Source code for rdflib.plugins.stores.sparqlstore

# -*- coding: utf-8 -*-
#
"""
This is an RDFLib store around Ivan Herman et al.'s SPARQL service wrapper.
This was first done in layer-cake, and then ported to RDFLib

"""
import re
import collections

from .sparqlconnector import SPARQLConnector

from rdflib.plugins.stores.regexmatching import NATIVE_REGEX

from rdflib.store import Store
from rdflib import Variable, BNode
from rdflib.graph import DATASET_DEFAULT_GRAPH_ID
from rdflib.term import Node
from typing import Any, Callable, Dict, Optional, Union, Tuple

# Defines some SPARQL keywords
LIMIT = "LIMIT"
OFFSET = "OFFSET"
ORDERBY = "ORDER BY"

BNODE_IDENT_PATTERN = re.compile(r"(?P<label>_\:[^\s]+)")

NodeToSparql = Callable[..., str]


def _node_to_sparql(node) -> str:
    if isinstance(node, BNode):
        raise Exception(
            "SPARQLStore does not support BNodes! "
            "See http://www.w3.org/TR/sparql11-query/#BGPsparqlBNodes"
        )
    return node.n3()


[docs]class SPARQLStore(SPARQLConnector, Store): # type: ignore[misc] """An RDFLib store around a SPARQL endpoint This is context-aware and should work as expected when a context is specified. For ConjunctiveGraphs, reading is done from the "default graph". Exactly what this means depends on your endpoint, because SPARQL does not offer a simple way to query the union of all graphs as it would be expected for a ConjuntiveGraph. This is why we recommend using Dataset instead, which is motivated by the SPARQL 1.1. Fuseki/TDB has a flag for specifying that the default graph is the union of all graphs (``tdb:unionDefaultGraph`` in the Fuseki config). .. warning:: By default the SPARQL Store does not support blank-nodes! As blank-nodes act as variables in SPARQL queries, there is no way to query for a particular blank node without using non-standard SPARQL extensions. See http://www.w3.org/TR/sparql11-query/#BGPsparqlBNodes You can make use of such extensions through the ``node_to_sparql`` argument. For example if you want to transform BNode('0001') into "<bnode:b0001>", you can use a function like this: >>> def my_bnode_ext(node): ... if isinstance(node, BNode): ... return '<bnode:b%s>' % node ... return _node_to_sparql(node) >>> store = SPARQLStore('http://dbpedia.org/sparql', ... node_to_sparql=my_bnode_ext) You can request a particular result serialization with the ``returnFormat`` parameter. This is a string that must have a matching plugin registered. Built in is support for ``xml``, ``json``, ``csv``, ``tsv`` and ``application/rdf+xml``. The underlying SPARQLConnector uses the urllib library. Any extra kwargs passed to the SPARQLStore connector are passed to urllib when doing HTTP calls. I.e. you have full control of cookies/auth/headers. Form example: >>> store = SPARQLStore('...my endpoint ...', auth=('user','pass')) will use HTTP basic auth. """ formula_aware = False transaction_aware = False graph_aware = True regex_matching = NATIVE_REGEX
[docs] def __init__( self, query_endpoint: str = None, sparql11: bool = True, context_aware: bool = True, node_to_sparql: NodeToSparql = _node_to_sparql, returnFormat: str = "xml", auth: Optional[Tuple[str, str]] = None, **sparqlconnector_kwargs, ): super(SPARQLStore, self).__init__( query_endpoint=query_endpoint, returnFormat=returnFormat, auth=auth, **sparqlconnector_kwargs, ) self.node_to_sparql = node_to_sparql self.nsBindings: Dict[str, Any] = {} self.sparql11 = sparql11 self.context_aware = context_aware self.graph_aware = context_aware self._queries = 0
[docs] def open(self, configuration: str, create=False): """This method is included so that calls to this Store via Graph, e.g. Graph("SPARQLStore"), can set the required parameters """ if type(configuration) == str: self.query_endpoint = configuration else: raise Exception( "configuration must be a string (a single query endpoint URI)" )
# Database Management Methods
[docs] def create(self, configuration): raise TypeError( "The SPARQL Store is read only. Try SPARQLUpdateStore for read/write." )
[docs] def destroy(self, configuration): raise TypeError("The SPARQL store is read only")
# Transactional interfaces
[docs] def commit(self): raise TypeError("The SPARQL store is read only")
[docs] def rollback(self): raise TypeError("The SPARQL store is read only")
