Regular expressions are used in string processing, form validation, and other occasions, which are practical and efficient. Here are some commonly used expressions for emergencies.
Note: The following content comes from the Internet, and may not be applicable due to different regular expression libraries
Regular expression that matches HTML markup: <(\S*?)[^>]*>.*?</\1>| <.*? />
Comment: The version circulating on the Internet is too bad, and the above one can only match the part, and there is still nothing that can be done about complex nested markup
Regular expression that matches the first and last spaced characters: ^\s*|\s*$
Comment: A very useful expression that can be used to remove whitespace at the beginning and end of a line (including spaces, tabs, page breaks, etc.).
Regular expression to match the email address: \w+([-+.] \w+)*@\w+([-.] \w+)*\.\w+([-.] \w+)*
Comment: Useful for form validation
Regular expression for matching URL URL: [a-zA-z]+://[^\s]*
Comment: The version circulating on the Internet has very limited functions, and the above one can basically meet the needs
Matching account legitimacy (letter begins, 5-16 bytes allowed, alphanumeric underscores allowed): ^[a-zA-Z][a-zA-Z0-9_]{4,15}$
Comment: Useful for form validation
Match domestic phone numbers: \d{3}-\d{8}|\d{4}-\d{7}
Comments: Matching forms such as 0511-4405222 or 021-87888822
Match Tencent QQ number: [1-9][0-9]{4,}
Comment: Tencent QQ number starts from 10,000
Match the Chinese postal code: [1-9]\d{5}(?! \d)
Comment: China's postal code is 6 digits
Matching ID:\d{15}|\d{18}
Commentary: Chinese ID cards are 15 or 18 digits
Matching IP address: \d+\.\d+\.\d+\.\d+
Comment: Useful when extracting IP addresses
Match specific numbers:
^[1-9]\d*$ // Matches positive integers
^-[1-9]\d*$ // Matches negative integers
^-? [1-9]\d*$ // matches integers
^[1-9]\d*|0$ // Matching non-negative integers (positive integers + 0)
^-[1-9]\d*|0$ //Matching non-positive integers (negative integers + 0)
^[1-9]\d*\.\d*|0\.\d*[1-9]\d*$ // matches positive floating-point numbers
^-([1-9]\d*\.\d*|0\.\d*[1-9]\d*)$ //Matches the negative floating point number
^-? ([1-9]\d*\.\d*|0\.\d*[1-9]\d*|0?\.0+|0)$ // matches the floating-point number
^[1-9]\d*\.\d*|0\.\d*[1-9]\d*|0?\.0+|0$ //Matching non-negative floating-point numbers (positive floating-point numbers + 0)
^(-([1-9]\d*\.\d*|0\.\d*[1-9]\d*))|0?\.0+|0$ //Match non-positive floating-point number(negative floating-point number + 0)
Comment: Useful when dealing with large amounts of data, pay attention to correction when applying specific applications
Matching a specific string:
^[A-Za-z]+$ // matches a string consisting of 26 letters
^[A-Z]+$ // matches a string consisting of 26 uppercase letters
^[a-z]+$ // matches a string consisting of lowercase letters of 26 English letters
^[A-Za-z0-9]+$ // matches a string consisting of numbers and 26 letters
^\w+$ // Matches strings consisting of numbers, 26 letters, or underscores
Commentary: Some of the most basic and most commonly used expressions
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Posted on 2/5/2015 9:41:50 AM
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