((subject, None, None)): yield p, o else: pred_objs = set() for s, p, o in self.triples((subject, None, None)): if (p, o) not in pred_objs: yield p, o try: pred_objs.add((p, o)) except MemoryError as e: logger.error( f"{e}. Consider not setting parameter 'unique' to True" ) raise def triples_choices( self, triple: _TripleChoiceType, context: Optional[_ContextType] = None, ) -> Generator[_TripleType, None, None]: subject, predicate, object_ = triple # type error: Argument 1 to "triples_choices" of "Store" has incompatible type "Tuple[Union[List[Node], Node], Union[Node, List[Node]], Union[Node, List[Node]]]"; expected "Union[Tuple[List[Node], Node, Node], Tuple[Node, List[Node], Node], Tuple[Node, Node, List[Node]]]" # type error note: unpacking discards type info for (s, p, o), cg in self.store.triples_choices( (subject, predicate, object_), context=self # type: ignore[arg-type] ): yield s, p, o @overload def value( self, subject: None = ..., predicate: None = ..., object: Optional[_ObjectType] = ..., default: Optional[Node] = ..., any: bool = ..., ) -> None: ... @overload def value( self, subject: Optional[_SubjectType] = ..., predicate: None = ..., object: None = ..., default: Optional[Node] = ..., any: bool = ..., ) -> None: ... @overload def value( self, subject: None = ..., predicate: Optional[_PredicateType] = ..., object: None = ..., default: Optional[Node] = ..., any: bool = ..., ) -> None: ... @overload def value( self, subject: Optional[_SubjectType] = ..., predicate: Optional[_PredicateType] = ..., object: Optional[_ObjectType] = ..., default: Optional[Node] = ..., any: bool = ..., ) -> Optional[Node]: ... def value( self, subject: Optional[_SubjectType] = None, predicate: Optional[_PredicateType] = RDF.value, object: Optional[_ObjectType] = None, default: Optional[Node] = None, any: bool = True, ) -> Optional[Node]: """Get a value for a pair of two criteria Exactly one of subject, predicate, object must be None. Useful if one knows that there may only be one value. It is one of those situations that occur a lot, hence this 'macro' like utility Args: subject: Subject of the triple pattern, exactly one of subject, predicate, object must be None predicate: Predicate of the triple pattern, exactly one of subject, predicate, object must be None object: Object of the triple pattern, exactly one of subject, predicate, object must be None default: Value to be returned if no values found any: If True, return any value in the case there is more than one, else, raise UniquenessError """ retval = default if ( (subject is None and predicate is None) or (subject is None and object is None) or (predicate is None and object is None) ): return None if object is None: values = self.objects(subject, predicate) if subject is None: values = self.subjects(predicate, object) if predicate is None: values = self.predicates(subject, object) try: retval = next(values) except StopIteration: retval = default else: if any is False: try: next(values) msg = ( "While trying to find a value for (%s, %s, %s) the" " following multiple values where found:\n" % (subject, predicate, object) ) triples = self.store.triples((subject, predicate, object), None) for (s, p, o), contexts in triples: msg += "(%s, %s, %s)\n (contexts: %s)\n" % ( s, p, o, list(contexts), ) raise exceptions.UniquenessError(msg) except StopIteration: pass return retval def items(self, list: Node) -> Generator[Node, None, None]: """Generator over all items in the resource specified by list Args: list: An RDF collection. """ chain = set([list]) while list: item = self.value(list, RDF.first) if item is not None: yield item # type error: Incompatible types in assignment (expression has type "Optional[Node]", variable has type "Node") list = self.value(list, RDF.rest) # type: ignore[assignment] if list in chain: raise ValueError("List contains a recursive rdf:rest reference") chain.add(list) def transitiveClosure( # noqa: N802 self, func: Callable[[_TCArgT, Graph], Iterable[_TCArgT]], arg: _TCArgT, seen: Optional[Dict[_TCArgT, int]] = None, ): """Generates transitive closure of a user-defined function against the graph ```python from rdflib.collection import Collection g = Graph() a = BNode("foo") b = BNode("bar") c = BNode("baz") g.add((a,RDF.first,RDF.type)) g.add((a,RDF.rest,b)) g.add((b,RDF.first,namespace.RDFS.label)) g.add((b,RDF.rest,c)) g.add((c,RDF.first,namespace.RDFS.comment)) g.add((c,RDF.rest,RDF.nil)) def topList(node,g): for s in g.subjects(RDF.rest, node): yield s def reverseList(node,g): for f in g.objects(node, RDF.first): print(f) for s in g.subjects(RDF.rest, node): yield s [rt for rt in g.transitiveClosure( topList,RDF.nil)] # [rdflib.term.BNode('baz'), # rdflib.term.BNode('bar'), # rdflib.term.BNode('foo')] [rt for rt in g.transitiveClosure( reverseList,RDF.nil)] # http://www.w3.org/2000/01/rdf-schema#comment # http://www.w3.org/2000/01/rdf-schema#label # http://www.w3.org/1999/02/22-rdf-syntax-ns#type # [rdflib.term.BNode('baz'), # rdflib.term.BNode('bar'), # rdflib.term.BNode('foo')] ``` Args: func: A function that generates a sequence of nodes arg: The starting node seen: A dict of visited nodes """ if seen is None: seen = {} elif arg in seen: return seen[arg] = 1 for rt in func(arg, self): yield rt for rt_2 in self.transitiveClosure(func, rt, seen): yield rt_2 def transitive_objects( self, subject: Optional[_SubjectType], predicate: Optional[_PredicateType], remember: Optional[Dict[Optional[_SubjectType], int]] = None, ) -> Generator[Optional[_SubjectType], None, None]: """Transitively generate objects for the ``predicate`` relationship Generated objects belong to the depth first transitive closure of the `predicate` relationship starting at `subject`. Args: subject: The subject to start the transitive closure from predicate: The predicate to follow remember: A dict of visited nodes """ if remember is None: remember = {} if subject in remember: return remember[subject] = 1 yield subject for object in self.objects(subject, predicate): for o in self.transitive_objects(object, predicate, remember): yield o def transitive_subjects( self, predicate: Optional[_PredicateType], object: Optional[_ObjectType], remember: Optional[Dict[Optional[_ObjectType], int]] = None, ) -> Generator[Optional[_ObjectType], None, None]: """Transitively generate subjects for the ``predicate`` relationship Generated subjects belong to the depth first transitive closure of the `predicate` relationship starting at `object`. Args: predicate: The predicate to follow object: The object to start the transitive closure from remember: A dict of visited nodes """ if remember is None: remember = {} if object in remember: return remember[object] = 1 yield object for subject in self.subjects(predicate, object): for s in self.transitive_subjects(predicate, subject, remember): yield s def qname(self, uri: str) -> str: return self.namespace_manager.qname(uri) def compute_qname(self, uri: str, generate: bool = True) -> Tuple[str, URIRef, str]: return self.namespace_manager.compute_qname(uri, generate) def bind( self, prefix: Optional[str], namespace: Any, # noqa: F811 override: bool = True, replace: bool = False, ) -> None: """Bind prefix to namespace If override is True will bind namespace to given prefix even if namespace was already bound to a different prefix. if replace, replace any existing prefix with the new namespace Args: prefix: The prefix to bind namespace: The namespace to bind the prefix to override: If True, override any existing prefix binding replace: If True, replace any existing namespace binding Example: ```python graph.bind("foaf", "http://xmlns.com/foaf/0.1/") ``` """ # TODO FIXME: This method's behaviour should be simplified and made # more robust. If the method cannot do what it is asked it should raise # an exception, it is also unclear why this method has all the # different modes. It seems to just make it more complex to use, maybe # it should be clarified when someone will need to use override=False # and replace=False. And also why silent failure here is preferred over # raising an exception. return self.namespace_manager.bind( prefix, namespace, override=override, replace=replace ) def namespaces(self) -> Generator[Tuple[str, URIRef], None, None]: """Generator over all the prefix, namespace tuples Returns: Generator yielding prefix, namespace tuples """ for prefix, namespace in self.namespace_manager.namespaces(): # noqa: F402 yield prefix, namespace def absolutize(self, uri: str, defrag: