Python 正则表达式捕获组扩展
Python regex capturing group extension
我正在使用命名捕获组，使用 (?P<name>) 以及与冠状病毒大流行相关的动词和词干列表。
import regex
import pandas as pd
data = {'id':[1, 2, 3, 4, 5], 'text':['The pandemy is spreading', 'He is fighting Covid-19', 'The pandemic virus spreads', 'This sentence is about a different topic' , 'How do we stop the virus ?']}
df = pd.DataFrame(data)
def covid_lang(text):
predicates = ['avoid', 'contain', 'track', 'spread', 'contact', 'stop', 'combat', 'fight']
subjects = ['Corona', 'corona', 'Covid-19', 'epidem', 'infect', 'virus', 'pandem', 'disease', 'outbreak']
p1 = fr'(?<=\b(?P<predicate>{"|".join(predicates)}))[^\.]*(?P<subject>{"|".join(subjects)}[a-z]*)'
result = []
for m in regex.finditer(p1, text, regex.S):
result.append([m.group('predicate'), m.group('subject')])
p2 = fr'\b(?P<subject>{"|".join(subjects)})[^\.]*(?<=\b(?P<predicate>{"|".join(predicates)}))'
for m in regex.finditer(p2, text, regex.S):
result.append([m.group('subject'), m.group('predicate')])
return result
df['result'] = df['text'].apply(covid_lang)
当有匹配时，我想 return 作为主语，不仅是词干，而且是整个词（即 'pandemic' 和 'pandemy' 而不是'pandem')。我试过在单词列表之后添加 [a-z]* ，这样当单词结束时捕获组就会停止，但它不会改变任何东西。
另外，是否可以在单个查询中加入两个查询（谓词在主题之前，主题在谓词之前）？我试过使用 (p1)|(p2) 但它不适用于命名的捕获组。
最后，是否可以在一个单词中包含 Corona 和 corona 等大小写字母？
这三个都应该做到：
from xml.etree.ElementPath import prepare_descendant
import regex
import pandas as pd
data = {'id':[1, 2, 3, 4, 5], 'text':['The pandemy is spreading', 'He is fighting Covid-19', 'The pandemic virus spreads', 'This sentence is about a different topic' , 'How do we stop the virus ?']}
df = pd.DataFrame(data)
def expand_word(word):
return f'({word}[a-z]*)'
def construct_named_group_from_list_of_words(word_type, word_list):
expanded_word_regex_list = [expand_word(stem) for stem in word_list]
word_in_named_group = fr'(?P<{word_type}>{"|".join(expanded_word_regex_list)})'
return word_in_named_group
def covid_lang(text):
predicates = ['avoid', 'contain', 'track', 'spread', 'contact', 'stop', 'combat', 'fight']
subjects = ['corona', 'covid-19', 'epidem', 'infect', 'virus', 'pandem', 'disease', 'outbreak']
predicate_in_named_group = construct_named_group_from_list_of_words("predicate", predicates)
subject_in_named_group = construct_named_group_from_list_of_words("subject", subjects)
result = []
p1 = fr'(?<=\b{predicate_in_named_group})[^\.]*{subject_in_named_group}'
p2 = fr'\b{subject_in_named_group}[^\.]*(?<=\b{predicate_in_named_group})'
p = fr'({p1})|({p2})'
for m in regex.finditer(p, text, regex.S | regex.IGNORECASE):
result.append([m.group('predicate'), m.group('subject')])
return result
df['result'] = df['text'].apply(covid_lang)
print(df)
输出：
id text result
0 1 The pandemy is spreading [[spreading, pandemy]]
1 2 He is fighting Covid-19 [[fight, Covid-19]]
2 3 The pandemic virus spreads [[spreads, pandemic]]
3 4 This sentence is about a different topic []
4 5 How do we stop the virus ? [[stop, virus]]
但我不确定你是否总是想先输出谓词？如果没有，应该这样做：
from xml.etree.ElementPath import prepare_descendant
import regex
import pandas as pd
