redhongx
86 lines
1.9 KiB
Python
86 lines
1.9 KiB
Python
# -*- coding: utf-8 -*-
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from __future__ import unicode_literals
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from . import normal
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from . import seg
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from . import tag
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from . import sentiment
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from .sim import bm25
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from .summary import textrank
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from .summary import words_merge
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class SnowNLP(object):
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def __init__(self, doc):
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self.doc = doc
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self.bm25 = bm25.BM25(doc)
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@property
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def words(self):
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return seg.seg(self.doc)
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@property
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def sentences(self):
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return normal.get_sentences(self.doc)
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@property
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def han(self):
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return normal.zh2hans(self.doc)
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@property
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def pinyin(self):
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return normal.get_pinyin(self.doc)
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@property
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def sentiments(self):
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return sentiment.classify(self.doc)
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@property
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def tags(self):
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words = self.words
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tags = tag.tag(words)
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return zip(words, tags)
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@property
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def tf(self):
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return self.bm25.f
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@property
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def idf(self):
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return self.bm25.idf
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def sim(self, doc):
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return self.bm25.simall(doc)
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def summary(self, limit=5):
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doc = []
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sents = self.sentences
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for sent in sents:
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words = seg.seg(sent)
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words = normal.filter_stop(words)
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doc.append(words)
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rank = textrank.TextRank(doc)
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rank.solve()
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ret = []
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for index in rank.top_index(limit):
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ret.append(sents[index])
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return ret
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def keywords(self, limit=5, merge=False):
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doc = []
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sents = self.sentences
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for sent in sents:
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words = seg.seg(sent)
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words = normal.filter_stop(words)
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doc.append(words)
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rank = textrank.KeywordTextRank(doc)
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rank.solve()
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ret = []
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for w in rank.top_index(limit):
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ret.append(w)
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if merge:
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wm = words_merge.SimpleMerge(self.doc, ret)
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return wm.merge()
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return ret
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