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使用re在多个标签中查找文本

2015-04-17 59 views
1

我正在尝试查找python中标签内的所有字符。以下是我的代码：使用re在多个标签中查找文本

import re 

text=''' <parse>(ROOT 
     (S 
     (NP (NNP Stanford) (NNP University)) 
     (VP (VBZ is) 
     (ADJP (JJ located) 
     (PP (IN in) 
     (NP (NNP California))))) 
     (. .))) 

     </parse> 
    <dependencies type="basic-dependencies"> 
     <dep type="root"> 
     <governor idx="0">ROOT</governor> 
     <dependent idx="4">located</dependent> 
     </dep> 
     <dep type="nn"> 
     <governor idx="2">University</governor> 
     <dependent idx="1">Stanford</dependent> 
     </dep> 
     <dep type="nsubj"> 
     <governor idx="4">located</governor> 
     <dependent idx="2">University</dependent> 
     </dep> 
     <dep type="cop"> 
     <governor idx="4">located</governor> 
     <dependent idx="3">is</dependent> 
     </dep> 
     <dep type="prep"> 
     <governor idx="4">located</governor> 
     <dependent idx="5">in</dependent> 
     </dep> 
     <dep type="pobj"> 
     <governor idx="5">in</governor> 
     <dependent idx="6">California</dependent> 
     </dep> 
    </dependencies> 
    <dependencies type="collapsed-dependencies"> 
     <dep type="root"> 
     <governor idx="0">ROOT</governor> 
     <dependent idx="4">located</dependent> 
     </dep> 
     <dep type="nn"> 
     <governor idx="2">University</governor> 
     <dependent idx="1">Stanford</dependent> 
     </dep> 
     <dep type="nsubj"> 
     <governor idx="4">located</governor> 
     <dependent idx="2">University</dependent> 
     </dep> 
     <dep type="cop"> 
     <governor idx="4">located</governor> 
     <dependent idx="3">is</dependent> 
     </dep> 
     <dep type="prep_in"> 
     <governor idx="4">located</governor> 
     <dependent idx="6">California</dependent> 
     </dep> 
    </dependencies> 
    <dependencies type="collapsed-ccprocessed-dependencies"> 
     <dep type="root"> 
     <governor idx="0">ROOT</governor> 
     <dependent idx="4">located</dependent> 
     </dep> 
     <dep type="nn"> 
     <governor idx="2">University</governor> 
     <dependent idx="1">Stanford</dependent> 
     </dep> 
     <dep type="nsubj"> 
     <governor idx="4">located</governor> 
     <dependent idx="2">University</dependent> 
     </dep> 
     <dep type="cop"> 
     <governor idx="4">located</governor> 
     <dependent idx="3">is</dependent> 
     </dep> 
     <dep type="prep_in"> 
     <governor idx="4">located</governor> 
     <dependent idx="6">California</dependent> 
     </dep> 
    </dependencies> 
    </sentence> 
    <sentence id="2"> 
    <tokens> 
     <token id="1"> 
     <word>It</word> 
     <lemma>it</lemma> 
     <CharacterOffsetBegin>46</CharacterOffsetBegin> 
     <CharacterOffsetEnd>48</CharacterOffsetEnd> 
     <POS>PRP</POS> 
     <NER>O</NER> 
     </token> 
     <token id="2"> 
     <word>is</word> 
     <lemma>be</lemma> 
     <CharacterOffsetBegin>49</CharacterOffsetBegin> 
     <CharacterOffsetEnd>51</CharacterOffsetEnd> 
     <POS>VBZ</POS> 
     <NER>O</NER> 
     </token> 
     <token id="3"> 
     <word>a</word> 
     <lemma>a</lemma> 
     <CharacterOffsetBegin>52</CharacterOffsetBegin> 
     <CharacterOffsetEnd>53</CharacterOffsetEnd> 
     <POS>DT</POS> 
     <NER>O</NER> 
     </token> 
     <token id="4"> 
     <word>great</word> 
     <lemma>great</lemma> 
     <CharacterOffsetBegin>54</CharacterOffsetBegin> 
     <CharacterOffsetEnd>59</CharacterOffsetEnd> 
     <POS>JJ</POS> 
     <NER>O</NER> 
     </token> 
     <token id="5"> 
     <word>university</word> 
     <lemma>university</lemma> 
     <CharacterOffsetBegin>60</CharacterOffsetBegin> 
     <CharacterOffsetEnd>70</CharacterOffsetEnd> 
     <POS>NN</POS> 
     <NER>O</NER> 
     </token> 
     <token id="6"> 
     <word>,</word> 
     <lemma>,</lemma> 
     <CharacterOffsetBegin>70</CharacterOffsetBegin> 
     <CharacterOffsetEnd>71</CharacterOffsetEnd> 
     <POS>,</POS> 
     <NER>O</NER> 
     </token> 
     <token id="7"> 
     <word>founded</word> 
     <lemma>found</lemma> 
     <CharacterOffsetBegin>72</CharacterOffsetBegin> 
     <CharacterOffsetEnd>79</CharacterOffsetEnd> 
     <POS>VBN</POS> 
     <NER>O</NER> 
     </token> 
     <token id="8"> 
     <word>in</word> 
     <lemma>in</lemma> 
     <CharacterOffsetBegin>80</CharacterOffsetBegin> 
     <CharacterOffsetEnd>82</CharacterOffsetEnd> 
     <POS>IN</POS> 
     <NER>O</NER> 
     </token> 
     <token id="9"> 
     <word>1891</word> 
     <lemma>1891</lemma> 
     <CharacterOffsetBegin>83</CharacterOffsetBegin> 
     <CharacterOffsetEnd>87</CharacterOffsetEnd> 
     <POS>CD</POS> 
     <NER>DATE</NER> 
     <NormalizedNER>1891</NormalizedNER> 
     <Timex tid="t1" type="DATE">1891</Timex> 
     </token> 
     <token id="10"> 
     <word>.</word> 
     <lemma>.</lemma> 
     <CharacterOffsetBegin>87</CharacterOffsetBegin> 
     <CharacterOffsetEnd>88</CharacterOffsetEnd> 
     <POS>.</POS> 
     <NER>O</NER> 
     </token> 
    </tokens> 
    <parse>(ROOT 
     (S 
     (NP (PRP It)) 
     (VP (VBZ is) 
     (NP 
     (NP (DT a) (JJ great) (NN university)) 
     (, ,) 
     (VP (VBN founded) 
     (PP (IN in) 
     (NP (CD 1891)))))) 
     (. .))) 