int = 1) -> URIRef: """Turn uri into an absolute URI if it's not one already""" return self.namespace_manager.absolutize(uri, defrag) # no destination and non-None positional encoding @overload def serialize( self, destination: None, format: str, base: Optional[str], encoding: str, **args: Any, ) -> bytes: ... # no destination and non-None keyword encoding @overload def serialize( self, destination: None = ..., format: str = ..., base: Optional[str] = ..., *, encoding: str, **args: Any, ) -> bytes: ... # no destination and None encoding @overload def serialize( self, destination: None = ..., format: str = ..., base: Optional[str] = ..., encoding: None = ..., **args: Any, ) -> str: ... # non-None destination @overload def serialize( self, destination: Union[str, pathlib.PurePath, IO[bytes]], format: str = ..., base: Optional[str] = ..., encoding: Optional[str] = ..., **args: Any, ) -> Graph: ... # fallback @overload def serialize( self, destination: Optional[Union[str, pathlib.PurePath, IO[bytes]]] = ..., format: str = ..., base: Optional[str] = ..., encoding: Optional[str] = ..., **args: Any, ) -> Union[bytes, str, Graph]: ... def serialize( self: _GraphT, destination: Optional[Union[str, pathlib.PurePath, IO[bytes]]] = None, format: str = "turtle", base: Optional[str] = None, encoding: Optional[str] = None, **args: Any, ) -> Union[bytes, str, _GraphT]: """Serialize the graph. Args: destination: The destination to serialize the graph to. This can be a path as a string or pathlib.PurePath object, or it can be an IO[bytes] like object. If this parameter is not supplied the serialized graph will be returned. format: The format that the output should be written in. This value references a Serializer plugin. Format support is managed with [plugins][rdflib.plugin]. Defaults to "turtle" and some other formats are builtin, like "xml" and "trix". See also [serialize module][rdflib.plugins.parsers]. base: The base IRI for formats that support it. For the turtle format this will be used as the @base directive. encoding: Encoding of output. args: Additional arguments to pass to the Serializer that will be used. Returns: The serialized graph if `destination` is None. The serialized graph is returned as str if no encoding is specified, and as bytes if an encoding is specified. self (i.e. the Graph instance) if `destination` is not None. """ # if base is not given as attribute use the base set for the graph if base is None: base = self.base serializer = plugin.get(format, Serializer)(self) stream: IO[bytes] if destination is None: stream = BytesIO() if encoding is None: serializer.serialize(stream, base=base, encoding="utf-8", **args) return stream.getvalue().decode("utf-8") else: serializer.serialize(stream, base=base, encoding=encoding, **args) return stream.getvalue() if hasattr(destination, "write"): stream = cast(IO[bytes], destination) serializer.serialize(stream, base=base, encoding=encoding, **args) else: if isinstance(destination, pathlib.PurePath): os_path = str(destination) else: location = cast(str, destination) scheme, netloc, path, params, _query, fragment = urlparse(location) if scheme == "file": if netloc != "": raise ValueError( f"the file URI {location!r} has an authority component which is not supported" ) os_path = url2pathname(path) else: os_path = location with open(os_path, "wb") as stream: serializer.serialize(stream, base=base, encoding=encoding, **args) return self def print( self, format: str = "turtle", encoding: str = "utf-8", out: Optional[TextIO] = None, ) -> None: print( self.serialize(None, format=format, encoding=encoding).decode(encoding), file=out, flush=True, ) def parse( self, source: Optional[ Union[IO[bytes], TextIO, InputSource, str, bytes, pathlib.PurePath] ] = None, publicID: Optional[str] = None, # noqa: N803 format: Optional[str] = None, location: Optional[str] = None, file: Optional[Union[BinaryIO, TextIO]] = None, data: Optional[Union[str, bytes]] = None, **args: Any, ) -> Graph: """Parse an RDF source adding the resulting triples to the Graph. The source is specified using one of source, location, file or data. Args: source: An `xml.sax.xmlreader.InputSource`, file-like object, `pathlib.Path` like object, or string. In the case of a string the string is the location of the source. publicID: The logical URI to use as the document base. If None specified the document location is used (at least in the case where there is a document location). This is used as the base URI when resolving relative URIs in the source document, as defined in `IETF RFC 3986 `_, given the source document does not define a base URI. format: Used if format can not be determined from source, e.g. file extension or Media Type. Format support is managed with [plugins][rdflib.plugin]. Available formats are e.g. "turle", "xml", "n3", "nt" and "trix" or see [parser module][rdflib.plugins.parsers]. location: A string indicating the relative or absolute URL of the source. `Graph`'s absolutize method is used if a relative location is specified. file: A file-like object. data: A string containing the data to be parsed. args: Additional arguments to pass to the parser. Returns: self, i.e. the Graph instance. Example: ```python >>> my_data = ''' ... ... ... Example ... This is really just an example. ... ... ... ''' >>> import os, tempfile >>> fd, file_name = tempfile.mkstemp() >>> f = os.fdopen(fd, "w") >>> dummy = f.write(my_data) # Returns num bytes written >>> f.close() >>> g = Graph() >>> result = g.parse(data=my_data, format="application/rdf+xml") >>> len(g) 2 >>> g = Graph() >>> result = g.parse(location=file_name, format="application/rdf+xml") >>> len(g) 2 >>> g = Graph() >>> with open(file_name, "r") as f: ... result = g.parse(f, format="application/rdf+xml") >>> len(g) 2 >>> os.remove(file_name) >>> # default turtle parsing >>> result = g.parse(data=" .") >>> len(g) 3 ``` !!! warning "Caution" This method can access directly or indirectly requested network or file resources, for example, when parsing JSON-LD documents with `@context` directives that point to a network location. When processing untrusted or potentially malicious documents, measures should be taken to restrict network and file access. For information on available security measures, see the RDFLib [Security Considerations](../security_considerations.md) documentation. """ source = create_input_source( source=source, publicID=publicID, location=location, file=file, data=data, format=format, ) if format is None: format = source.content_type could_not_guess_format = False if format is None: if ( hasattr(source, "file") and getattr(source.file, "name", None) and isinstance(source.file.name, str) ): format = rdflib.util.guess_format(source.file.name) if format is None: format = "turtle" could_not_guess_format = True try: parser = plugin.get(format, Parser)() except plugin.PluginException: # Handle the case when a URLInputSource returns RDF but with the headers # as a format that does not exist in the plugin system. # Use guess_format to guess the format based on the input's file suffix. format = rdflib.util.guess_format( source if not isinstance(source, InputSource) else str(source) ) if format is None: raise parser = plugin.get(format, Parser)() try: # TODO FIXME: Parser.parse should have **kwargs argument. parser.parse(source, self, **args) except SyntaxError as se: if could_not_guess_format: raise ParserError( "Could not guess RDF format for %r from file extension so tried Turtle but failed." "You can explicitly specify format using the format argument." % source ) else: raise se finally: if source.auto_close: source.close() return self def query( self, query_object: Union[str, Query], processor: Union[str, query.Processor] = "sparql", result: Union[str, Type[query.Result]] = "sparql", initNs: Optional[Mapping[str, Any]] = None, # noqa: N803 initBindings: Optional[Mapping[str, Identifier]] = None, # noqa: N803 use_store_provided: bool = True, **kwargs: Any, ) -> query.Result: """ Query this graph. Args: query_object: The query string or object to execute. processor: The query processor to use. Default is "sparql". result: The result format to use. Default is "sparql". initNs: Initial namespaces to use for resolving prefixes in the query. If none are given, the namespaces from the graph's namespace manager are used. initBindings: Initial variable bindings to use. A type of 'prepared queries' can be realized by providing these bindings. use_store_provided: Whether to use