data = {'id':[1, 2, 3, 4, 5], 'text':['The pandemy is spreading', 'He is fighting Covid-19', 'The pandemic virus spreads', 'This sentence is about a different topic' , 'How do we stop the virus ?']}
df = pd.DataFrame(data)
def expand_word(word):
return f'({word}[a-z]*)'
def construct_named_group_from_list_of_words(word_type, word_list):
expanded_word_regex_list = [expand_word(stem) for stem in word_list]
word_in_named_group = fr'(?P<{word_type}>{"|".join(expanded_word_regex_list)})'
return word_in_named_group
def covid_lang(text):
predicates = ['avoid', 'contain', 'track', 'spread', 'contact', 'stop', 'combat', 'fight']
subjects = ['corona', 'covid-19', 'epidem', 'infect', 'virus', 'pandem', 'disease', 'outbreak']
predicate_in_named_group = construct_named_group_from_list_of_words("predicate", predicates)
subject_in_named_group = construct_named_group_from_list_of_words("subject", subjects)
result = []
p1 = fr'(?<=\b{predicate_in_named_group})[^\.]*{subject_in_named_group}'
p2 = fr'\b{subject_in_named_group}[^\.]*(?<=\b{predicate_in_named_group})'
for m in regex.finditer(p1, text, regex.S | regex.IGNORECASE):
result.append([m.group('predicate'), m.group('subject')])
for m in regex.finditer(p2, text, regex.S | regex.IGNORECASE):
result.append([m.group('subject'), m.group('predicate')])
return result
df['result'] = df['text'].apply(covid_lang)
print(df)
输出：
id text result
0 1 The pandemy is spreading [[pandemy, spreading]]
1 2 He is fighting Covid-19 [[fight, Covid-19]]
2 3 The pandemic virus spreads [[pandemic, spreads]]
3 4 This sentence is about a different topic []
4 5 How do we stop the virus ? [[stop, virus]]
我正在使用命名捕获组，使用 (?P<name>) 以及与冠状病毒大流行相关的动词和词干列表。
import regex
import pandas as pd
data = {'id':[1, 2, 3, 4, 5], 'text':['The pandemy is spreading', 'He is fighting Covid-19', 'The pandemic virus spreads', 'This sentence is about a different topic' , 'How do we stop the virus ?']}
df = pd.DataFrame(data)
def covid_lang(text):
predicates = ['avoid', 'contain', 'track', 'spread', 'contact', 'stop', 'combat', 'fight']
subjects = ['Corona', 'corona', 'Covid-19', 'epidem', 'infect', 'virus', 'pandem', 'disease', 'outbreak']
p1 = fr'(?<=\b(?P<predicate>{"|".join(predicates)}))[^\.]*(?P<subject>{"|".join(subjects)}[a-z]*)'
result = []
for m in regex.finditer(p1, text, regex.S):
result.append([m.group('predicate'), m.group('subject')])
p2 = fr'\b(?P<subject>{"|".join(subjects)})[^\.]*(?<=\b(?P<predicate>{"|".join(predicates)}))'
for m in regex.finditer(p2, text, regex.S):
result.append([m.group('subject'), m.group('predicate')])
return result
df['result'] = df['text'].apply(covid_lang)
当有匹配时，我想 return 作为主语，不仅是词干，而且是整个词（即 'pandemic' 和 'pandemy' 而不是'pandem')。我试过在单词列表之后添加 [a-z]* ，这样当单词结束时捕获组就会停止，但它不会改变任何东西。
另外，是否可以在单个查询中加入两个查询（谓词在主题之前，主题在谓词之前）？我试过使用 (p1)|(p2) 但它不适用于命名的捕获组。
最后，是否可以在一个单词中包含 Corona 和 corona 等大小写字母？
这三个都应该做到：
from xml.etree.ElementPath import prepare_descendant
import regex
import pandas as pd
data = {'id':[1, 2, 3, 4, 5], 'text':['The pandemy is spreading', 'He is fighting Covid-19', 'The pandemic virus spreads', 'This sentence is about a different topic' , 'How do we stop the virus ?']}