     </parse> 
    <dependencies type="basic-dependencies"> 
     <dep type="root"> 
     <governor idx="0">ROOT</governor> 
     <dependent idx="5">university</dependent> 
     </dep> 
     <dep type="nsubj"> 
     <governor idx="5">university</governor> 
     <dependent idx="1">It</dependent> 
     </dep> 
     <dep type="cop"> 
     <governor idx="5">university</governor> 
     <dependent idx="2">is</dependent> 
     </dep> 
     <dep type="det"> 
     <governor idx="5">university</governor> 
     <dependent idx="3">a</dependent> 
     </dep> 
     <dep type="amod"> 
     <governor idx="5">university</governor> 
     <dependent idx="4">great</dependent> 
     </dep> 
     <dep type="vmod"> 
     <governor idx="5">university</governor> 
     <dependent idx="7">founded</dependent> 
     </dep> 
     <dep type="prep"> 
     <governor idx="7">founded</governor> 
     <dependent idx="8">in</dependent> 
     </dep> 
     <dep type="pobj"> 
     <governor idx="8">in</governor> 
     <dependent idx="9">1891</dependent> 
     </dep> 
    </dependencies> 
    <dependencies type="collapsed-dependencies"> 
     <dep type="root"> 
     <governor idx="0">ROOT</governo''' 


p1=re.compile("<parse>(.*)</parse>",re.DOTALL) 
parse=p1.findall(text) 
print parse

