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- # encoding=utf-8
- from __future__ import unicode_literals
- from whoosh.analysis import RegexAnalyzer, LowercaseFilter, StopFilter, StemFilter
- from whoosh.analysis import Tokenizer, Token
- from whoosh.lang.porter import stem
- import jieba
- import re
- STOP_WORDS = frozenset(('a', 'an', 'and', 'are', 'as', 'at', 'be', 'by', 'can',
- 'for', 'from', 'have', 'if', 'in', 'is', 'it', 'may',
- 'not', 'of', 'on', 'or', 'tbd', 'that', 'the', 'this',
- 'to', 'us', 'we', 'when', 'will', 'with', 'yet',
- 'you', 'your', '的', '了', '和'))
- accepted_chars = re.compile(r"[\u4E00-\u9FD5]+")
- class ChineseTokenizer(Tokenizer):
- def __call__(self, text, **kargs):
- words = jieba.tokenize(text, mode="search")
- token = Token()
- for (w, start_pos, stop_pos) in words:
- if not accepted_chars.match(w) and len(w) <= 1:
- continue
- token.original = token.text = w
- token.pos = start_pos
- token.startchar = start_pos
- token.endchar = stop_pos
- yield token
- def ChineseAnalyzer(stoplist=STOP_WORDS, minsize=1, stemfn=stem, cachesize=50000):
- return (ChineseTokenizer() | LowercaseFilter() |
- StopFilter(stoplist=stoplist, minsize=minsize) |
- StemFilter(stemfn=stemfn, ignore=None, cachesize=cachesize))
|
