def NearNode(self, node):
""" near search isn't working yet """
word_nodes = []
word_nodes = flatten_NearNode(node.getValue(), word_nodes)
sets = [self(n) for n in word_nodes]
rs = intersectionResultSets(sets)
raise NotImplementedError('Near search not implemented yet')
def NearNode(self, node):
""" near search isn't working yet """
word_nodes = []
word_nodes = flatten_NearNode(node.getValue(), word_nodes)
sets = [self(n) for n in word_nodes]
rs = intersectionResultSets(sets)
raise NotImplementedError('Near search not implemented yet')
def PhraseNode(self, node):
# Dealing with PhraseNodes is somewhat tricks
# node.getValue() should return a sequence of WordNodes representing
# the terms of the phrase
# first tcreate he a copy of the ordered(!) terms
words = [n.getValue() for n in node.getValue()]
# So first perform a simple word search for all terms
sets = [self(n) for n in node.getValue()]
# Now intersect the results (AND). This descreases the number of documents
# to be checked.
rs = intersectionResultSets(sets)
# Now check if the found documents really contain the words as phrase
return lookup_by_phrase(self.searchrequest, rs.getDocids(), words,
self._getField(node))
def PhraseNode(self, node):
# Dealing with PhraseNodes is somewhat tricks
# node.getValue() should return a sequence of WordNodes representing
# the terms of the phrase
# first tcreate he a copy of the ordered(!) terms
words = [n.getValue() for n in node.getValue()]
# So first perform a simple word search for all terms
sets = [self(n) for n in node.getValue()]
# Now intersect the results (AND). This descreases the number of documents
# to be checked.
rs = intersectionResultSets(sets)
# Now check if the found documents really contain the words as phrase
return lookup_by_phrase(self.searchrequest,
rs.getDocids(),
words,
self._getField(node))
def AndNode(self, node):
sets = [self(n) for n in node.getValue()]
return intersectionResultSets(sets)
def AndNode(self, node):
sets = [self(n) for n in node.getValue()]
return intersectionResultSets(sets)