输出上面的代码是：

['(ROOT\n   (S\n   (NP (NNP Stanford) (NNP University))\n   (VP (VBZ is)\n   (ADJP (JJ located)\n   (PP (IN in)\n   (NP (NNP California)))))\n   (. .)))\n\n   </parse>\n  <dependencies type="basic-dependencies">\n   <dep type="root">\n   <governor idx="0">ROOT</governor>\n   <dependent idx="4">located</dependent>\n   </dep>\n   <dep type="nn">\n   <governor idx="2">University</governor>\n   <dependent idx="1">Stanford</dependent>\n   </dep>\n   <dep type="nsubj">\n   <governor idx="4">located</governor>\n   <dependent idx="2">University</dependent>\n   </dep>\n   <dep type="cop">\n   <governor idx="4">located</governor>\n   <dependent idx="3">is</dependent>\n   </dep>\n   <dep type="prep">\n   <governor idx="4">located</governor>\n   <dependent idx="5">in</dependent>\n   </dep>\n   <dep type="pobj">\n   <governor idx="5">in</governor>\n   <dependent idx="6">California</dependent>\n   </dep>\n  </dependencies>\n  <dependencies type="collapsed-dependencies">\n   <dep type="root">\n   <governor idx="0">ROOT</governor>\n   <dependent idx="4">located</dependent>\n   </dep>\n   <dep type="nn">\n   <governor idx="2">University</governor>\n   <dependent idx="1">Stanford</dependent>\n   </dep>\n   <dep type="nsubj">\n   <governor idx="4">located</governor>\n   <dependent idx="2">University</dependent>\n   </dep>\n   <dep type="cop">\n   <governor idx="4">located</governor>\n   <dependent idx="3">is</dependent>\n   </dep>\n   <dep type="prep_in">\n   <governor idx="4">located</governor>\n   <dependent idx="6">California</dependent>\n   </dep>\n  </dependencies>\n  <dependencies type="collapsed-ccprocessed-dependencies">\n   <dep type="root">\n   <governor idx="0">ROOT</governor>\n   <dependent idx="4">located</dependent>\n   </dep>\n   <dep type="nn">\n   <governor idx="2">University</governor>\n   <dependent idx="1">Stanford</dependent>\n   </dep>\n   <dep type="nsubj">\n   <governor idx="4">located</governor>\n   <dependent idx="2">University</dependent>\n   </dep>\n   <dep type="cop">\n   <governor idx="4">located</governor>\n   <dependent idx="3">is</dependent>\n   </dep>\n   <dep type="prep_in">\n   <governor idx="4">located</governor>\n   <dependent idx="6">California</dependent>\n   </dep>\n  </dependencies>\n  </sentence>\n  <sentence id="2">\n  <tokens>\n   <token id="1">\n   <word>It</word>\n   <lemma>it</lemma>\n   <CharacterOffsetBegin>46</CharacterOffsetBegin>\n   <CharacterOffsetEnd>48</CharacterOffsetEnd>\n   <POS>PRP</POS>\n   <NER>O</NER>\n   </token>\n   <token id="2">\n   <word>is</word>\n   <lemma>be</lemma>\n   <CharacterOffsetBegin>49</CharacterOffsetBegin>\n   <CharacterOffsetEnd>51</CharacterOffsetEnd>\n   <POS>VBZ</POS>\n   <NER>O</NER>\n   </token>\n   <token id="3">\n   <word>a</word>\n   <lemma>a</lemma>\n   <CharacterOffsetBegin>52</CharacterOffsetBegin>\n   <CharacterOffsetEnd>53</CharacterOffsetEnd>\n   <POS>DT</POS>\n   <NER>O</NER>\n   </token>\n   <token id="4">\n   <word>great</word>\n   <lemma>great</lemma>\n   <CharacterOffsetBegin>54</CharacterOffsetBegin>\n   <CharacterOffsetEnd>59</CharacterOffsetEnd>\n   <POS>JJ</POS>\n   <NER>O</NER>\n   </token>\n   <token id="5">\n   <word>university</word>\n   <lemma>university</lemma>\n   <CharacterOffsetBegin>60</CharacterOffsetBegin>\n   <CharacterOffsetEnd>70</CharacterOffsetEnd>\n   <POS>NN</POS>\n   <NER>O</NER>\n   </token>\n   <token id="6">\n   <word>,</word>\n   <lemma>,</lemma>\n   <CharacterOffsetBegin>70</CharacterOffsetBegin>\n   <CharacterOffsetEnd>71</CharacterOffsetEnd>\n   <POS>,</POS>\n   <NER>O</NER>\n   </token>\n   <token id="7">\n   <word>founded</word>\n   <lemma>found</lemma>\n   <CharacterOffsetBegin>72</CharacterOffsetBegin>\n   <CharacterOffsetEnd>79</CharacterOffsetEnd>\n   <POS>VBN</POS>\n   <NER>O</NER>\n   </token>\n   <token id="8">\n   <word>in</word>\n   <lemma>in</lemma>\n   <CharacterOffsetBegin>80</CharacterOffsetBegin>\n   <CharacterOffsetEnd>82</CharacterOffsetEnd>\n   <POS>IN</POS>\n   <NER>O</NER>\n   </token>\n   <token id="9">\n   <word>1891</word>\n   <lemma>1891</lemma>\n   <CharacterOffsetBegin>83</CharacterOffsetBegin>\n   <CharacterOffsetEnd>87</CharacterOffsetEnd>\n   <POS>CD</POS>\n   <NER>DATE</NER>\n   <NormalizedNER>1891</NormalizedNER>\n   <Timex tid="t1" type="DATE">1891</Timex>\n   </token>\n   <token id="10">\n   <word>.</word>\n   <lemma>.</lemma>\n   <CharacterOffsetBegin>87</CharacterOffsetBegin>\n   <CharacterOffsetEnd>88</CharacterOffsetEnd>\n   <POS>.</POS>\n   <NER>O</NER>\n   </token>\n  </tokens>\n  <parse>(ROOT\n   (S\n   (NP (PRP It))\n   (VP (VBZ is)\n   (NP\n   (NP (DT a) (JJ great) (NN university))\n   (, ,)\n   (VP (VBN founded)\n   (PP (IN in)\n   (NP (CD 1891))))))\n   (. .)))\n\n   ']

