def test_regular_or():
ix = get_index()
with ix.searcher() as s:
oq = Or([Term("text", "bravo"), Term("text", "alfa")])
m = oq.matcher(s)
while m.is_active():
orig = s.stored_fields(m.id())["text"]
for span in m.spans():
v = orig[span.start]
assert v == "bravo" or v == "alfa"
m.next()
def matcher(self, searcher, context=None):
fieldname = self.fieldname
constantscore = self.constantscore
reader = searcher.reader()
qs = [Term(fieldname, word) for word in self._btexts(reader)]
if not qs:
return matching.NullMatcher()
if len(qs) == 1:
# If there's only one term, just use it
q = qs[0]
elif constantscore or len(qs) > self.TOO_MANY_CLAUSES:
# If there's so many clauses that an Or search would take forever,
# trade memory for time and just find all the matching docs and
# serve them as one ListMatcher
fmt = searcher.schema[fieldname].format
doc_to_values = defaultdict(list)
doc_to_weights = defaultdict(float)
for q in qs:
m = q.matcher(searcher)
while m.is_active():
docnum = m.id()
doc_to_values[docnum].append(m.value())
if not constantscore:
doc_to_weights[docnum] += m.weight()
m.next()
docnums = sorted(doc_to_values.keys())
# This is a list of lists of value strings -- ListMatcher will
# actually do the work of combining multiple values if the user
# asks for them
values = [doc_to_values[docnum] for docnum in docnums]
kwargs = {"values": values, "format": fmt}
if constantscore:
kwargs["all_weights"] = self.boost
else:
kwargs["weights"] = [doc_to_weights[docnum]
for docnum in docnums]
#return matching.ListMatcher(docnums, term=term, **kwargs)
return matching.ListMatcher(docnums, **kwargs)
else:
# The default case: Or the terms together
from whoosh.query import Or
q = Or(qs)
m = q.matcher(searcher, context)
#m = matching.SingleTermMatcher(m, term)
return m
def matcher(self, searcher, weighting=None):
fieldname = self.fieldname
constantscore = self.constantscore
reader = searcher.reader()
qs = [Term(fieldname, word) for word in self._words(reader)]
if not qs:
return matching.NullMatcher()
if len(qs) == 1:
# If there's only one term, just use it
q = qs[0]
elif constantscore or len(qs) > self.TOO_MANY_CLAUSES:
# If there's so many clauses that an Or search would take forever,
# trade memory for time and just find all the matching docs serve
# them up as one or more ListMatchers
fmt = searcher.schema[fieldname].format
doc_to_values = defaultdict(list)
doc_to_weights = defaultdict(float)
for q in qs:
m = q.matcher(searcher)
while m.is_active():
docnum = m.id()
doc_to_values[docnum].append(m.value())
if not constantscore:
doc_to_weights[docnum] += m.weight()
m.next()
docnums = sorted(doc_to_values.keys())
# This is a list of lists of value strings -- ListMatcher will
# actually do the work of combining multiple values if the user
# asks for them
values = [doc_to_values[docnum] for docnum in docnums]
kwargs = {"values": values, "format": fmt}
if constantscore:
kwargs["all_weights"] = self.boost
else:
kwargs["weights"] = [
doc_to_weights[docnum] for docnum in docnums
]
return matching.ListMatcher(docnums, **kwargs)
else:
# The default case: Or the terms together
from whoosh.query import Or
q = Or(qs)
return q.matcher(searcher, weighting=weighting)