the store's query method if available. kwargs: Additional arguments to pass to the query processor. Returns: A [`rdflib.query.Result`][`rdflib.query.Result`] instance. !!! warning "Caution" This method can access indirectly requested network endpoints, for example, query processing will attempt to access network endpoints specified in `SERVICE` directives. When processing untrusted or potentially malicious queries, measures should be taken to restrict network and file access. For information on available security measures, see the RDFLib [Security Considerations](../security_considerations.md) documentation. """ initBindings = initBindings or {} # noqa: N806 initNs = initNs or dict(self.namespaces()) # noqa: N806 if self.default_union: query_graph = "__UNION__" elif isinstance(self, ConjunctiveGraph): query_graph = self.default_context.identifier else: query_graph = self.identifier if hasattr(self.store, "query") and use_store_provided: try: return self.store.query( query_object, initNs, initBindings, query_graph, **kwargs, ) except NotImplementedError: pass # store has no own implementation if not isinstance(result, query.Result): result = plugin.get(cast(str, result), query.Result) if not isinstance(processor, query.Processor): processor = plugin.get(processor, query.Processor)(self) # type error: Argument 1 to "Result" has incompatible type "Mapping[str, Any]"; expected "str" return result(processor.query(query_object, initBindings, initNs, **kwargs)) # type: ignore[arg-type] def update( self, update_object: Union[Update, str], processor: Union[str, rdflib.query.UpdateProcessor] = "sparql", initNs: Optional[Mapping[str, Any]] = None, # noqa: N803 initBindings: Optional[Mapping[str, Identifier]] = None, # noqa: N803 use_store_provided: bool = True, **kwargs: Any, ) -> None: """Update this graph with the given update query. Args: update_object: The update query string or object to execute. processor: The update processor to use. Default is "sparql". initNs: Initial namespaces to use for resolving prefixes in the query. If none are given, the namespaces from the graph's namespace manager are used. initBindings: Initial variable bindings to use. use_store_provided: Whether to use the store's update method if available. kwargs: Additional arguments to pass to the update processor. !!! warning "Caution" This method can access indirectly requested network endpoints, for example, query processing will attempt to access network endpoints specified in `SERVICE` directives. When processing untrusted or potentially malicious queries, measures should be taken to restrict network and file access. For information on available security measures, see the RDFLib Security Considerations documentation. """ initBindings = initBindings or {} # noqa: N806 initNs = initNs or dict(self.namespaces()) # noqa: N806 if self.default_union: query_graph = "__UNION__" elif isinstance(self, ConjunctiveGraph): query_graph = self.default_context.identifier else: query_graph = self.identifier if hasattr(self.store, "update") and use_store_provided: try: return self.store.update( update_object, initNs, initBindings, query_graph, **kwargs, ) except NotImplementedError: pass # store has no own implementation if not isinstance(processor, query.UpdateProcessor): processor = plugin.get(processor, query.UpdateProcessor)(self) return processor.update(update_object, initBindings, initNs, **kwargs) def n3(self, namespace_manager: Optional[NamespaceManager] = None) -> str: """Return an n3 identifier for the Graph""" return "[%s]" % self.identifier.n3(namespace_manager=namespace_manager) def __reduce__(self) -> Tuple[Type[Graph], Tuple[Store, _ContextIdentifierType]]: return ( Graph, ( self.store, self.identifier, ), ) def isomorphic(self, other: Graph) -> bool: """Check if this graph is isomorphic to another graph. Performs a basic check if these graphs are the same. If no BNodes are involved, this is accurate. Args: other: The graph to compare with. Returns: True if the graphs are isomorphic, False otherwise. Note: This is only an approximation. See rdflib.compare for a correct implementation of isomorphism checks. """ # TODO: this is only an approximation. if len(self) != len(other): return False for s, p, o in self: if not isinstance(s, BNode) and not isinstance(o, BNode): if not (s, p, o) in other: # noqa: E713 return False for s, p, o in other: if not isinstance(s, BNode) and not isinstance(o, BNode): if not (s, p, o) in self: # noqa: E713 return False # TODO: very well could be a false positive at this point yet. return True def connected(self) -> bool: """Check if the Graph is connected. The Graph is considered undirectional. Returns: True if all nodes have been visited and there are no unvisited nodes left, False otherwise. Note: Performs a search on the Graph, starting from a random node. Then iteratively goes depth-first through the triplets where the node is subject and object. """ all_nodes = list(self.all_nodes()) discovered = [] # take a random one, could also always take the first one, doesn't # really matter. if not all_nodes: return False visiting = [all_nodes[random.randrange(len(all_nodes))]] while visiting: x = visiting.pop() if x not in discovered: discovered.append(x) for new_x in self.objects(subject=x): if new_x not in discovered and new_x not in visiting: visiting.append(new_x) for new_x in self.subjects(object=x): if new_x not in discovered and new_x not in visiting: visiting.append(new_x) # optimisation by only considering length, since no new objects can # be introduced anywhere. if len(all_nodes) == len(discovered): return True else: return False def all_nodes(self) -> Set[Node]: res = set(self.objects()) res.update(self.subjects()) return res def collection(self, identifier: _SubjectType) -> Collection: """Create a new `Collection` instance. Args: identifier: A URIRef or BNode instance. Returns: A new Collection instance. Example: ```python >>> graph = Graph() >>> uri = URIRef("http://example.org/resource") >>> collection = graph.collection(uri) >>> assert isinstance(collection, Collection) >>> assert collection.uri is uri >>> assert collection.graph is graph >>> collection += [ Literal(1), Literal(2) ] ``` """ return Collection(self, identifier) def resource(self, identifier: Union[Node, str]) -> Resource: """Create a new ``Resource`` instance. Args: identifier: A URIRef or BNode instance. Returns: A new Resource instance. Example: ```python >>> graph = Graph() >>> uri = URIRef("http://example.org/resource") >>> resource = graph.resource(uri) >>> assert isinstance(resource, Resource) >>> assert resource.identifier is uri >>> assert resource.graph is graph ``` """ if not isinstance(identifier, Node): identifier = URIRef(identifier) return Resource(self, identifier) def _process_skolem_tuples( self, target: Graph, func: Callable[[_TripleType], _TripleType] ) -> None: for t in self.triples((None, None, None)): target.add(func(t)) def skolemize( self, new_graph: Optional[Graph] = None, bnode: Optional[BNode] = None, authority: Optional[str] = None, basepath: Optional[str] = None, ) -> Graph: def do_skolemize(bnode: BNode, t: _TripleType) -> _TripleType: (s, p, o) = t if s == bnode: if TYPE_CHECKING: assert isinstance(s, BNode) s = s.skolemize(authority=authority, basepath=basepath) if o == bnode: if TYPE_CHECKING: assert isinstance(o, BNode) o = o.skolemize(authority=authority, basepath=basepath) return s, p, o def do_skolemize2(t: _TripleType) -> _TripleType: (s, p, o) = t if isinstance(s, BNode): s = s.skolemize(authority=authority, basepath=basepath) if isinstance(o, BNode): o = o.skolemize(authority=authority, basepath=basepath) return s, p, o retval = Graph() if new_graph is None else new_graph if bnode is None: self._process_skolem_tuples(retval, do_skolemize2) elif isinstance(bnode, BNode): # type error: Argument 1 to "do_skolemize" has incompatible type "Optional[BNode]"; expected "BNode" self._process_skolem_tuples(retval, lambda t: do_skolemize(bnode, t)) # type: ignore[arg-type, unused-ignore] return retval def de_skolemize( self, new_graph: Optional[Graph] = None, uriref: Optional[URIRef] = None ) -> Graph: def do_de_skolemize(uriref: URIRef, t: _TripleType) -> _TripleType: (s, p, o) = t if s == uriref: if TYPE_CHECKING: assert isinstance(s, URIRef) s = s.de_skolemize() if o == uriref: if TYPE_CHECKING: assert isinstance(o, URIRef) o = o.de_skolemize() return s, p, o def do_de_skolemize2(t: _TripleType) -> _TripleType: (s, p, o) = t if