Regular expression (2)

re modular ( Built-in module )

  

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re The module is python Provides a set of modules for processing regular expressions . The core functions are the first four , Other functions are the last four :

1. findall lookup character string all Relevant Character set . return list

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lst = re.findall(r"m", "my mother, I love him!")
print(lst)

lst = re.findall(r"\d+", "6 Before the point . I kidnapped 12 Children at the age of , You're going to give it to me 5000 ten thousand ")
print(lst)

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['m', 'm', 'm']
['6', '12', '5000']

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2. finditer and findall almost . It's just that what comes back is iterator ,

Extremely efficient , In the days to come , Reptiles are also good , Data cleaning is also good , I hope to choose this first finditer

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iters = re.finditer("\d+", "6 Before the point . I kidnapped 12 Children at the age of , You're going to give it to me 5000 ten thousand ")
for it in iters:
    print(it.group()) #  You still need to group 

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6
12
5000

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3. search  On the string One match . But if it matches The first result . will Return this result . If it doesn't match search The one who returns is None.

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ret = re.search(r"\d+", "6 Before the point . I kidnapped 12 Children at the age of , You're going to give it to me 5000 ten thousand ")
print(ret)# Return the object class , You need to use the instance method to get the value 
print(ret.group())# use group Instance method can take out the attribute 

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<re.Match object; span=(0, 1), match='6'>
6

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4. match   Only from the start Conduct matching .（ Be similar to Regular expression metacharacters ^  Matches the beginning of the string ）

ret = re.match(r"\d+", "6 Before the point . I kidnapped 12 Children at the age of , You're going to give it to me 5000 ten thousand ")
print(ret)# Return the object class , You need to use the instance method to get the value 
print(ret.group())# use group Instance method can take out the attribute 

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<re.Match object; span=(0, 1), match='6'>
6

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5.split On the string cutting .( It's similar to cutting meat with a knife , Metacharacters are knives , Meat string )

ret = re.split('[a-l]', 'Andy has a apple,but she not have banana')# from a-l take 12 A different knife , Cut the meat , Put it into the list after cutting , Take the knife back 
print(ret)

['An', 'y ', '', 's ', ' ', 'pp', '', ',', 'ut s', '', ' not ', '', 'v', ' ', '', 'n', 'n', '']

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6.sub On the string Replace .( Similar to... In string processing replace, But he low,sub Than him high That's too much ！)

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ret=re.sub(r"\d+",'big_sb',' My name is 123, This year, 12 year , From 12 Middle school ')# You can change all the figures into big pancakes 
print(ret)

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 My name is big_sb, This year, big_sb year , From big_sb Middle school 

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7.subn  On the string Replace . And return tuples （ Replaced string , Number of replacements ）

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ret=re.subn(r"\d+",'big_sb',' My name is 123, This year, 12 year , From 12 Middle school ')
print(ret)

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(' My name is big_sb, This year, big_sb year , From big_sb Middle school ', 3)

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8.complie Preprocessing strings .( It is equivalent to setting some rule of regular expression on the string first , Then filter the string )

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obj = re.compile(r'\d+') #  Compile the regular expression into a   Regular expression objects ,  The rule is to match all the numbers 
ret = obj.finditer('ewq123e2ee2e') #  Regular expression object calls finditer,  The parameter is the string to be matched 
for i in  ret:
    print(ret.group())

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123
2
2

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    Regular expressions and re There are so many modules . If you want to explain all the contents of regular clearly , At least a week . For our daily use . The above knowledge points are enough . If you encounter some extreme situations, it is recommended to find ways to deal with them separately . First split the string . Then consider using regular .