Mac Easy 2010 May/Mac Life Ubuntu.iso/casper/filesystem.squashfs/var/lib/python-support/python2.6/rdflib/sparql/graphPattern.pyc

Python Compiled Bytecode | 2009-04-20 | 14.9 KB | 392 lines

# Source Generated with Decompyle++
# File: in.pyc (Python 2.6)

'''
Graph pattern class used by the SPARQL implementation
'''
import sys
import os
import time
import datetime
from rdflib.Literal import Literal
from rdflib.BNode import BNode
from rdflib.URIRef import URIRef
from types import *
from rdflib.sparql import _questChar, Debug, SPARQLError
from rdflib.sparql.Unbound import Unbound

def _createResource(v):
    """Create an RDFLib Literal instance with the corresponding XML
    Schema datatype set. If the variable is already an RDFLib
    resource, it simply returns the resource; otherwise the
    corresponding Literal.  A SPARQLError Exception is raised if the
    type is not implemented.

    The Literal contains the string representation of the variable (as
    Python does it by default) with the corresponding XML Schema URI
    set.

    @param v: Python variable
    @return: either an RDFLib Literal (if 'v' is not an RDFLib Resource), or the same variable if it is already
    an RDFLib resource (ie, Literal, BNode, or URIRef)
    @raise SPARQLError: if the type of 'v' is not implemented
    """
    if isinstance(v, Literal) and isinstance(v, BNode) or isinstance(v, URIRef):
        return v
    return Literal(v)


def _isResQuest(r):
    '''
    Is \'r\' a request string (ie, of the form "?XXX")?

    @rtype: Boolean
    '''
    if r and isinstance(r, basestring) and r[0] == _questChar:
        return True
    return False


class GraphPattern:
    '''
    Storage of one Graph Pattern, ie, the pattern tuples and the
    possible (functional) constraints (filters)
    '''

    def __init__(self, patterns = []):
        '''
        @param patterns: an initial list of graph pattern tuples
        '''
        self.patterns = []
        self.constraints = []
        self.unbounds = []
        self.bnodes = { }
        if type(patterns) == list:
            self.addPatterns(patterns)
        elif type(patterns) == tuple:
            self.addPattern(patterns)
        else:
            raise SPARQLError('illegal argument, pattern must be a tuple or a list of tuples')
        return type(patterns) == list


    def _generatePattern(self, tupl):
        """
        Append a tuple to the local patterns. Possible type literals
        are converted to real literals on the fly.  Each tuple should
        be contain either 3 elements (for an RDF Triplet pattern) or
        four, where the fourth element is a per-pattern constraint
        (filter). (The general constraint of SPARQL can be optimized
        by assigning a constraint to a specific pattern; because it
        stops the graph expansion, its usage might be much more
        optimal than the the 'global' constraint).

        @param tupl: either a three or four element tuple
        """
        if type(tupl) != tuple:
            raise SPARQLError('illegal argument, pattern must be a tuple, got %s' % type(tupl))
        type(tupl) != tuple
        if len(tupl) != 3 and len(tupl) != 4:
            raise SPARQLError('illegal argument, pattern must be a tuple of 3 or 4 element, got %s' % len(tupl))
        len(tupl) != 4
        if len(tupl) == 3:
            (s, p, o) = tupl
            f = None
        else:
            (s, p, o, f) = tupl
        final = []
        for c in (s, p, o):
            if _isResQuest(c):
                if c not in self.unbounds:
                    self.unbounds.append(c)

                final.append(c)
                continue
            if isinstance(c, BNode):
                final.append(c)
                continue
            final.append(_createResource(c))

        final.append(f)
        return tuple(final)


    def addPattern(self, tupl):
        """
        Append a tuple to the local patterns. Possible type literals
        are converted to real literals on the fly.  Each tuple should
        be contain either 3 elements (for an RDF Triplet pattern) or
        four, where the fourth element is a per-pattern constraint
        (filter). (The general constraint of SPARQL can be optimized
        by assigning a constraint to a specific pattern; because it
        stops the graph expansion, its usage might be much more
        optimal than the the 'global' constraint).

