path: root/rdflib/store.py

from __future__ import annotations

import pickle
from io import BytesIO
from typing import (
    TYPE_CHECKING,
    Any,
    Dict,
    Generator,
    Iterable,
    Iterator,
    List,
    Mapping,
    Optional,
    Tuple,
    Union,
)

from rdflib.events import Dispatcher, Event

if TYPE_CHECKING:
    from rdflib.graph import (
        Graph,
        _ContextType,
        _ObjectType,
        _PredicateType,
        _QuadType,
        _SubjectType,
        _TriplePatternType,
        _TripleType,
    )
    from rdflib.plugins.sparql.sparql import Query, Update
    from rdflib.query import Result
    from rdflib.term import Identifier, Node, URIRef

"""
============
rdflib.store
============

Types of store
--------------

``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 formulae, 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.

``Transaction-capable``: capable of providing transactional integrity to the
RDF operations performed on it.

``Graph-aware``: capable of keeping track of empty graphs.

------
"""


# Constants representing the state of a Store (returned by the open method)
VALID_STORE = 1
CORRUPTED_STORE = 0
NO_STORE = -1
UNKNOWN = None


Pickler = pickle.Pickler
Unpickler = pickle.Unpickler
UnpicklingError = pickle.UnpicklingError

__all__ = [
    "StoreCreatedEvent",
    "TripleAddedEvent",
    "TripleRemovedEvent",
    "NodePickler",
    "Store",
]


class StoreCreatedEvent(Event):
    """
    This event is fired when the Store is created, it has the following
    attribute:

      - ``configuration``: string used to create the store

    """


class TripleAddedEvent(Event):
    """
    This event is fired when a triple is added, it has the following
    attributes:

      - the ``triple`` added to the graph
      - the ``context`` of the triple, if any
      - the ``graph`` to which the triple was added
    """


class TripleRemovedEvent(Event):
    """
    This event is fired when a triple is removed, it has the following
    attributes:

      - the ``triple`` removed from the graph
      - the ``context`` of the triple, if any
      - the ``graph`` from which the triple was removed
    """


class NodePickler:
    def __init__(self) -> None:
        self._objects: Dict[str, Any] = {}
        self._ids: Dict[Any, str] = {}
        self._get_object = self._objects.__getitem__

    def _get_ids(self, key: Any) -> Optional[str]:
        try:
            return self._ids.get(key)
        except TypeError:
            return None

    def register(self, object: Any, id: str) -> None:
        self._objects[id] = object
        self._ids[object] = id

    def loads(self, s: bytes) -> "Node":
        up = Unpickler(BytesIO(s))
        # NOTE on type error: https://github.com/python/mypy/issues/2427
        # type error: Cannot assign to a method
        up.persistent_load = self._get_object  # type: ignore[assignment]
        try:
            return up.load()
        except KeyError as e:
            raise UnpicklingError("Could not find Node class for %s" % e)

    def dumps(
        self, obj: "Node", protocol: Optional[Any] = None, bin: Optional[Any] = None
    ):
        src = BytesIO()
        p = Pickler(src)
        # NOTE on type error: https://github.com/python/mypy/issues/2427
        # type error: Cannot assign to a method
        p.persistent_id = self._get_ids  # type: ignore[assignment]
        p.dump(obj)
        return src.getvalue()

    def __getstate__(self) -> Mapping[str, Any]:
        state = self.__dict__.copy()
        del state["_get_object"]
        state.update(
            {"_ids": tuple(self._ids.items()), "_objects": tuple(self._objects.items())}
        )
        return state

    def __setstate__(self, state: Mapping[str, Any]) -> None:
        self.__dict__.update(state)
        self._ids = dict(self._ids)
        self._objects = dict(self._objects)
        self._get_object = self._objects.__getitem__


class Store:
    # Properties
    context_aware: bool = False
    formula_aware: bool = False
    transaction_aware: bool = False
    graph_aware: bool = False

    def __init__(
        self,
        configuration: Optional[str] = None,
        identifier: Optional["Identifier"] = None,
    ):
        """
        identifier: URIRef of the Store. Defaults to CWD
        configuration: string containing information open can use to
        connect to datastore.
        """
        self.__node_pickler: Optional[NodePickler] = None
        self.dispatcher = Dispatcher()
        if configuration:
            self.open(configuration)

    @property
    def node_pickler(self) -> NodePickler:
        if self.__node_pickler is None:
            from rdflib.graph import Graph, QuotedGraph
            from rdflib.term import BNode, Literal, URIRef, Variable

            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")
        return self.__node_pickler

    # Database management methods
    # NOTE: Can't find any stores using this, we should consider deprecating it.
    def create(self, configuration: str) -> None:
        self.dispatcher.dispatch(StoreCreatedEvent(configuration=configuration))

    def open(self, configuration: str, create: bool = False) -> Optional[int]:
        """
        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: bool = False) -> None:
        """
        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: str) -> None:
        """
        This destroys the instance of the store identified by the
        configuration string.
        """

    def gc(self) -> None:
        """
        Allows the store to perform any needed garbage collection
        """
        pass