RDFLibGenid._is_rdflib_skolem(s): # type error: Argument 1 to "RDFLibGenid" has incompatible type "Node"; expected "str" s = RDFLibGenid(s).de_skolemize() # type: ignore[arg-type] elif Genid._is_external_skolem(s): # type error: Argument 1 to "Genid" has incompatible type "Node"; expected "str" s = Genid(s).de_skolemize() # type: ignore[arg-type] if isinstance(o, URIRef): if RDFLibGenid._is_rdflib_skolem(o): o = RDFLibGenid(o).de_skolemize() elif Genid._is_external_skolem(o): o = Genid(o).de_skolemize() return s, p, o retval = Graph() if new_graph is None else new_graph if uriref is None: self._process_skolem_tuples(retval, do_de_skolemize2) elif isinstance(uriref, Genid): # type error: Argument 1 to "do_de_skolemize" has incompatible type "Optional[URIRef]"; expected "URIRef" self._process_skolem_tuples(retval, lambda t: do_de_skolemize(uriref, t)) # type: ignore[arg-type, unused-ignore] return retval def cbd( self, resource: _SubjectType, *, target_graph: Optional[Graph] = None ) -> Graph: """Retrieves the Concise Bounded Description of a Resource from a Graph. Args: resource: A URIRef object, the Resource to query for. target_graph: Optionally, a graph to add the CBD to; otherwise, a new graph is created for the CBD. Returns: A Graph, subgraph of self if no graph was provided otherwise the provided graph. Note: Concise Bounded Description (CBD) is defined as: Given a particular node (the starting node) in a particular RDF graph (the source graph), a subgraph of that particular graph, taken to comprise a concise bounded description of the resource denoted by the starting node, can be identified as follows: 1. Include in the subgraph all statements in the source graph where the subject of the statement is the starting node; 2. Recursively, for all statements identified in the subgraph thus far having a blank node object, include in the subgraph all statements in the source graph where the subject of the statement is the blank node in question and which are not already included in the subgraph. 3. Recursively, for all statements included in the subgraph thus far, for all reifications of each statement in the source graph, include the concise bounded description beginning from the rdf:Statement node of each reification. This results in a subgraph where the object nodes are either URI references, literals, or blank nodes not serving as the subject of any statement in the graph. See: """ if target_graph is None: subgraph = Graph() else: subgraph = target_graph def add_to_cbd(uri: _SubjectType) -> None: for s, p, o in self.triples((uri, None, None)): subgraph.add((s, p, o)) # recurse 'down' through ll Blank Nodes if type(o) is BNode and (o, None, None) not in subgraph: add_to_cbd(o) # for Rule 3 (reification) # for any rdf:Statement in the graph with the given URI as the object of rdf:subject, # get all triples with that rdf:Statement instance as subject # find any subject s where the predicate is rdf:subject and this uri is the object # (these subjects are of type rdf:Statement, given the domain of rdf:subject) for s, p, o in self.triples((None, RDF.subject, uri)): # find all triples with s as the subject and add these to the subgraph for s2, p2, o2 in self.triples((s, None, None)): subgraph.add((s2, p2, o2)) add_to_cbd(resource) return subgraph _ContextType = Graph class ConjunctiveGraph(Graph): """A ConjunctiveGraph is an (unnamed) aggregation of all the named graphs in a store. !!! warning "Deprecation notice" ConjunctiveGraph is deprecated, use [`rdflib.graph.Dataset`][rdflib.graph.Dataset] instead. It has a `default` graph, whose name is associated with the graph throughout its life. Constructor can take an identifier to use as the name of this default graph or it will assign a BNode. All methods that add triples work against this default graph. All queries are carried out against the union of all graphs. """ _default_context: _ContextType def __init__( self, store: Union[Store, str] = "default", identifier: Optional[Union[IdentifiedNode, str]] = None, default_graph_base: Optional[str] = None, ): super(ConjunctiveGraph, self).__init__(store, identifier=identifier) if type(self) is ConjunctiveGraph: warnings.warn( "ConjunctiveGraph is deprecated, use Dataset instead.", DeprecationWarning, stacklevel=2, ) assert self.store.context_aware, ( "ConjunctiveGraph must be backed by" " a context aware store." ) self.context_aware = True self.default_union = True # Conjunctive! self._default_context: _ContextType = Graph( store=self.store, identifier=identifier or BNode(), base=default_graph_base ) @property def default_context(self): return self._default_context @default_context.setter def default_context(self, value): self._default_context = value def __str__(self) -> str: pattern = ( "[a rdflib:ConjunctiveGraph;rdflib:storage " "[a rdflib:Store;rdfs:label '%s']]" ) return pattern % self.store.__class__.__name__ @overload def _spoc( self, triple_or_quad: _QuadType, default: bool = False, ) -> _QuadType: ... @overload def _spoc( self, triple_or_quad: Union[_TripleType, _OptionalQuadType], default: bool = False, ) -> _OptionalQuadType: ... @overload def _spoc( self, triple_or_quad: None, default: bool = False, ) -> Tuple[None, None, None, Optional[Graph]]: ... @overload def _spoc( self, triple_or_quad: Optional[_TripleOrQuadPatternType], default: bool = False, ) -> _QuadPatternType: ... @overload def _spoc( self, triple_or_quad: _TripleOrQuadSelectorType, default: bool = False, ) -> _QuadSelectorType: ... @overload def _spoc( self, triple_or_quad: Optional[_TripleOrQuadSelectorType], default: bool = False, ) -> _QuadSelectorType: ... def _spoc( self, triple_or_quad: Optional[_TripleOrQuadSelectorType], default: bool = False, ) -> _QuadSelectorType: """ helper method for having methods that support either triples or quads """ if triple_or_quad is None: return (None, None, None, self.default_context if default else None) if len(triple_or_quad) == 3: c = self.default_context if default else None # type error: Too many values to unpack (3 expected, 4 provided) (s, p, o) = triple_or_quad # type: ignore[misc, unused-ignore] elif len(triple_or_quad) == 4: # type error: Need more than 3 values to unpack (4 expected) (s, p, o, c) = triple_or_quad # type: ignore[misc, unused-ignore] c = self._graph(c) return s, p, o, c def __contains__(self, triple_or_quad: _TripleOrQuadSelectorType) -> bool: """Support for 'triple/quad in graph' syntax""" s, p, o, c = self._spoc(triple_or_quad) for t in self.triples((s, p, o), context=c): return True return False def add( self: _ConjunctiveGraphT, triple_or_quad: _TripleOrOptionalQuadType, ) -> _ConjunctiveGraphT: """Add a triple or quad to the store. if a triple is given it is added to the default context """ s, p, o, c = self._spoc(triple_or_quad, default=True) _assertnode(s, p, o) # type error: Argument "context" to "add" of "Store" has incompatible type "Optional[Graph]"; expected "Graph" self.store.add((s, p, o), context=c, quoted=False) # type: ignore[arg-type] return self @overload def _graph(self, c: Union[Graph, _ContextIdentifierType, str]) -> Graph: ... @overload def _graph(self, c: None) -> None: ... def _graph( self, c: Optional[Union[Graph, _ContextIdentifierType, str]] ) -> Optional[Graph]: if c is None: return None if not isinstance(c, Graph): return self.get_context(c) else: if isinstance(c, (Dataset, ConjunctiveGraph)): # Preserve the old behaviour for datasets. return c else: # Copy the graph triples so they're added to the store. try: _graph = self.get_graph(c.identifier) assert _graph is not None except IndexError: _graph = self.get_context(c.identifier) _graph.