        @param tupl: either a three or four element tuple
        """
        self.patterns.append(self._generatePattern(tupl))


    def insertPattern(self, tupl):
        """
        Insert a tuple to to the start of local patterns. Possible
        type literals are converted to real literals on the fly.  Each
        tuple should be contain either 3 elements (for an RDF Triplet
        pattern) or four, where the fourth element is a per-pattern
        constraint (filter). (The general constraint of SPARQL can be
        optimized by assigning a constraint to a specific pattern;
        because it stops the graph expansion, its usage might be much
        more optimal than the the 'global' constraint).

        Semantically, the behaviour induced by a graphPattern does not
        depend on the order of the patterns. However, due to the
        behaviour of the expansion algorithm, users may control the
        speed somewhat by adding patterns that would 'cut' the
        expansion tree soon (ie, patterns that reduce the available
        triplets significantly). API users may be able to do that,
        hence this additional method.

        @param tupl: either a three or four element tuple
        """
        self.patterns.insert(0, self._generatePattern(tupl))


    def addPatterns(self, lst):
        """
        Append a list of tuples to the local patterns. Possible type
        literals are converted to real literals on the fly.  Each
        tuple should be contain either three elements (for an RDF
        Triplet pattern) or four, where the fourth element is a
        per-pattern constraint. (The general constraint of SPARQL can
        be optimized by assigning a constraint to a specific pattern;
        because it stops the graph expansion, its usage might be much
        more optimal than the the 'global' constraint).

        @param lst: list consisting of either a three or four element tuples
        """
        for l in lst:
            self.addPattern(l)



    def insertPatterns(self, lst):
        """
        Insert a list of tuples to the start of the local
        patterns. Possible type literals are converted to real
        literals on the fly.  Each tuple should be contain either
        three elements (for an RDF Triplet pattern) or four, where the
        fourth element is a per-pattern constraint. (The general
        constraint of SPARQL can be optimized by assigning a
        constraint to a specific pattern; because it stops the graph
        expansion, its usage might be much more optimal than the the
        'global' constraint).

        Semantically, the behaviour induced by a graphPattern does not
        depend on the order of the patterns. However, due to the
        behaviour of the expansion algorithm, users may control the
        speed somewhat by adding patterns that would 'cut' the
        expansion tree soon (ie, patterns that reduce the available
        triplets significantly). API users may be able to do that,
        hence this additional method.

        @param lst: list consisting of either a three or four element tuples
        """
        for i in xrange(len(lst) - 1, -1, -1):
            self.insertPattern(lst[i])



    def addConstraint(self, func):
        """
        Add a global filter constraint to the graph pattern. 'func'
        must be a method with a single input parameter (a dictionary)
        returning a boolean. This method is I{added} to previously
        added methods, ie, I{all} methods must return True to accept a
        binding.

        @param func: filter function
        """
        if type(func) == FunctionType:
            self.constraints.append(func)
        else:
            raise SPARQLError('illegal argument, constraint must be a function type, got %s' % type(func))
        return type(func) == FunctionType


    def addConstraints(self, lst):
        '''
        Add a list of global filter constraints to the graph
        pattern. Each function in the list must be a method with a
        single input parameter (a dictionary) returning a
        boolean. These methods are I{added} to previously added
        methods, ie, I{all} methods must return True to accept a
        binding.

        @param lst: list of functions
        '''
        for l in lst:
            self.addConstraint(l)



    def construct(self, tripleStore, bindings):
        '''
        Add triples to a tripleStore based on a variable bindings of
        the patterns stored locally.  The triples are patterned by the
        current Graph Pattern. The method is used to construct a graph
        after a successful querying.

