Python regular expressions (RE) : email, ID, IP address, phone number, password, etc

Regular expressions (regular, regular, and RE) are the most common programming tricks in Python, and many times a good regular expression is worth dozens of lines of code. For example, match (verify) the mailbox, ID card, mobile phone number, IP address, URL, and HTML.

A regular expression is a special sequence of characters that contains predefined patterns (rules) that can be used to match and verify other strings (text, web pages, etc.).

The difficulty of mastering regular expressions, however, is that they contain a lot of basic pattern syntax to memorize, and these basic pattern syntax can be combined to produce infinite variations.

Therefore, it is not recommended to memorize the basic pattern of regular grammar, can be used as you look up, use more, will naturally form a mechanical memory.

Basic schema syntax

Character range matching

metacharacters

Multiple repeat matching

Locate matching

Regular matching process

import re

# regular expression for password strength
re_password = re.compile(r'^(? =.*\\d)(? =.*[a-z])(? =. * [a-z]). 8, 10 {} $')
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At the same time, when re.compiler(pattern[, flags]), you can select regular expression modifiers to control the matching pattern.

Details are shown in the following table:

matching

re.match(pattern, string, flags=0)

Matches from the start position of the string, or returns None if the start position does not match, which requires special attention.

Flags is the modifier of the regular expression.

import re

print(re.match(r'hello'.'Hello world', re.I))
print(re.match(r'world'.'Hello world', re.I))

<_sre.SRE_Match object at 0x7f2c7c626648>
None
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re.search(pattern, string, flags=0)

Unlike the match method, it scans the entire string and returns the first successful match.

import re

print(re.search(r'hello'.'Hello world', re.I))
print(re.search(r'world'.'Hello world', re.I))

<_sre.SRE_Match object at 0x7fbcf9945648>
<_sre.SRE_Match object at 0x7fbcf9945648>
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As you can see, the search method successfully found the world string.

If we want to output matching results, we can use groups and groups.

import re

print(re.search(r'world'.'Hello world', re.I).group(0))
print(re.search(r'(world)'.'Hello world', re.I).groups())

world
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One idea is that () applies to groups in regular expressions.

One more thing to note is that regular expression matches default to greedy matches.

import re

print(re.match(r'^(\d+)(0*)$'.'102300').groups())
print(re.match(r'^(\d+?) (0 *) $'.'102300').groups())

('102300'.' ')
('1023'.'00')
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\d+ = 0* = 0* = 0* = 0* = 0* = 0*

You must make \d+ use non-greedy matches (that is, as few matches as possible) in order to match the following zeros and add? Can be used by \d+.

Match and search can only match once, but if you want to match all, you can use findAll and finditer.

findall(string[, pos[, endpos]]

import re
 
# match number
pattern = re.compile(r'\d+')
result1 = pattern.findall('runoob 123 google 456')
result2 = pattern.findall('run88oob123google456'.0.10)
 
print(result1)
print(result2)

['123'.'456']
['88'.'12']
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finditer(pattern, string, flags=0)

import re

# match number
it = re.finditer(r"\d+"."12a32bc43jf3") 
for match in it: 
    print (match.group())

12 
32 
43 
3
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In addition to pure matching, there will be a need to split and replace, so here are two methods:

re.split(pattern, string[, maxsplit=0, flags=0])

import re
print(re.split('\W+'.'runoob, runoob, runoob.'))'runoob'.'runoob'.'runoob'.' ']
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re.sub(pattern, repl, string, count=0, flags=0)

import re

dt = '2020-01-01'
print(re.sub(r'\D'.' ', dt))

2020 01 01
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Common regular expressions

1. Verification password strength:

   ^ (? =.*\\d)(? =.*[a-z])(? =. * [a-z]). 8, 10 {} $

2. Calibration Chinese:

   ^[\\u4e00-\\u9fa5]{0,}$

3. A string of numbers, 26 letters, or underscores:

   ^\\w+$

4. Verification Email Address:

   [\\w!#$%&'*+/=?^_`{|}~-]+(? :\\.[\\w!#$%&'*+/=?^_`{|}~-]+)*@(? :[\\w](? :[\\w-]*[\\w])? \ \.) +[\\w](? :[\\w-]*[\\w])?

