##############################################################################
#
# Copyright (c) 2001 Zope Corporation and Contributors. All Rights Reserved.
#
# This software is subject to the provisions of the Zope Public License,
# Version 2.0 (ZPL). A copy of the ZPL should accompany this distribution.
# THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED
# WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED
# WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS
# FOR A PARTICULAR PURPOSE
#
#############################################################################
from Lexicon import Lexicon
from Splitter import Splitter
from UnTextIndex import Or
import re, string
from BTrees.IIBTree import IISet, union, IITreeSet
from BTrees.OIBTree import OIBTree
from BTrees.IOBTree import IOBTree
from BTrees.OOBTree import OOBTree
from randid import randid
class GlobbingLexicon(Lexicon):
"""Lexicon which supports basic globbing function ('*' and '?').
This lexicon keeps several data structures around that are useful
for searching. They are:
'_lexicon' -- Contains the mapping from word => word_id
'_inverseLex' -- Contains the mapping from word_id => word
'_digrams' -- Contains a mapping from digram => word_id
Before going further, it is necessary to understand what a digram is,
as it is a core component of the structure of this lexicon. A digram
is a two-letter sequence in a word. For example, the word 'zope'
would be converted into the digrams::
['$z', 'zo', 'op', 'pe', 'e$']
where the '$' is a word marker. It is used at the beginning and end
of the words. Those digrams are significant.
"""
multi_wc = '*'
single_wc = '?'
eow = '$'
def __init__(self):
self.clear()
def clear(self):
self._lexicon = OIBTree()
self._inverseLex = IOBTree()
self._digrams = OOBTree()
def _convertBTrees(self, threshold=200):
Lexicon._convertBTrees(self, threshold)
if type(self._digrams) is OOBTree: return
from BTrees.convert import convert
_digrams=self._digrams
self._digrams=OOBTree()
self._digrams._p_jar=self._p_jar
convert(_digrams, self._digrams, threshold, IITreeSet)
def createDigrams(self, word):
"""Returns a list with the set of digrams in the word."""
digrams = list(word)
digrams.append(self.eow)
last = self.eow
for i in range(len(digrams)):
last, digrams[i] = digrams[i], last + digrams[i]
return digrams
def getWordId(self, word):
"""Provided 'word', return the matching integer word id."""
if self._lexicon.has_key(word):
return self._lexicon[word]
else:
return self.assignWordId(word)
set = getWordId # Kludge for old code
def getWord(self, wid):
return self._inverseLex.get(wid, None)
def assignWordId(self, word):
"""Assigns a new word id to the provided word, and return it."""
# Double check it's not in the lexicon already, and if it is, just
# return it.
if self._lexicon.has_key(word):
return self._lexicon[word]
# Get word id. BBB Backward compat pain.
inverse=self._inverseLex
try: insert=inverse.insert
except AttributeError:
# we have an "old" BTree object
if inverse:
wid=inverse.keys()[-1]+1
else:
self._inverseLex=IOBTree()
wid=1
inverse[wid] = word
else:
# we have a "new" IOBTree object
wid=randid()
while not inverse.insert(wid, word):
wid=randid()
self._lexicon[word] = wid
# Now take all the digrams and insert them into the digram map.
for digram in self.createDigrams(word):
set = self._digrams.get(digram, None)
if set is None:
self._digrams[digram] = set = IISet()
set.insert(wid)
return wid
def get(self, pattern):
""" Query the lexicon for words matching a pattern."""
wc_set = [self.multi_wc, self.single_wc]
digrams = []
globbing = 0
for i in range(len(pattern)):
if pattern[i] in wc_set:
globbing = 1
continue
if i == 0:
digrams.insert(i, (self.eow + pattern[i]) )
digrams.append((pattern[i] + pattern[i+1]))
else:
try:
if pattern[i+1] not in wc_set:
digrams.append( pattern[i] + pattern[i+1] )
except IndexError:
digrams.append( (pattern[i] + self.eow) )
if not globbing:
result = self._lexicon.get(pattern, None)
if result is None:
return ()
return (result, )
## now get all of the intsets that contain the result digrams
result = None
for digram in digrams:
result=union(result, self._digrams.get(digram, None))
if not result:
return ()
else:
## now we have narrowed the list of possible candidates
## down to those words which contain digrams. However,
## some words may have been returned that match digrams,
## but do not match 'pattern'. This is because some words
## may contain all matching digrams, but in the wrong
## order.
expr = re.compile(self.createRegex(pattern))
words = []
hits = IISet()
for x in result:
if expr.match(self._inverseLex[x]):
hits.insert(x)
return hits
def __getitem__(self, word):
""" """
return self.get(word)
def query_hook(self, q):
"""expand wildcards"""
ListType = type([])
i = len(q) - 1
while i >= 0:
e = q[i]
if isinstance(e, ListType):
self.query_hook(e)
elif ( (self.multi_wc in e) or
(self.single_wc in e) ):
wids = self.get(e)
words = []
for wid in wids:
if words:
words.append(Or)
words.append(wid)
if not words:
# if words is empty, return something that will make
# textindex's __getitem__ return an empty result list
words.append('')
q[i] = words
i = i - 1
return q
def Splitter(self, astring, words=None):
""" wrap the splitter """
## don't do anything, less efficient but there's not much
## sense in stemming a globbing lexicon.
return Splitter(astring)
def createRegex(self, pat):
"""Translate a PATTERN to a regular expression.
There is no way to quote meta-characters.
"""
# Remove characters that are meaningful in a regex
transTable = string.maketrans("", "")
result = string.translate(pat, transTable,
r'()&|!@#$%^{}\<>.')
# First, deal with multi-character globbing
result = string.replace(result, '*', '.*')
# Next, we need to deal with single-character globbing
result = string.replace(result, '?', '.')
return "%s$" % result