        @param tripleStore: an (rdflib) Triple Store
        @param bindings: dictionary
        '''
        localBnodes = { }
        for c in self.bnodes:
            localBnodes[c] = BNode()


        def bind(st):
            if _isResQuest(st):
                if st in bindings:
                    return bindings[st]
                if isinstance(self, GraphPattern2):
                    return st
                return None
            _isResQuest(st)
            if isinstance(st, BNode):
                for c in self.bnodes:
                    if self.bnodes[c] == st:
                        return localBnodes[c]

                return st
            return st

        for pattern in self.patterns:
            (s, p, o, f) = pattern
            triplet = []
            valid = True
            for res in (s, p, o):
                val = bind(res)
                if val != None:
                    triplet.append(val)
                    continue
                (None, None, None)
                valid = False

            if valid:
                tripleStore.add(tuple(triplet))
                continue



    def __add__(self, other):
        '''Adding means concatenating all the patterns and filters arrays'''
        retval = GraphPattern()
        retval += self
        retval += other
        return retval


    def __iadd__(self, other):
        '''Adding means concatenating all the patterns and filters arrays'''
        self.patterns += other.patterns
        self.constraints += other.constraints
        for c in other.unbounds:
            if c not in self.unbounds:
                self.unbounds.append(c)
                continue
            self

        for c in other.bnodes:
            if c not in self.bnodes:
                self.bnodes[c] = other.bnodes[c]
                continue
            self

        return self


    def __repr__(self):
        retval = '   Patterns:    %s\n' % self.patterns
        retval += '   Constraints: %s\n' % self.constraints
        retval += '   Unbounds:    %s\n' % self.unbounds
        return retval


    def __str__(self):
        return self.__repr__()


    def isEmpty(self):
        '''Is the pattern empty?
        @rtype: Boolean
        '''
        return len(self.patterns) == 0



class BasicGraphPattern(GraphPattern):
    '''One, justified, problem with the current definition of L{GraphPattern<GraphPattern>} is that it
    makes it difficult for users to use a literal of the type "?XXX", because any string beginning
    with "?" will be considered to be an unbound variable. The only way of doing this is that the user
    explicitly creates a Literal object and uses that as part of the pattern.

    This class is a superclass of L{GraphPattern<GraphPattern>} which does I{not} do this, but requires the
    usage of a separate variable class instance'''

    def __init__(self, patterns = []):
        '''
        @param patterns: an initial list of graph pattern tuples
        '''
        GraphPattern.__init__(self, patterns)


    def _generatePattern(self, tupl):
        """
        Append a tuple to the local patterns. Possible type literals
        are converted to real literals on the fly.  Each tuple should
        be contain either 3 elements (for an RDF Triplet pattern) or
        four, where the fourth element is a per-pattern constraint
        (filter). (The general constraint of SPARQL can be optimized
        by assigning a constraint to a specific pattern; because it
        stops the graph expansion, its usage might be much more
        optimal than the the 'global' constraint).

        @param tupl: either a three or four element tuple
        """
        if type(tupl) != tuple:
            raise SPARQLError('illegal argument, pattern must be a tuple, got %s' % type(tupl))
        type(tupl) != tuple
        if len(tupl) != 3 and len(tupl) != 4:
            raise SPARQLError('illegal argument, pattern must be a tuple of 3 or 4 element, got %s' % len(tupl))
        len(tupl) != 4
        if len(tupl) == 3:
            (s, p, o) = tupl
            f = None
        else:
            (s, p, o, f) = tupl
        final = []
        for c in (s, p, o):
            if isinstance(c, Unbound):
                if c.name not in self.unbounds:
                    self.unbounds.append(c.name)

                final.append(c.name)
                continue
            if isinstance(c, BNode):
                final.append(c)
                continue
            final.append(_createResource(c))

        final.append(f)
        return tuple(final)


if __name__ == '__main__':
    v1 = Unbound('a')
    g = BasicGraphPattern([
        ('a', '?b', 24),
        ('?r', '?c', 12345),
        (v1, '?c', 3333)])
    print g