5. Check ID card number

   15:

   ^[1-9]\\d{7}((0\\d)|(1[0-2]))(([0|1|2]\\d)|3[0-1])\\d{3}$

   18:

   ^[1-9]\\d{5}[1-9]\\d{3}((0\\d)|(1[0-2]))(([0|1|2]\\d)|3[0-1])\\d{3}([0-9]|X)$

6. Verification Mobile phone Number:

   ^(13[0-9]|14[5|7]|15[0|1|2|3|5|6|7|8|9]|18[0|1|2|3|5|6|7|8|9])\\d{8}$

7. IP address:

   v4:

   \\b(? : (? : 25 [0 to 5] | 2 [0 to 4] [0-9] | [01]? [0-9] [0-9]?) \ \.) {3} (? : 25 [0 to 5] | 2 [0 to 4] [0-9] | [01]? [0-9] [0-9]?) \\b

   v6:

   (([0-9 a - fA - F] {1, 4} {7, 7}) [0-9 a - fA - F] {1, 4} | ([0-9 a - fA - F] {1, 4} {1, 7}) : | ([0-9 a - fA - F] {1, 4} {1, 6}) : [0-9 a - fA - F] {1, 4} | ([0-9 - fA - a F] {1, 4} {1, 5}) (: [0-9 a - fA - F] {1, 4}, {1, 2} | ([0-9] a - fA - F {1, 4} {1, 4}) (: [0-9 a - fA - F] {1, 4}, {1, 3} | ([0-9 a - fA - F] {1, 4} {1, 3}) (: [0-9 - a FA - F] {1, 4} {1, 4} | ([0-9 a - fA - F] {1, 4}} {1, 2) (: [0-9 a - fA - F] {1, 4}, {1, 5} | [0-9 a - fA - F] {1, 4} : ((: [0-9 a - fA - F] {1, 4}, {1, 6}) | : ((: [0-9 - a FA - F] {1, 4} {1, 7} | :) | fe80: : [0-9 a - fA - F] {0, 4}) {0, 4} % [0-9 a zA - Z] {1} | : : (FFFF (: 0 {1, 4}) {0, 1} {0, 1} ((25) [0 to 5) | (2 [0 to 4] | 1 {0, 1} [0 9]) {0, 1} [0-9]) \ \.) {3} (25 [0 to 5) | (2 [0 to 4] | 1 {0, 1} [0-9]) {0, 1} [0-9]) | ([0-9 a - fA - F] {1, 4} {1, 4}) : ((25 [0 to 5) | (2 [0 to 4] | 1 {0, 1} [0-9]) {0, 1} [0-9]) \ \.) {3} (25 [0 to 5) | (2 | 1 [0-4] [0-9] {0, 1}) [0-9] {0, 1}))

8. Extract page hyperlinks:

   (<a\\s*(? ! .*\\brel=)[^>]*)(href="https? : \ \ / \ \ / ((?) ! (? : (? :www\\.) ? '.implode('|(? :www\\.) ? ', $follow_list).'))[^"]+)"((? ! .*\\brel=)[^>]*)(? : [^ >] *) >

9. Calibration date:

   ^ (? : (? ! 0000) [0-9] {4} - (? : (? : 0 | [1-9] [0-2] 1) - (? : 0 [1-9] [0-9] | | 1 2 [0 to 8]) | (? : 0 [9] 13 - | [0-2] 1) - (? 30) : 29 | | (? : 0 [13578] 1 [02]) - 31) | | (? : [0-9] {2} (? : 0 [48] | [2468] [048] | [13579] [26]) | (? : 0 [48] | [2468] [048] | [13579] [26]) 00) - 02 - $29)

10. Check amount:

    ^ [0-9] + (. [0-9] {2})? $

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Finally, we have a book entitled “Understanding NLP Chinese Word Segmentation: From Principle to Practice”, which will help you master Chinese word segmentation from scratch and step into the door of NLP.

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