[docs] def add(self, _, context=None, quoted=False): raise TypeError("The SPARQL store is read only")
[docs] def addN(self, quads): raise TypeError("The SPARQL store is read only")
[docs] def remove(self, _, context): raise TypeError("The SPARQL store is read only")
def _query(self, *args, **kwargs): self._queries += 1 return super(SPARQLStore, self).query(*args, **kwargs) def _inject_prefixes(self, query, extra_bindings): bindings = set(list(self.nsBindings.items()) + list(extra_bindings.items())) if not bindings: return query return "\n".join( [ "\n".join(["PREFIX %s: <%s>" % (k, v) for k, v in bindings]), "", # separate ns_bindings from query with an empty line query, ] )
[docs] def query( self, query, initNs=None, initBindings=None, queryGraph=None, DEBUG=False ): self.debug = DEBUG assert isinstance(query, str) if initNs is not None and len(initNs) > 0: query = self._inject_prefixes(query, initNs) if initBindings: if not self.sparql11: raise Exception("initBindings not supported for SPARQL 1.0 Endpoints.") v = list(initBindings) # VALUES was added to SPARQL 1.1 on 2012/07/24 query += "\nVALUES ( %s )\n{ ( %s ) }\n" % ( " ".join("?" + str(x) for x in v), " ".join(self.node_to_sparql(initBindings[x]) for x in v), ) return self._query( query, default_graph=queryGraph if self._is_contextual(queryGraph) else None )
[docs] def triples(self, spo, context=None): """ - tuple **(s, o, p)** the triple used as filter for the SPARQL select. (None, None, None) means anything. - context **context** the graph effectively calling this method. Returns a tuple of triples executing essentially a SPARQL like SELECT ?subj ?pred ?obj WHERE { ?subj ?pred ?obj } **context** may include three parameter to refine the underlying query: * LIMIT: an integer to limit the number of results * OFFSET: an integer to enable paging of results * ORDERBY: an instance of Variable('s'), Variable('o') or Variable('p') or, by default, the first 'None' from the given triple .. warning:: - Using LIMIT or OFFSET automatically include ORDERBY otherwise this is because the results are retrieved in a not deterministic way (depends on the walking path on the graph) - Using OFFSET without defining LIMIT will discard the first OFFSET - 1 results `` a_graph.LIMIT = limit a_graph.OFFSET = offset triple_generator = a_graph.triples(mytriple): # do something # Removes LIMIT and OFFSET if not required for the next triple() calls del a_graph.LIMIT del a_graph.OFFSET `` """ s, p, o = spo vars = [] if not s: s = Variable("s") vars.append(s) if not p: p = Variable("p") vars.append(p) if not o: o = Variable("o") vars.append(o) if vars: v = " ".join([term.n3() for term in vars]) verb = "SELECT %s " % v else: verb = "ASK" nts = self.node_to_sparql query = "%s { %s %s %s }" % (verb, nts(s), nts(p), nts(o)) # The ORDER BY is necessary if ( hasattr(context, LIMIT) or hasattr(context, OFFSET) or hasattr(context, ORDERBY) ): var = None if isinstance(s, Variable): var = s elif isinstance(p, Variable): var = p elif isinstance(o, Variable): var = o elif hasattr(context, ORDERBY) and isinstance( getattr(context, ORDERBY), Variable ): var = getattr(context, ORDERBY) query = query + " %s %s" % (ORDERBY, var.n3()) try: query = query + " LIMIT %s" % int(getattr(context, LIMIT)) except (ValueError, TypeError, AttributeError): pass try: query = query + " OFFSET %s" % int(getattr(context, OFFSET)) except (ValueError, TypeError, AttributeError): pass result = self._query( query, default_graph=context.identifier if self._is_contextual(context) else None, ) if vars: if type(result) == tuple: if result[0] == 401: raise ValueError( "It looks like you need to authenticate with this SPARQL Store. HTTP unauthorized" ) for row in result: yield ( row.get(s, s), row.get(p, p), row.get(o, o), ), None # why is the context here not the passed in graph 'context'? else: if result.askAnswer: yield (s, p, o), None
[docs] def triples_choices(self, _, context=None): """ A variant of triples that can take a list of terms instead of a single term in any slot. Stores can implement this to optimize the response time from the import default 'fallback' implementation, which will iterate over each term in the list and dispatch to triples. """ raise NotImplementedError("Triples choices currently not supported")
