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## Context-aware: An RDF store capable of storing statements within contexts is considered context-aware.
## Essentially, such a store is able to partition the RDF model it represents into individual, named, and addressable sub-graphs.
## Relevant Notation3 reference regarding formula's, quoted statements, and such: http://www.w3.org/DesignIssues/Notation3.html
## Formula-aware: An RDF store capable of distinguishing between statements that are asserted and statements
## that are quoted is considered formula-aware.
## Conjunctive Graph: This refers to the 'top-level' Graph. It is the aggregation of all the contexts
## within it and is also the appropriate, absolute boundary for closed world assumptions / models.
## For the sake of persistence, Conjunctive Graphs must be distinguished by identifiers (that may not
## neccessarily be RDF identifiers or may be an RDF identifier normalized - SHA1/MD5 perhaps - for database
## naming purposes ).
## Conjunctive Query: Any query that doesn't limit the store to search within a named context only. Such a
## query expects a context-aware store to search the entire asserted universe (the conjunctive graph).
## A formula-aware store is expected not to include quoted statements when matching such a query.
from rdflib import RDF
from rdflib import exceptions
#Constants representing the state of a Store (returned by the open method)
VALID_STORE = 1
CORRUPTED_STORE = 0
NO_STORE = -1
UNKNOWN = None
from rdflib.events import Dispatcher, Event
class StoreCreatedEvent(Event):
"""
This event is fired when the Store is created, it has the folloing attribute:
- 'configuration' string that is used to create the store
"""
class TripleAddedEvent(Event):
"""
This event is fired when a triple is added, it has the following attributes:
- 'triple' added to the graph
- 'context' of the triple if any
- 'graph' that the triple was added to
"""
class TripleRemovedEvent(Event):
"""
This event is fired when a triple is removed, it has the following attributes:
- 'triple' removed from the graph
- 'context' of the triple if any
- 'graph' that the triple was removed from
"""
class Store(object):
#Properties
context_aware = False
formula_aware = False
transaction_aware = False
batch_unification = False
def __init__(self, configuration=None, identifier=None):
"""
identifier: URIRef of the Store. Defaults to CWD
configuration: string containing infomation open can use to
connect to datastore.
"""
self.__node_pickler = None
self.dispatcher = Dispatcher()
if configuration:
self.open(configuration)
def __get_node_pickler(self):
if self.__node_pickler is None:
from rdflib.store.NodePickler import NodePickler
from rdflib.URIRef import URIRef
from rdflib.BNode import BNode
from rdflib.Literal import Literal
from rdflib.Graph import Graph, QuotedGraph, GraphValue
from rdflib.Variable import Variable
from rdflib.Statement import Statement
self.__node_pickler = np = NodePickler()
np.register(self, "S")
np.register(URIRef, "U")
np.register(BNode, "B")
np.register(Literal, "L")
np.register(Graph, "G")
np.register(QuotedGraph, "Q")
np.register(Variable, "V")
np.register(Statement, "s")
np.register(GraphValue, "v")
return self.__node_pickler
node_pickler = property(__get_node_pickler)
#Database management methods
def create(self, configuration):
self.dispatcher.dispatch(StoreCreatedEvent(configuration=configuration))
def open(self, configuration, create=False):
"""
Opens the store specified by the configuration string. If
create is True a store will be created if it does not already
exist. If create is False and a store does not already exist
an exception is raised. An exception is also raised if a store
exists, but there is insufficient permissions to open the
store. This should return one of VALID_STORE,CORRUPTED_STORE,or NO_STORE
"""
return UNKNOWN
def close(self, commit_pending_transaction=False):
"""
This closes the database connection. The commit_pending_transaction parameter specifies whether to
commit all pending transactions before closing (if the store is transactional).
"""
def destroy(self, configuration):
"""
This destroys the instance of the store identified by the configuration string.
"""
def gc(self):
"""
Allows the store to perform any needed garbage collection
"""
pass
#RDF APIs
def add(self, (subject, predicate, object), context, quoted=False):
"""
Adds the given statement to a specific context or to the model. The quoted argument
is interpreted by formula-aware stores to indicate this statement is quoted/hypothetical
It should be an error to not specify a context and have the quoted argument be True.
It should also be an error for the quoted argument to be True when the store is not formula-aware.
"""
self.dispatcher.dispatch(TripleAddedEvent(triple=(subject, predicate, object), context=context))
def addN(self, quads):
"""
Adds each item in the list of statements to a specific context. The quoted argument
is interpreted by formula-aware stores to indicate this statement is quoted/hypothetical.
Note that the default implementation is a redirect to add
"""
for s,p,o,c in quads:
assert c is not None, "Context associated with %s %s %s is None!"%(s,p,o)
self.add(
(s,p,o),
c
)
def remove(self, (subject, predicate, object), context=None):
""" Remove the set of triples matching the pattern from the store """
self.dispatcher.dispatch(TripleRemovedEvent(triple=(subject, predicate, object), context=context))
def triples_choices(self, (subject, predicate, object_),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 default 'fallback' implementation, which will iterate
over each term in the list and dispatch to tripless
"""
if isinstance(object_,list):
assert not isinstance(subject,list), "object_ / subject are both lists"
assert not isinstance(predicate,list), "object_ / predicate are both lists"
if object_:
for obj in object_:
for (s1, p1, o1), cg in self.triples((subject,predicate,obj),context):
yield (s1, p1, o1), cg
else:
for (s1, p1, o1), cg in self.triples((subject,predicate,None),context):
yield (s1, p1, o1), cg
elif isinstance(subject,list):
assert not isinstance(predicate,list), "subject / predicate are both lists"
if subject:
for subj in subject:
for (s1, p1, o1), cg in self.triples((subj,predicate,object_),context):
yield (s1, p1, o1), cg
else:
for (s1, p1, o1), cg in self.triples((None,predicate,object_),context):
yield (s1, p1, o1), cg
elif isinstance(predicate,list):
assert not isinstance(subject,list), "predicate / subject are both lists"
if predicate:
for pred in predicate:
for (s1, p1, o1), cg in self.triples((subject,pred,object_),context):
yield (s1, p1, o1), cg
else:
for (s1, p1, o1), cg in self.triples((subject,None,object_),context):
yield (s1, p1, o1), cg
def triples(self, (subject, predicate, object), context=None):
"""
A generator over all the triples matching the pattern. Pattern can
include any objects for used for comparing against nodes in the store, for
example, REGEXTerm, URIRef, Literal, BNode, Variable, Graph, QuotedGraph, Date? DateRange?
A conjunctive query can be indicated by either providing a value of None
for the context or the identifier associated with the Conjunctive Graph (if it's context aware).
"""
# variants of triples will be done if / when optimization is needed
def __len__(self, context=None):
"""
Number of statements in the store. This should only account for non-quoted (asserted) statements
if the context is not specified, otherwise it should return the number of statements in the formula or context given.
"""
def contexts(self, triple=None):
"""
Generator over all contexts in the graph. If triple is specified, a generator over all
contexts the triple is in.
"""
# Optional Namespace methods
def bind(self, prefix, namespace):
""" """
def prefix(self, namespace):
""" """
def namespace(self, prefix):
""" """
def namespaces(self):
""" """
# Optional Transactional methods
def commit(self):
""" """
def rollback(self):
""" """
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