但我只需要解析标签中的人物，没有别的。请解决这个问题。以下应该是输出：

'(ROOT\n   (S\n   (NP (NNP Stanford) (NNP University))\n   (VP (VBZ is)\n   (ADJP (JJ located)\n   (PP (IN in)\n   (NP (NNP California)))))\n   (. .)))\n\n   
(ROOT\n   (S\n   (NP (PRP It))\n   (VP (VBZ is)\n   (NP\n   (NP (DT a) (JJ great) (NN university))\n   (, ,)\n   (VP (VBN founded)\n   (PP (IN in)\n   (NP (CD 1891))))))\n   (. .)))\n\n

来源

2015-04-17 UserP

+3

使用XML解析器。 – 2015-04-17 09:28:36

+0

请阅读http://stackoverflow.com/help/mcve – jonrsharpe

+0

'p1 = re.compile（“（。*？）”，re.DOTALL）' –

回答

1

如果你需要使用正则表达式，用这一个：

(?s)<parse>(.*?)</parse>

见demo

import re 
p = re.compile(ur'(?s)<parse>(.*?)</parse>') 
parse = re.findall(p, text) 
print parse

来源

2015-04-17 09:32:24

+0

感谢您节省了一天的时间。 – UserP

+0

您随时欢迎您！ +1一个很好的问题。 –

0

使用BeautifulSoup解析器。

>>> from bs4 import BeautifulSoup 
>>> soup = BeautifulSoup(text) 
>>> for i in soup.select('parse'): 
     print(i.text) 


(ROOT 
     (S 
     (NP (NNP Stanford) (NNP University)) 
     (VP (VBZ is) 
     (ADJP (JJ located) 
     (PP (IN in) 
     (NP (NNP California))))) 
     (. .))) 


(ROOT 
     (S 
     (NP (PRP It)) 
     (VP (VBZ is) 
     (NP 
     (NP (DT a) (JJ great) (NN university)) 
     (, ,) 
     (VP (VBN founded) 
     (PP (IN in) 
     (NP (CD 1891)))))) 
     (. .)))

来源

2015-04-17 09:32:11

+0

** + 1 **这绝对是正确的方法去。否则解析器仍然会读取<！ - 我们不再需要这个：（DO（BAD THINGS）） - >' – Eric

+0

你真的想'BeautifulSoup（text，“xml”）'虽然 – Eric

+0

@Eric我试过，但它不会识别第二个解析标签。 –

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