df = pd.DataFrame(data)
def expand_word(word):
return f'({word}[a-z]*)'
def construct_named_group_from_list_of_words(word_type, word_list):
expanded_word_regex_list = [expand_word(stem) for stem in word_list]
word_in_named_group = fr'(?P<{word_type}>{"|".join(expanded_word_regex_list)})'
return word_in_named_group
def covid_lang(text):
predicates = ['avoid', 'contain', 'track', 'spread', 'contact', 'stop', 'combat', 'fight']
subjects = ['corona', 'covid-19', 'epidem', 'infect', 'virus', 'pandem', 'disease', 'outbreak']
predicate_in_named_group = construct_named_group_from_list_of_words("predicate", predicates)
subject_in_named_group = construct_named_group_from_list_of_words("subject", subjects)
result = []
p1 = fr'(?<=\b{predicate_in_named_group})[^\.]*{subject_in_named_group}'
p2 = fr'\b{subject_in_named_group}[^\.]*(?<=\b{predicate_in_named_group})'
p = fr'({p1})|({p2})'
for m in regex.finditer(p, text, regex.S | regex.IGNORECASE):
result.append([m.group('predicate'), m.group('subject')])
return result
df['result'] = df['text'].apply(covid_lang)
print(df)
输出：
id text result
0 1 The pandemy is spreading [[spreading, pandemy]]
1 2 He is fighting Covid-19 [[fight, Covid-19]]
2 3 The pandemic virus spreads [[spreads, pandemic]]
3 4 This sentence is about a different topic []
4 5 How do we stop the virus ? [[stop, virus]]
但我不确定你是否总是想先输出谓词？如果没有，应该这样做：
from xml.etree.ElementPath import prepare_descendant
import regex
import pandas as pd
data = {'id':[1, 2, 3, 4, 5], 'text':['The pandemy is spreading', 'He is fighting Covid-19', 'The pandemic virus spreads', 'This sentence is about a different topic' , 'How do we stop the virus ?']}
df = pd.DataFrame(data)
def expand_word(word):
return f'({word}[a-z]*)'
def construct_named_group_from_list_of_words(word_type, word_list):
expanded_word_regex_list = [expand_word(stem) for stem in word_list]
word_in_named_group = fr'(?P<{word_type}>{"|".join(expanded_word_regex_list)})'
return word_in_named_group
def covid_lang(text):
predicates = ['avoid', 'contain', 'track', 'spread', 'contact', 'stop', 'combat', 'fight']
subjects = ['corona', 'covid-19', 'epidem', 'infect', 'virus', 'pandem', 'disease', 'outbreak']
predicate_in_named_group = construct_named_group_from_list_of_words("predicate", predicates)
subject_in_named_group = construct_named_group_from_list_of_words("subject", subjects)
result = []
p1 = fr'(?<=\b{predicate_in_named_group})[^\.]*{subject_in_named_group}'
p2 = fr'\b{subject_in_named_group}[^\.]*(?<=\b{predicate_in_named_group})'
for m in regex.finditer(p1, text, regex.S | regex.IGNORECASE):
result.append([m.group('predicate'), m.group('subject')])
for m in regex.finditer(p2, text, regex.S | regex.IGNORECASE):
result.append([m.group('subject'), m.group('predicate')])
return result
df['result'] = df['text'].apply(covid_lang)
print(df)
输出：
id text result
0 1 The pandemy is spreading [[pandemy, spreading]]
1 2 He is fighting Covid-19 [[fight, Covid-19]]
2 3 The pandemic virus spreads [[pandemic, spreads]]
3 4 This sentence is about a different topic []
4 5 How do we stop the virus ? [[stop, virus]]