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