[docs] def __len__(self, context=None): if not self.sparql11: raise NotImplementedError( "For performance reasons, this is not" + "supported for sparql1.0 endpoints" ) else: q = "SELECT (count(*) as ?c) WHERE {?s ?p ?o .}" result = self._query( q, default_graph=context.identifier if self._is_contextual(context) else None, ) return int(next(iter(result)).c)
[docs] def contexts(self, triple=None): """ Iterates over results to "SELECT ?NAME { GRAPH ?NAME { ?s ?p ?o } }" or "SELECT ?NAME { GRAPH ?NAME {} }" if triple is `None`. Returns instances of this store with the SPARQL wrapper object updated via addNamedGraph(?NAME). This causes a named-graph-uri key / value pair to be sent over the protocol. Please note that some SPARQL endpoints are not able to find empty named graphs. """ if triple: nts = self.node_to_sparql s, p, o = triple params = ( nts(s if s else Variable("s")), nts(p if p else Variable("p")), nts(o if o else Variable("o")), ) q = "SELECT ?name WHERE { GRAPH ?name { %s %s %s }}" % params else: q = "SELECT ?name WHERE { GRAPH ?name {} }" result = self._query(q) return (row.name for row in result)
# Namespace persistence interface implementation
[docs] def bind(self, prefix, namespace): self.nsBindings[prefix] = namespace
[docs] def prefix(self, namespace): """ """ return dict([(v, k) for k, v in self.nsBindings.items()]).get(namespace)
[docs] def namespace(self, prefix): return self.nsBindings.get(prefix)
[docs] def namespaces(self): for prefix, ns in self.nsBindings.items(): yield prefix, ns
[docs] def add_graph(self, graph): raise TypeError("The SPARQL store is read only")
[docs] def remove_graph(self, graph): raise TypeError("The SPARQL store is read only")
def _is_contextual(self, graph): """Returns `True` if the "GRAPH" keyword must appear in the final SPARQL query sent to the endpoint. """ if (not self.context_aware) or (graph is None): return False if isinstance(graph, str): return graph != "__UNION__" else: return graph.identifier != DATASET_DEFAULT_GRAPH_ID
[docs] def subjects(self, predicate=None, object=None): """A generator of subjects with the given predicate and object""" for t, c in self.triples((None, predicate, object)): yield t[0]
[docs] def predicates(self, subject=None, object=None): """A generator of predicates with the given subject and object""" for t, c in self.triples((subject, None, object)): yield t[1]
[docs] def objects(self, subject=None, predicate=None): """A generator of objects with the given subject and predicate""" for t, c in self.triples((subject, predicate, None)): yield t[2]
[docs] def subject_predicates(self, object=None): """A generator of (subject, predicate) tuples for the given object""" for t, c in self.triples((None, None, object)): yield t[0], t[1]
[docs] def subject_objects(self, predicate=None): """A generator of (subject, object) tuples for the given predicate""" for t, c in self.triples((None, predicate, None)): yield t[0], t[2]
[docs] def predicate_objects(self, subject=None): """A generator of (predicate, object) tuples for the given subject""" for t, c in self.triples((subject, None, None)): yield t[1], t[2]
[docs]class SPARQLUpdateStore(SPARQLStore): """A store using SPARQL queries for reading and SPARQL Update for changes. This can be context-aware, if so, any changes will be to the given named graph only. In favor of the SPARQL 1.1 motivated Dataset, we advise against using this with ConjunctiveGraphs, as it reads and writes from and to the "default graph". Exactly what this means depends on the endpoint and can result in confusion. For Graph objects, everything works as expected. See the :class:`SPARQLStore` base class for more information. """ where_pattern = re.compile(r"""(?P<where>WHERE\s*\{)""", re.IGNORECASE) ############################################################## # Regex for injecting GRAPH blocks into updates on a context # ############################################################## # Observations on the SPARQL grammar (http://www.w3.org/TR/2013/REC-sparql11-query-20130321/): # 1. Only the terminals STRING_LITERAL1, STRING_LITERAL2, # STRING_LITERAL_LONG1, STRING_LITERAL_LONG2, and comments can contain # curly braces. # 2. The non-terminals introduce curly braces in pairs only. # 3. Unescaped " can occur only in strings and comments. # 3. Unescaped ' can occur only in strings, comments, and IRIRefs. # 4. \ always escapes the following character, especially \", \', and # \\ denote literal ", ', and \ respectively. # 5. # always starts a comment outside of string and IRI # 6. A comment ends at the next newline # 7. IRIREFs need to be detected, as they may contain # without starting a comment # 8. PrefixedNames do not contain a # # As a consequence, it should be rather easy to detect strings and comments # in order to avoid unbalanced curly braces. # From the SPARQL grammar STRING_LITERAL1 = "'([^'\\\\]|\\\\.)