__iadd__(c) # Return the graph with the same backing store. return _graph def addN( # noqa: N802 self: _ConjunctiveGraphT, quads: Iterable[_QuadType] ) -> _ConjunctiveGraphT: """Add a sequence of triples with context""" self.store.addN( (s, p, o, self._graph(c)) for s, p, o, c in quads if _assertnode(s, p, o) ) return self # type error: Argument 1 of "remove" is incompatible with supertype "Graph"; supertype defines the argument type as "Tuple[Optional[Node], Optional[Node], Optional[Node]]" def remove(self: _ConjunctiveGraphT, triple_or_quad: _TripleOrOptionalQuadType) -> _ConjunctiveGraphT: # type: ignore[override] """Removes a triple or quads if a triple is given it is removed from all contexts a quad is removed from the given context only """ s, p, o, c = self._spoc(triple_or_quad) self.store.remove((s, p, o), context=c) return self @overload def triples( self, triple_or_quad: _TripleOrQuadPatternType, context: Optional[_ContextType] = ..., ) -> Generator[_TripleType, None, None]: ... @overload def triples( self, triple_or_quad: _TripleOrQuadPathPatternType, context: Optional[_ContextType] = ..., ) -> Generator[_TriplePathType, None, None]: ... @overload def triples( self, triple_or_quad: _TripleOrQuadSelectorType, context: Optional[_ContextType] = ..., ) -> Generator[_TripleOrTriplePathType, None, None]: ... def triples( self, triple_or_quad: _TripleOrQuadSelectorType, context: Optional[_ContextType] = None, ) -> Generator[_TripleOrTriplePathType, None, None]: """Iterate over all the triples in the entire conjunctive graph For legacy reasons, this can take the context to query either as a fourth element of the quad, or as the explicit context keyword parameter. The kw param takes precedence. """ s, p, o, c = self._spoc(triple_or_quad) context = self._graph(context or c) if self.default_union: if context == self.default_context: context = None else: if context is None: context = self.default_context if isinstance(p, Path): if context is None: context = self for s, o in p.eval(context, s, o): yield s, p, o else: for (s, p, o), cg in self.store.triples((s, p, o), context=context): yield s, p, o def quads( self, triple_or_quad: Optional[_TripleOrQuadPatternType] = None ) -> Generator[_OptionalQuadType, None, None]: """Iterate over all the quads in the entire conjunctive graph""" s, p, o, c = self._spoc(triple_or_quad) for (s, p, o), cg in self.store.triples((s, p, o), context=c): for ctx in cg: yield s, p, o, ctx def triples_choices( self, triple: _TripleChoiceType, context: Optional[_ContextType] = None, ) -> Generator[_TripleType, None, None]: """Iterate over all the triples in the entire conjunctive graph""" s, p, o = triple if context is None: if not self.default_union: context = self.default_context else: context = self._graph(context) # type error: Argument 1 to "triples_choices" of "Store" has incompatible type "Tuple[Union[List[Node], Node], Union[Node, List[Node]], Union[Node, List[Node]]]"; expected "Union[Tuple[List[Node], Node, Node], Tuple[Node, List[Node], Node], Tuple[Node, Node, List[Node]]]" # type error note: unpacking discards type info for (s1, p1, o1), cg in self.store.triples_choices((s, p, o), context=context): # type: ignore[arg-type] yield s1, p1, o1 def __len__(self) -> int: """Number of triples in the entire conjunctive graph""" return self.store.__len__() def contexts( self, triple: Optional[_TripleType] = None ) -> Generator[_ContextType, None, None]: """Iterate over all contexts in the graph If triple is specified, iterate over all contexts the triple is in. """ for context in self.store.contexts(triple): if isinstance(context, Graph): # TODO: One of these should never happen and probably # should raise an exception rather than smoothing over # the weirdness - see #225 yield context else: # type error: Statement is unreachable yield self.get_context(context) # type: ignore[unreachable] def get_graph(self, identifier: _ContextIdentifierType) -> Union[Graph, None]: """Returns the graph identified by given identifier""" return [x for x in self.contexts() if x.identifier == identifier][0] def get_context( self, identifier: Optional[Union[_ContextIdentifierType, str]], quoted: bool = False, base: Optional[str] = None, ) -> Graph: """Return a context graph for the given identifier identifier must be a URIRef or BNode. """ return Graph( store=self.store, identifier=identifier, namespace_manager=self.namespace_manager, base=base, ) def remove_context(self, context: _ContextType) -> None: """Removes the given context from the graph""" self.store.remove((None, None, None), context) def context_id(self, uri: str, context_id: Optional[str] = None) -> URIRef: """URI#context""" uri = uri.split("#", 1)[0] if context_id is None: context_id = "#context" return URIRef(context_id, base=uri) def parse( self, source: Optional[ Union[IO[bytes], TextIO, InputSource, str, bytes, pathlib.PurePath] ] = None, publicID: Optional[str] = None, # noqa: N803 format: Optional[str] = None, location: Optional[str] = None, file: Optional[Union[BinaryIO, TextIO]] = None, data: Optional[Union[str, bytes]] = None, **args: Any, ) -> Graph: """Parse source adding the resulting triples to its own context (sub graph of this graph). See [`rdflib.graph.Graph.parse`][rdflib.graph.Graph.parse] for documentation on arguments. Args: source: The source to parse publicID: The public ID of the source format: The format of the source location: The location of the source file: The file object to parse data: The data to parse **args: Additional arguments Returns: The graph into which the source was parsed. In the case of n3 it returns the root context. Note: If the source is in a format that does not support named graphs its triples will be added to the default graph (i.e. ConjunctiveGraph.default_context). !!! warning "Caution" This method can access directly or indirectly requested network or file resources, for example, when parsing JSON-LD documents with `@context` directives that point to a network location. When processing untrusted or potentially malicious documents, measures should be taken to restrict network and file access. For information on available security measures, see the RDFLib Security Considerations documentation. !!! example "Changed in 7.0" The `publicID` argument is no longer used as the identifier (i.e. name) of the default graph as was the case before version 7.0. In the case of sources that do not support named graphs, the `publicID` parameter will also not be used as the name for the graph that the data is loaded into, and instead the triples from sources that do not support named graphs will be loaded into the default graph (i.e. ConjunctiveGraph.default_context). """ source = create_input_source( source=source, publicID=publicID, location=location, file=file, data=data, format=format, ) # NOTE on type hint: `xml.sax.xmlreader.InputSource.getPublicId` has no # type annotations but given that systemId should be a string, and # given that there is no specific mention of type for publicId, it # seems reasonable to assume it should also be a string. Furthermore, # create_input_source will ensure that publicId is not None, though it # would be good if this guarantee was made more explicit i.e. by type # hint on InputSource (TODO/FIXME). context = self.default_context context.parse(source, publicID=publicID, format=format, **args) return self def __reduce__(self) -> Tuple[Type[Graph], Tuple[Store, _ContextIdentifierType]]: return ConjunctiveGraph, (self.store, self.identifier) DATASET_DEFAULT_GRAPH_ID = URIRef("urn:x-rdflib:default") class Dataset(ConjunctiveGraph): """ An RDFLib Dataset is an object that stores multiple Named Graphs - instances of RDFLib Graph identified by IRI - within it and allows whole-of-dataset or single Graph use. RDFLib's Dataset class is based on the [RDF 1.2. 'Dataset' definition](https://www.w3.org/TR/rdf12-datasets/): An RDF dataset is a collection of RDF graphs, and comprises: - Exactly one default graph, being an RDF graph. The default graph does not have a name and MAY be empty. - Zero or more named graphs. Each named graph is a pair consisting of an IRI or a blank node (the graph name), and an RDF graph. Graph names are unique within an RDF dataset. Accordingly, a Dataset allows for `Graph` objects to be added to it with [`URIRef`][rdflib.term.URIRef] or [`BNode`][rdflib.term.BNode] identifiers and always creats a default graph with the [`URIRef`][rdflib.term.URIRef] identifier `urn:x-rdflib:default`. Dataset extends Graph's Subject, Predicate, Object (s, p, o) 'triple' structure to include a graph identifier - archaically called Context - producing 'quads' of s, p, o, g. Triples, or quads, can be added to a Dataset. Triples, or quads with the graph identifer :code:`urn:x-rdflib:default` go into the default graph. !!! warning "Deprecation notice" Dataset builds on the `ConjunctiveGraph` class but that class's direct use is now deprecated (since RDFLib 7.x) and it should not be used. `ConjunctiveGraph` will be removed from future RDFLib versions. Examples of usage and see also the `examples/datast.py` file: ```python >>> # Create a new Dataset >>> ds = Dataset() >>> # simple triples goes to default graph >>> ds.add(( ... URIRef("http://example.org/a"), ... URIRef("http://www.example.org/b"), ... Literal("foo") ... )) # doctest: +ELLIPSIS )> >>> # Create