    # RDF APIs
    def add(
        self,
        triple: "_TripleType",
        context: "_ContextType",
        quoted: bool = False,
    ) -> None:
        """
        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=triple, context=context))

    def addN(self, quads: Iterable["_QuadType"]) -> None:  # noqa: N802
        """
        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,
        triple: "_TriplePatternType",
        context: Optional["_ContextType"] = None,
    ) -> None:
        """Remove the set of triples matching the pattern from the store"""
        self.dispatcher.dispatch(TripleRemovedEvent(triple=triple, context=context))

    def triples_choices(
        self,
        triple: Union[
            Tuple[List["_SubjectType"], "_PredicateType", "_ObjectType"],
            Tuple["_SubjectType", List["_PredicateType"], "_ObjectType"],
            Tuple["_SubjectType", "_PredicateType", List["_ObjectType"]],
        ],
        context: Optional["_ContextType"] = None,
    ) -> Generator[
        Tuple[
            _TripleType,
            Iterator[Optional["_ContextType"]],
        ],
        None,
        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 triples
        """
        subject, predicate, object_ = triple
        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

    # type error: Missing return statement
    def triples(  # type: ignore[return]
        self,
        triple_pattern: "_TriplePatternType",
        context: Optional["_ContextType"] = None,
    ) -> Iterator[Tuple["_TripleType", Iterator[Optional["_ContextType"]]]]:
        """
        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?

        :param context: A conjunctive query can be indicated by either
                        providing a value of None, or a specific context can be
                        queries by passing a Graph instance (if store is context aware).
        """
        subject, predicate, object = triple_pattern

    # variants of triples will be done if / when optimization is needed

    # type error: Missing return statement
    def __len__(self, context: Optional["_ContextType"] = None) -> int:  # type: ignore[empty-body]
        """
        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.

        :param context: a graph instance to query or None
        """

    # type error: Missing return statement
    def contexts(  # type: ignore[empty-body]
        self, triple: Optional["_TripleType"] = None
    ) -> Generator["_ContextType", None, None]:
        """
        Generator over all contexts in the graph. If triple is specified,
        a generator over all contexts the triple is in.

        if store is graph_aware, may also return empty contexts

        :returns: a generator over Nodes
        """

    # TODO FIXME: the result of query is inconsistent.
    def query(
        self,
        query: Union["Query", str],
        initNs: Mapping[str, Any],  # noqa: N803
        initBindings: Mapping["str", "Identifier"],  # noqa: N803
        queryGraph: str,  # noqa: N803
        **kwargs: Any,
    ) -> "Result":
        """
        If stores provide their own SPARQL implementation, override this.

        queryGraph is None, a URIRef or '__UNION__'
        If None the graph is specified in the query-string/object
        If URIRef it specifies the graph to query,
        If  '__UNION__' the union of all named graphs should be queried
        (This is used by ConjunctiveGraphs
        Values other than None obviously only makes sense for
        context-aware stores.)

        """

        raise NotImplementedError

    def update(
        self,
        update: Union["Update", str],
        initNs: Mapping[str, Any],  # noqa: N803
        initBindings: Mapping["str", "Identifier"],  # noqa: N803
        queryGraph: str,  # noqa: N803
        **kwargs: Any,
    ) -> None:
        """
        If stores provide their own (SPARQL) Update implementation,
        override this.

        queryGraph is None, a URIRef or '__UNION__'
        If None the graph is specified in the query-string/object
        If URIRef it specifies the graph to query,
        If  '__UNION__' the union of all named graphs should be queried
        (This is used by ConjunctiveGraphs
        Values other than None obviously only makes sense for
        context-aware stores.)

        """

        raise NotImplementedError

    # Optional Namespace methods

    def bind(self, prefix: str, namespace: "URIRef", override: bool = True) -> None:
        """
        :param override: rebind, even if the given namespace is already bound to another prefix.
        """

    def prefix(self, namespace: "URIRef") -> Optional["str"]:
        """"""

    def namespace(self, prefix: str) -> Optional["URIRef"]:
        """ """

    def namespaces(self) -> Iterator[Tuple[str, "URIRef"]]:
        """ """
        # This is here so that the function becomes an empty generator.
        # See https://stackoverflow.com/q/13243766 and
        # https://www.python.org/dev/peps/pep-0255/#why-a-new-keyword-for-yield-why-not-a-builtin-function-instead
        if False:
            yield None  # type: ignore[unreachable]

    # Optional Transactional methods

    def commit(self) -> None:
        """ """

    def rollback(self) -> None:
        """ """

    # Optional graph methods

    def add_graph(self, graph: "Graph") -> None:
        """
        Add a graph to the store, no effect if the graph already
        exists.
        :param graph: a Graph instance
        """
        raise Exception("Graph method called on non-graph_aware store")

    def remove_graph(self, graph: "Graph") -> None:
        """
        Remove a graph from the store, this should also remove all
        triples in the graph

        :param graphid: a Graph instance
        """
        raise Exception("Graph method called on non-graph_aware store")