*'" STRING_LITERAL2 = '"([^"\\\\]|\\\\.)*"' STRING_LITERAL_LONG1 = "'''(('|'')?([^'\\\\]|\\\\.))*'''" STRING_LITERAL_LONG2 = '"""(("|"")?([^"\\\\]|\\\\.))*"""' String = "(%s)|(%s)|(%s)|(%s)" % ( STRING_LITERAL1, STRING_LITERAL2, STRING_LITERAL_LONG1, STRING_LITERAL_LONG2, ) IRIREF = '<([^<>"{}|^`\\]\\\\[\\x00-\\x20])*>' COMMENT = "#[^\\x0D\\x0A]*([\\x0D\\x0A]|\\Z)" # Simplified grammar to find { at beginning and } at end of blocks BLOCK_START = "{" BLOCK_END = "}" ESCAPED = "\\\\." # Match anything that doesn't start or end a block: BlockContent = "(%s)|(%s)|(%s)|(%s)" % (String, IRIREF, COMMENT, ESCAPED) BlockFinding = "(?P<block_start>%s)|(?P<block_end>%s)|(?P<block_content>%s)" % ( BLOCK_START, BLOCK_END, BlockContent, ) BLOCK_FINDING_PATTERN = re.compile(BlockFinding) # Note that BLOCK_FINDING_PATTERN.finditer() will not cover the whole # string with matches. Everything that is not matched will have to be # part of the modified query as is. ##################################################################
[docs] def __init__( self, query_endpoint: Optional[str] = None, update_endpoint: Optional[str] = None, sparql11: bool = True, context_aware: bool = True, postAsEncoded: bool = True, autocommit: bool = True, dirty_reads: bool = False, **kwds, ): """ :param autocommit if set, the store will commit after every writing operations. If False, we only make queries on the server once commit is called. :param dirty_reads if set, we do not commit before reading. So you cannot read what you wrote before manually calling commit. """ SPARQLStore.__init__( self, query_endpoint, sparql11, context_aware, update_endpoint=update_endpoint, **kwds, ) self.postAsEncoded = postAsEncoded self.autocommit = autocommit self.dirty_reads = dirty_reads self._edits = None self._updates = 0
def open(self, configuration: Union[str, Tuple[str, str]], create=False): """This method is included so that calls to this Store via Graph, e.g. Graph("SPARQLStore"), can set the required parameters """ if type(configuration) == str: self.query_endpoint = configuration # type: ignore[assignment] elif type(configuration) == tuple: self.query_endpoint = configuration[0] self.update_endpoint = configuration[1] else: raise Exception( "configuration must be either a string (a single query endpoint URI) " "or a tuple (a query/update endpoint URI pair)" )
[docs] def query(self, *args, **kwargs): if not self.autocommit and not self.dirty_reads: self.commit() return SPARQLStore.query(self, *args, **kwargs)
[docs] def triples(self, *args, **kwargs): if not self.autocommit and not self.dirty_reads: self.commit() return SPARQLStore.triples(self, *args, **kwargs)
[docs] def contexts(self, *args, **kwargs): if not self.autocommit and not self.dirty_reads: self.commit() return SPARQLStore.contexts(self, *args, **kwargs)
[docs] def __len__(self, *args, **kwargs): if not self.autocommit and not self.dirty_reads: self.commit() return SPARQLStore.__len__(self, *args, **kwargs)
# TODO: FIXME: open is defined twice
[docs] def open(self, configuration, create=False): # type: ignore[no-redef] """ sets the endpoint URLs for this SPARQLStore :param configuration: either a tuple of (query_endpoint, update_endpoint), or a string with the endpoint which is configured as query and update endpoint :param create: if True an exception is thrown. """ if create: raise Exception("Cannot create a SPARQL Endpoint") if isinstance(configuration, tuple): self.query_endpoint = configuration[0] if len(configuration) > 1: self.update_endpoint = configuration[1] else: self.query_endpoint = configuration self.update_endpoint = configuration
def _transaction(self): if self._edits is None: self._edits = [] return self._edits # Transactional interfaces