a graph in the dataset, if the graph name has already been >>> # used, the corresponding graph will be returned >>> # (ie, the Dataset keeps track of the constituent graphs) >>> g = ds.graph(URIRef("http://www.example.com/gr")) >>> # add triples to the new graph as usual >>> g.add(( ... URIRef("http://example.org/x"), ... URIRef("http://example.org/y"), ... Literal("bar") ... )) # doctest: +ELLIPSIS )> >>> # alternatively: add a quad to the dataset -> goes to the graph >>> ds.add(( ... URIRef("http://example.org/x"), ... URIRef("http://example.org/z"), ... Literal("foo-bar"), ... g ... )) # doctest: +ELLIPSIS )> >>> # querying triples return them all regardless of the graph >>> for t in ds.triples((None,None,None)): # doctest: +SKIP ... print(t) # doctest: +NORMALIZE_WHITESPACE (rdflib.term.URIRef("http://example.org/a"), rdflib.term.URIRef("http://www.example.org/b"), rdflib.term.Literal("foo")) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/z"), rdflib.term.Literal("foo-bar")) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/y"), rdflib.term.Literal("bar")) >>> # querying quads() return quads; the fourth argument can be unrestricted >>> # (None) or restricted to a graph >>> for q in ds.quads((None, None, None, None)): # doctest: +SKIP ... print(q) # doctest: +NORMALIZE_WHITESPACE (rdflib.term.URIRef("http://example.org/a"), rdflib.term.URIRef("http://www.example.org/b"), rdflib.term.Literal("foo"), None) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/y"), rdflib.term.Literal("bar"), rdflib.term.URIRef("http://www.example.com/gr")) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/z"), rdflib.term.Literal("foo-bar"), rdflib.term.URIRef("http://www.example.com/gr")) >>> # unrestricted looping is equivalent to iterating over the entire Dataset >>> for q in ds: # doctest: +SKIP ... print(q) # doctest: +NORMALIZE_WHITESPACE (rdflib.term.URIRef("http://example.org/a"), rdflib.term.URIRef("http://www.example.org/b"), rdflib.term.Literal("foo"), None) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/y"), rdflib.term.Literal("bar"), rdflib.term.URIRef("http://www.example.com/gr")) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/z"), rdflib.term.Literal("foo-bar"), rdflib.term.URIRef("http://www.example.com/gr")) >>> # resticting iteration to a graph: >>> for q in ds.quads((None, None, None, g)): # doctest: +SKIP ... print(q) # doctest: +NORMALIZE_WHITESPACE (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/y"), rdflib.term.Literal("bar"), rdflib.term.URIRef("http://www.example.com/gr")) (rdflib.term.URIRef("http://example.org/x"), rdflib.term.URIRef("http://example.org/z"), rdflib.term.Literal("foo-bar"), rdflib.term.URIRef("http://www.example.com/gr")) >>> # Note that in the call above - >>> # ds.quads((None,None,None,"http://www.example.com/gr")) >>> # would have been accepted, too >>> # graph names in the dataset can be queried: >>> for c in ds.graphs(): # doctest: +SKIP ... print(c.identifier) # doctest: urn:x-rdflib:default http://www.example.com/gr >>> # A graph can be created without specifying a name; a skolemized genid >>> # is created on the fly >>> h = ds.graph() >>> for c in ds.graphs(): # doctest: +SKIP ... print(c) # doctest: +NORMALIZE_WHITESPACE +ELLIPSIS DEFAULT https://rdflib.github.io/.well-known/genid/rdflib/N... http://www.example.com/gr >>> # Note that the Dataset.graphs() call returns names of empty graphs, >>> # too. This can be restricted: >>> for c in ds.graphs(empty=False): # doctest: +SKIP ... print(c) # doctest: +NORMALIZE_WHITESPACE DEFAULT http://www.example.com/gr >>> # a graph can also be removed from a dataset via ds.remove_graph(g) ``` !!! example "New in version 4.0" """ def __init__( self, store: Union[Store, str] = "default", default_union: bool = False, default_graph_base: Optional[str] = None, ): super(Dataset, self).__init__(store=store, identifier=None) if not self.store.graph_aware: raise Exception("Dataset must be backed by a graph-aware store!") self._default_context = Graph( store=self.store, identifier=DATASET_DEFAULT_GRAPH_ID, base=default_graph_base, ) self.default_union = default_union @property def default_context(self): warnings.warn( "Dataset.default_context is deprecated, use Dataset.default_graph instead.", DeprecationWarning, stacklevel=2, ) return self._default_context @default_context.setter def default_context(self, value): warnings.warn( "Dataset.default_context is deprecated, use Dataset.default_graph instead.", DeprecationWarning, stacklevel=2, ) self._default_context = value @property def default_graph(self): return self._default_context @default_graph.setter def default_graph(self, value): self._default_context = value @property def identifier(self): warnings.warn( "Dataset.identifier is deprecated and will be removed in future versions.", DeprecationWarning, stacklevel=2, ) return super(Dataset, self).identifier def __str__(self) -> str: pattern = ( "[a rdflib:Dataset;rdflib:storage " "[a rdflib:Store;rdfs:label '%s']]" ) return pattern % self.store.__class__.__name__ # type error: Return type "Tuple[Type[Dataset], Tuple[Store, bool]]" of "__reduce__" incompatible with return type "Tuple[Type[Graph], Tuple[Store, IdentifiedNode]]" in supertype "ConjunctiveGraph" # type error: Return type "Tuple[Type[Dataset], Tuple[Store, bool]]" of "__reduce__" incompatible with return type "Tuple[Type[Graph], Tuple[Store, IdentifiedNode]]" in supertype "Graph" def __reduce__(self) -> Tuple[Type[Dataset], Tuple[Store, bool]]: # type: ignore[override] return (type(self), (self.store, self.default_union)) def __getstate__(self) -> Tuple[Store, _ContextIdentifierType, _ContextType, bool]: return self.store, self.identifier, self.default_graph, self.default_union def __setstate__( self, state: Tuple[Store, _ContextIdentifierType, _ContextType, bool] ) -> None: # type error: Property "store" defined in "Graph" is read-only # type error: Property "identifier" defined in "Graph" is read-only self.store, self.identifier, self.default_graph, self.default_union = state # type: ignore[misc] def __iadd__(self: _DatasetT, other: Iterable[_QuadType]) -> _DatasetT: # type: ignore[override, misc] """Add all quads in Dataset other to Dataset. BNode IDs are not changed.""" self.addN((s, p, o, g) for s, p, o, g in other) return self def graph( self, identifier: Optional[Union[_ContextIdentifierType, _ContextType, str]] = None, base: Optional[str] = None, ) -> Graph: if identifier is None: from rdflib.term import _SKOLEM_DEFAULT_AUTHORITY, rdflib_skolem_genid self.bind( "genid", _SKOLEM_DEFAULT_AUTHORITY + rdflib_skolem_genid, override=False, ) identifier = BNode().skolemize() g = self._graph(identifier) g.base = base self.store.add_graph(g) return g def parse( self, source: Optional[ Union[IO[bytes], TextIO, InputSource, str, bytes, pathlib.PurePath] ] = None, publicID: Optional[str] = None, # noqa: N803 format: Optional[str] = None, location: Optional[str] = None, file: Optional[Union[BinaryIO, TextIO]] = None, data: Optional[Union[str, bytes]] = None, **args: Any, ) -> Dataset: """Parse an RDF source adding the resulting triples to the Graph. Args: source: The source to parse. See rdflib.graph.Graph.parse for details. publicID: The public ID of the source. format: The format of the source. location: The location of the source. file: The file object to parse. data: The data to parse. **args: Additional arguments. Returns: The graph that the source was parsed into. Note: The source is specified using one of source, location, file or data. If the source is in a format that does not support named graphs its triples will be added to the default graph (i.e. :attr:`.Dataset.default_graph`). If the source is in a format that does not support named graphs its triples will be added to the default graph (i.e. Dataset.default_graph). !!! warning "Caution" This method can access directly or indirectly requested network or file resources, for example, when parsing JSON-LD documents with `@context` directives that point to a network location. When processing untrusted or potentially malicious documents, measures should be taken to restrict network and file access. For information on available security measures, see the RDFLib Security Considerations documentation. !!! example "Changed in 7.0" The `publicID` argument is no longer used as the identifier (i.e. name) of the default graph as was the case before version 7.0. In the case of sources that do not support named graphs, the `publicID` parameter will also not be used as the name for the graph that the data is loaded into, and instead the triples from sources that do not support named graphs will be loaded into the default graph (i.e. Dataset.default_graph). """ ConjunctiveGraph.parse( self, source, publicID, format, location, file, data, **args ) return self def add_graph( self, g: Optional[Union[_ContextIdentifierType, _ContextType, str]] ) -> Graph: """alias of graph for consistency""" return self.graph(g) def remove_graph( self: _DatasetT, g: Optional[Union[_ContextIdentifierType, _ContextType, str]] ) -> _DatasetT: if not isinstance(g, Graph): g = self.get_context(g) self.store.remove_graph(g) if g is None or g == self.default_graph: # default graph cannot be removed # only triples deleted, so add it back in self.store.add_graph(self.default_graph) return self def contexts( self, triple: Optional[_TripleType] = None ) -> Generator[_ContextType, None, None]: warnings.warn( "Dataset.contexts is deprecated, use Dataset.graphs instead.", DeprecationWarning, stacklevel=2, ) default = False for c in super(Dataset, self).contexts(triple): default |= c.identifier == DATASET_DEFAULT_GRAPH_ID yield c if not default: yield self.graph(DATASET_DEFAULT_GRAPH_ID) def graphs( self, triple: Optional[_TripleType] = None ) -> Generator[_ContextType, None, None]: default = False for c in super(Dataset, self).contexts(triple): default |= c.identifier == DATASET_DEFAULT_GRAPH_ID yield c if not default: yield self.graph(DATASET_DEFAULT_GRAPH_ID) # type error: Return type "Generator[Tuple[Node, Node, Node, Optional[Node]], None, None]" of "quads" incompatible with return type "Generator[Tuple[Node, Node, Node, Optional[Graph]], None, None]" in supertype "ConjunctiveGraph" def quads( # type: ignore[override] self, quad: Optional[_TripleOrQuadPatternType] = None ) -> Generator[_OptionalIdentifiedQuadType, None, None]: for s, p, o, c in super(Dataset, self).quads(quad): # type error: Item "None" of "Optional[Graph]" has no attribute "identifier" if c.identifier == self.default_graph: # type: ignore[union-attr] yield s, p, o, None else: # type error: Item "None" of "Optional[Graph]" has no attribute "identifier" [union-attr] yield s, p, o, c.identifier # type: ignore[union-attr] # type error: Return type "Generator[Tuple[Node, URIRef, Node, Optional[IdentifiedNode]], None, None]" of "__iter__" incompatible with return type "Generator[Tuple[IdentifiedNode, IdentifiedNode, Union[IdentifiedNode, Literal]], None, None]" in supertype "Graph" def __iter__( # type: ignore[override] self, ) -> Generator[_OptionalIdentifiedQuadType, None, None]: """Iterates over all quads in the store""" return self.quads((None, None, None, None)) @overload def serialize( self, destination: None, format: str, base: Optional[str], encoding: str, **args: Any, ) -> bytes: ... # no destination and non-None keyword encoding @overload def serialize( self, destination: None = ..., format: str = ..., base: Optional[str] = ..., *, encoding: str, **args: Any, ) -> bytes: ... # no destination and None encoding @overload def serialize( self, destination: None = ..., format: str = ..., base: Optional[str] = ..., encoding: None = ..., **args: Any, ) -> str: ... # non-None destination @overload def serialize( self, destination: Union[str, pathlib.PurePath, IO[bytes]], format: str = ..., base: Optional[str] = ..., encoding: Optional[str] = ..., **args: Any, ) -> Graph: ... # fallback @overload def serialize( self, destination: Optional[Union[str, pathlib.PurePath, IO[bytes]]] = ..., format: str = ..., base: Optional[str] = ..., encoding: Optional[str] = ..., **args: Any, ) -> Union[bytes, str, Graph]: ... def serialize( self, destination: Optional[Union[str, pathlib.PurePath, IO[bytes]]] = None, format: str = "trig", base: Optional[str] = None, encoding: Optional[str] = None, **args: Any, ) -> Union[bytes, str, Graph]: return super(Dataset, self).serialize( destination=destination, format=format, base=base, encoding=encoding, **args ) class QuotedGraph(Graph): """ Quoted Graphs are intended to implement Notation 3 formulae. They are associated with a required identifier that the N3 parser *must* provide in order to maintain consistent formulae identification for scenarios such as implication and other such processing. """ def __init__( self, store: Union[Store, str], identifier: Optional[Union[_ContextIdentifierType, str]], ): super(QuotedGraph, self).__init__(store, identifier) def add(self: _GraphT, triple: _TripleType) -> _GraphT: """Add a triple with self as context""" s, p, o = triple assert isinstance(s, Node), "Subject %s must be an rdflib term" % (s,) assert isinstance(p, Node), "Predicate %s must be an rdflib term" % (p,) assert isinstance(o, Node), "Object %s must be an rdflib term" % (o,) self.store.add((s, p, o), self, quoted=True) return self def addN(self: _GraphT, quads: Iterable[_QuadType]) -> _GraphT: # noqa: N802 """Add a sequence of triple with context""" self.store.addN( (s, p, o, c) for s, p, o, c in quads if isinstance(c, QuotedGraph) and c.identifier is self.identifier and _assertnode(s, p, o) ) return self def n3(self, namespace_manager: Optional[NamespaceManager] = None) -> str: """Return an n3 identifier for the Graph""" return "{%s}" % self.identifier.n3(namespace_manager=namespace_manager) def __str__(self) -> str: identifier = self.identifier.n3() label = self.store.__class__.__name__ pattern = ( "{this rdflib.identifier %s;rdflib:storage " "[a rdflib:Store;rdfs:label '%s']}" ) return pattern % (identifier, label) def __reduce__(self) -> Tuple[Type[Graph], Tuple[Store, _ContextIdentifierType]]: return QuotedGraph, (self.store, self.identifier) # Make sure QuotedGraph is ordered correctly # wrt to other Terms. # this must be done here, as the QuotedGraph cannot be # circularily imported in term.py rdflib.term._ORDERING[QuotedGraph] = 11 class Seq: """Wrapper around an RDF Seq resource It implements a container type in Python with the order of the items returned corresponding to the Seq content. It is based on the natural ordering of the predicate names _1, _2, _3, etc, which is the 'implementation' of a sequence in RDF terms. Args: graph: the graph containing the Seq subject:the subject of a Seq. Note that the init does not check whether this is a Seq, this is done in whoever creates this instance! """ def __init__(self, graph: Graph, subject: _SubjectType): self._list: List[Tuple[int, _ObjectType]] _list = self._list = list() LI_INDEX = URIRef(str(RDF) + "_") # noqa: N806 for p, o in graph.predicate_objects(subject): # type error: "Node" has no attribute "startswith" if p.startswith(LI_INDEX): # type: ignore[attr-defined] # != RDF.Seq: # type error: "Node" has no attribute "replace" i = int(p.replace(LI_INDEX, "")) # type: ignore[attr-defined] _list.append((i, o)) # here is the trick: the predicates are _1, _2, _3, etc. Ie, # by sorting the keys (by integer) we have what we want! _list.sort() def toPython(self) -> Seq: # noqa: N802 return self def __iter__(self) -> Generator[_ObjectType, None, None]: """Generator over the items in the Seq""" for _, item in self._list: yield item def __len__(self) -> int: """Length of the Seq""" return len(self._list) def __getitem__(self, index) -> _ObjectType: """Item given by index from the Seq""" index, item = self._list.__getitem__(index) return item class ModificationException(Exception): # noqa: N818 def __init__(self) -> None: pass def __str__(self) -> str: return ( "Modifications and transactional operations not allowed on " "ReadOnlyGraphAggregate instances" ) class UnSupportedAggregateOperation(Exception): # noqa: N818 def __init__(self) -> None: pass def __str__(self) -> str: return "This operation is not supported by ReadOnlyGraphAggregate " "instances" class ReadOnlyGraphAggregate(ConjunctiveGraph): """Utility class for treating a set of graphs as a single graph Only read operations are supported (hence the name). Essentially a ConjunctiveGraph over an explicit subset of the entire store. """ def __init__(self, graphs: List[Graph], store: Union[str, Store] = "default"): if store is not None: super(ReadOnlyGraphAggregate, self).__init__(store) Graph.__init__(self, store) self.