[docs] def commit(self): """add(), addN(), and remove() are transactional to reduce overhead of many small edits. Read and update() calls will automatically commit any outstanding edits. This should behave as expected most of the time, except that alternating writes and reads can degenerate to the original call-per-triple situation that originally existed. """ if self._edits and len(self._edits) > 0: self._update("\n;\n".join(self._edits)) self._edits = None
[docs] def rollback(self): self._edits = None
[docs] def add(self, spo, context=None, quoted=False): """Add a triple to the store of triples.""" if not self.update_endpoint: raise Exception("UpdateEndpoint is not set") assert not quoted (subject, predicate, obj) = spo nts = self.node_to_sparql triple = "%s %s %s ." % (nts(subject), nts(predicate), nts(obj)) if self._is_contextual(context): q = "INSERT DATA { GRAPH %s { %s } }" % (nts(context.identifier), triple) else: q = "INSERT DATA { %s }" % triple self._transaction().append(q) if self.autocommit: self.commit()
[docs] def addN(self, quads): """Add a list of quads to the store.""" if not self.update_endpoint: raise Exception("UpdateEndpoint is not set - call 'open'") contexts = collections.defaultdict(list) for subject, predicate, obj, context in quads: contexts[context].append((subject, predicate, obj)) data = [] nts = self.node_to_sparql for context in contexts: triples = [ "%s %s %s ." % (nts(subject), nts(predicate), nts(obj)) for subject, predicate, obj in contexts[context] ] data.append( "INSERT DATA { GRAPH %s { %s } }\n" % (nts(context.identifier), "\n".join(triples)) ) self._transaction().extend(data) if self.autocommit: self.commit()
[docs] def remove(self, spo, context): """Remove a triple from the store""" if not self.update_endpoint: raise Exception("UpdateEndpoint is not set - call 'open'") (subject, predicate, obj) = spo if not subject: subject = Variable("S") if not predicate: predicate = Variable("P") if not obj: obj = Variable("O") nts = self.node_to_sparql triple = "%s %s %s ." % (nts(subject), nts(predicate), nts(obj)) if self._is_contextual(context): cid = nts(context.identifier) q = "WITH %(graph)s DELETE { %(triple)s } WHERE { %(triple)s }" % { "graph": cid, "triple": triple, } else: q = "DELETE { %s } WHERE { %s } " % (triple, triple) self._transaction().append(q) if self.autocommit: self.commit()
[docs] def setTimeout(self, timeout): self._timeout = int(timeout)
def _update(self, update): self._updates += 1 SPARQLConnector.update(self, update)
[docs] def update(self, query, initNs={}, initBindings={}, queryGraph=None, DEBUG=False): """ Perform a SPARQL Update Query against the endpoint, INSERT, LOAD, DELETE etc. Setting initNs adds PREFIX declarations to the beginning of the update. Setting initBindings adds inline VALUEs to the beginning of every WHERE clause. By the SPARQL grammar, all operations that support variables (namely INSERT and DELETE) require a WHERE clause. Important: initBindings fails if the update contains the substring 'WHERE {' which does not denote a WHERE clause, e.g. if it is part of a literal. .. admonition:: Context-aware query rewriting - **When:** If context-awareness is enabled and the graph is not the default graph of the store. - **Why:** To ensure consistency with the :class:`~rdflib.plugins.stores.memory.Memory` store. The graph must accept "local" SPARQL requests (requests with no GRAPH keyword) as if it was the default graph. - **What is done:** These "local" queries are rewritten by this store. The content of each block of a SPARQL Update operation is wrapped in a GRAPH block except if the block is empty. This basically causes INSERT, INSERT DATA, DELETE, DELETE DATA and WHERE to operate only on the context. - **Example:** `"INSERT DATA { <urn:michel> <urn:likes> <urn:pizza> }"` is converted into `"INSERT DATA { GRAPH <urn:graph> { <urn:michel> <urn:likes> <urn:pizza> } }"`. - **Warning:** Queries are presumed to be "local" but this assumption is **not checked**. For instance, if the query already contains GRAPH blocks, the latter will be wrapped in new GRAPH blocks. - **Warning:** A simplified grammar is used that should tolerate extensions of the SPARQL grammar. Still, the process may fail in uncommon situations and produce invalid output. """ if not self.update_endpoint: raise Exception("Update endpoint is not set!") self.debug = DEBUG assert isinstance(query, str) query = self._inject_prefixes(query, initNs) if self._is_contextual(queryGraph): query = self._insert_named_graph(query, queryGraph) if initBindings: # For INSERT and DELETE the WHERE clause is obligatory # (http://www.w3.org/TR/2013/REC-sparql11-query-20130321/#rModify) # Other query types do not allow variables and don't # have a WHERE clause. This also works for updates with # more than one INSERT/DELETE. v = list(initBindings) values = "\nVALUES ( %s )\n{ ( %s ) }\n" % ( " ".join("?" + str(x) for x in v), " ".join(self.node_to_sparql(initBindings[x]) for x in v), ) query = self.where_pattern.sub("WHERE { " + values, query) self._transaction().append(query) if self.autocommit: self.commit()
def _insert_named_graph(self, query, query_graph): """ Inserts GRAPH <query_graph> {} into blocks of SPARQL Update operations For instance, "INSERT DATA { <urn:michel> <urn:likes> <urn:pizza> }" is converted into "INSERT DATA { GRAPH <urn:graph> { <urn:michel> <urn:likes> <urn:pizza> } }" """ if isinstance(query_graph, Node): query_graph = self.node_to_sparql(query_graph) else: query_graph = "<%s>" % query_graph graph_block_open = " GRAPH %s {" % query_graph graph_block_close = "} " # SPARQL Update supports the following operations: # LOAD, CLEAR, DROP, ADD, MOVE, COPY, CREATE, INSERT DATA, DELETE DATA, DELETE/INSERT, DELETE WHERE # LOAD, CLEAR, DROP, ADD, MOVE, COPY, CREATE do not make much sense in a context. # INSERT DATA, DELETE DATA, and DELETE WHERE require the contents of their block to be wrapped in a GRAPH <?> { }. # DELETE/INSERT supports the WITH keyword, which sets the graph to be # used for all following DELETE/INSERT instruction including the # non-optional WHERE block. Equivalently, a GRAPH block can be added to # all blocks. # # Strategy employed here: Wrap the contents of every top-level block into a `GRAPH <?> { }`. level = 0 modified_query = [] pos = 0 for match in self.BLOCK_FINDING_PATTERN.finditer(query): if match.group("block_start") is not None: level += 1 if level == 1: modified_query.append(query[pos : match.end()]) modified_query.append(graph_block_open) pos = match.end() elif match.group("block_end") is not None: if level == 1: since_previous_pos = query[pos : match.start()] if modified_query[-1] is graph_block_open and ( since_previous_pos == "" or since_previous_pos.isspace() ): # In this case, adding graph_block_start and # graph_block_end results in an empty GRAPH block. Some # endpoints (e.g. TDB) can not handle this. Therefore # remove the previously added block_start. modified_query.pop() modified_query.append(since_previous_pos) else: modified_query.append(since_previous_pos) modified_query.append(graph_block_close) pos = match.start() level -= 1 modified_query.append(query[pos:]) return "".join(modified_query)
[docs] def add_graph(self, graph): if not self.graph_aware: Store.add_graph(self, graph) elif graph.identifier != DATASET_DEFAULT_GRAPH_ID: self.update("CREATE GRAPH %s" % self.node_to_sparql(graph.identifier))
[docs] def remove_graph(self, graph): if not self.graph_aware: Store.remove_graph(self, graph) elif graph.identifier == DATASET_DEFAULT_GRAPH_ID: self.update("DROP DEFAULT") else: self.update("DROP GRAPH %s" % self.node_to_sparql(graph.identifier))
[docs] def subjects(self, predicate=None, object=None): """A generator of subjects with the given predicate and object""" for t, c in self.triples((None, predicate, object)): yield t[0]
[docs] def predicates(self, subject=None, object=None): """A generator of predicates with the given subject and object""" for t, c in self.triples((subject, None, object)): yield t[1]
[docs] def objects(self, subject=None, predicate=None): """A generator of objects with the given subject and predicate""" for t, c in self.triples((subject, predicate, None)): yield t[2]
[docs] def subject_predicates(self, object=None): """A generator of (subject, predicate) tuples for the given object""" for t, c in self.triples((None, None, object)): yield t[0], t[1]
[docs] def subject_objects(self, predicate=None): """A generator of (subject, object) tuples for the given predicate""" for t, c in self.triples((None, predicate, None)): yield t[0], t[2]
[docs] def predicate_objects(self, subject=None): """A generator of (predicate, object) tuples for the given subject""" for t, c in self.triples((subject, None, None)): yield t[1], t[2]