__namespace_manager = None assert ( isinstance(graphs, list) and graphs and [g for g in graphs if isinstance(g, Graph)] ), "graphs argument must be a list of Graphs!!" self.graphs = graphs def __repr__(self) -> str: return "" % len(self.graphs) def destroy(self, configuration: str) -> NoReturn: raise ModificationException() # Transactional interfaces (optional) def commit(self) -> NoReturn: raise ModificationException() def rollback(self) -> NoReturn: raise ModificationException() def open(self, configuration: str | tuple[str, str], create: bool = False) -> None: # TODO: is there a use case for this method? for graph in self.graphs: # type error: Too many arguments for "open" of "Graph" # type error: Argument 1 to "open" of "Graph" has incompatible type "ReadOnlyGraphAggregate"; expected "str" [arg-type] # type error: Argument 2 to "open" of "Graph" has incompatible type "str"; expected "bool" [arg-type] graph.open(self, configuration, create) # type: ignore[call-arg, arg-type] # type error: Signature of "close" incompatible with supertype "Graph" def close(self) -> None: # type: ignore[override] for graph in self.graphs: graph.close() def add(self, triple: _TripleOrOptionalQuadType) -> NoReturn: raise ModificationException() def addN(self, quads: Iterable[_QuadType]) -> NoReturn: # noqa: N802 raise ModificationException() # type error: Argument 1 of "remove" is incompatible with supertype "Graph"; supertype defines the argument type as "Tuple[Optional[Node], Optional[Node], Optional[Node]]" def remove(self, triple: _TripleOrOptionalQuadType) -> NoReturn: # type: ignore[override] raise ModificationException() # type error: Signature of "triples" incompatible with supertype "ConjunctiveGraph" @overload # type: ignore[override] def triples( self, triple: _TriplePatternType, ) -> Generator[_TripleType, None, None]: ... @overload def triples( self, triple: _TriplePathPatternType, ) -> Generator[_TriplePathType, None, None]: ... @overload def triples( self, triple: _TripleSelectorType, ) -> Generator[_TripleOrTriplePathType, None, None]: ... def triples( self, triple: _TripleSelectorType, ) -> Generator[_TripleOrTriplePathType, None, None]: s, p, o = triple for graph in self.graphs: if isinstance(p, Path): for s, o in p.eval(self, s, o): yield s, p, o else: for s1, p1, o1 in graph.triples((s, p, o)): yield s1, p1, o1 def __contains__(self, triple_or_quad: _TripleOrQuadSelectorType) -> bool: context = None if len(triple_or_quad) == 4: # type error: Tuple index out of range context = triple_or_quad[3] # type: ignore [misc, unused-ignore] for graph in self.graphs: if context is None or graph.identifier == context.identifier: if triple_or_quad[:3] in graph: return True return False # type error: Signature of "quads" incompatible with supertype "ConjunctiveGraph" def quads( # type: ignore[override] self, triple_or_quad: _TripleOrQuadSelectorType ) -> Generator[ Tuple[_SubjectType, Union[Path, _PredicateType], _ObjectType, _ContextType], None, None, ]: """Iterate over all the quads in the entire aggregate graph""" c = None if len(triple_or_quad) == 4: # type error: Need more than 3 values to unpack (4 expected) s, p, o, c = triple_or_quad # type: ignore[misc, unused-ignore] else: # type error: Too many values to unpack (3 expected, 4 provided) s, p, o = triple_or_quad # type: ignore[misc, unused-ignore] if c is not None: for graph in [g for g in self.graphs if g == c]: for s1, p1, o1 in graph.triples((s, p, o)): yield s1, p1, o1, graph else: for graph in self.graphs: for s1, p1, o1 in graph.triples((s, p, o)): yield s1, p1, o1, graph def __len__(self) -> int: return sum(len(g) for g in self.graphs) def __hash__(self) -> NoReturn: raise UnSupportedAggregateOperation() def __cmp__(self, other) -> int: if other is None: return -1 elif isinstance(other, Graph): return -1 elif isinstance(other, ReadOnlyGraphAggregate): return (self.graphs > other.graphs) - (self.graphs < other.graphs) else: return -1 def __iadd__(self: _GraphT, other: Iterable[_TripleType]) -> NoReturn: raise ModificationException() def __isub__(self: _GraphT, other: Iterable[_TripleType]) -> NoReturn: raise ModificationException() # Conv. methods def triples_choices( self, triple: _TripleChoiceType, context: Optional[_ContextType] = None, ) -> Generator[_TripleType, None, None]: subject, predicate, object_ = triple for graph in self.graphs: # type error: Argument 1 to "triples_choices" of "Graph" has incompatible type "Tuple[Union[List[Node], Node], Union[Node, List[Node]], Union[Node, List[Node]]]"; expected "Union[Tuple[List[Node], Node, Node], Tuple[Node, List[Node], Node], Tuple[Node, Node, List[Node]]]" # type error note: unpacking discards type info choices = graph.triples_choices((subject, predicate, object_)) # type: ignore[arg-type] for s, p, o in choices: yield s, p, o def qname(self, uri: str) -> str: if hasattr(self, "namespace_manager") and self.namespace_manager: return self.namespace_manager.qname(uri) raise UnSupportedAggregateOperation() def compute_qname(self, uri: str, generate: bool = True) -> Tuple[str, URIRef, str]: if hasattr(self, "namespace_manager") and self.namespace_manager: return self.namespace_manager.compute_qname(uri, generate) raise UnSupportedAggregateOperation() # type error: Signature of "bind" incompatible with supertype "Graph" def bind( # type: ignore[override] self, prefix: Optional[str], namespace: Any, override: bool = True # noqa: F811 ) -> NoReturn: raise UnSupportedAggregateOperation() def namespaces(self) -> Generator[Tuple[str, URIRef], None, None]: if hasattr(self, "namespace_manager"): for prefix, namespace in self.namespace_manager.namespaces(): yield prefix, namespace else: for graph in self.graphs: for prefix, namespace in graph.namespaces(): yield prefix, namespace def absolutize(self, uri: str, defrag: int = 1) -> NoReturn: raise UnSupportedAggregateOperation() # type error: Signature of "parse" incompatible with supertype "ConjunctiveGraph" def parse( # type: ignore[override] self, source: Optional[ Union[IO[bytes], TextIO, InputSource, str, bytes, pathlib.PurePath] ], publicID: Optional[str] = None, # noqa: N803 format: Optional[str] = None, **args: Any, ) -> NoReturn: raise ModificationException() def n3(self, namespace_manager: Optional[NamespaceManager] = None) -> NoReturn: raise UnSupportedAggregateOperation() def __reduce__(self) -> NoReturn: raise UnSupportedAggregateOperation() @overload def _assertnode(*terms: Node) -> te.Literal[True]: ... @overload def _assertnode(*terms: Any) -> bool: ... def _assertnode(*terms: Any) -> bool: for t in terms: assert isinstance(t, Node), "Term %s must be an rdflib term" % (t,) return True class BatchAddGraph: """Wrapper around graph that turns batches of calls to Graph's add (and optionally, addN) into calls to batched calls to addN`. Args: graph: The graph to wrap batch_size: The maximum number of triples to buffer before passing to Graph's addN batch_addn: If True, then even calls to `addN` will be batched according to batch_size Attributes: graph: The wrapped graph count: The number of triples buffered since initialization or the last call to reset batch: The current buffer of triples """ def __init__(self, graph: Graph, batch_size: int = 1000, batch_addn: bool = False): if not batch_size or batch_size < 2: raise ValueError("batch_size must be a positive number") self.graph = graph self.__graph_tuple = (graph,) self.__batch_size = batch_size self.__batch_addn = batch_addn self.reset() def reset(self) -> BatchAddGraph: """ Manually clear the buffered triples and reset the count to zero """ self.batch: List[_QuadType] = [] self.count = 0 return self def add( self, triple_or_quad: Union[ _TripleType, _QuadType, ], ) -> BatchAddGraph: """Add a triple to the buffer. Args: triple_or_quad: The triple or quad to add Returns: The BatchAddGraph instance """ if len(self.batch) >= self.__batch_size: self.graph.addN(self.batch) self.batch = [] self.count += 1 if len(triple_or_quad) == 3: # type error: Argument 1 to "append" of "list" has incompatible type "Tuple[Node, ...]"; expected "Tuple[Node, Node, Node, Graph]" self.batch.append(triple_or_quad + self.__graph_tuple) # type: ignore[arg-type, unused-ignore] else: # type error: Argument 1 to "append" of "list" has incompatible type "Union[Tuple[Node, Node, Node], Tuple[Node, Node, Node, Graph]]"; expected "Tuple[Node, Node, Node, Graph]" self.batch.append(triple_or_quad) # type: ignore[arg-type, unused-ignore] return self def addN(self, quads: Iterable[_QuadType]) -> BatchAddGraph: # noqa: N802 if self.__batch_addn: for q in quads: self.add(q) else: self.graph.addN(quads) return self def __enter__(self) -> BatchAddGraph: self.reset() return self def __exit__(self, *exc) -> None: if exc[0] is None: self.graph.addN(self.batch)