Recently done an internal system project, involving a large number of text validation, which used a number of commonly used regular expressions, collection is not easy, first recorded here, for later use.
Matching regular expressions for Chinese characters: [\U4E00-\U9FA5]
Match Double-byte characters (including Chinese characters): [^\x00-\xff] can be used to compute the length of a string (a double-byte character length meter 2,ascii 1)
Regular expression matching blank rows: \n\s*\r can be used to delete blank lines
Regular expression:< matching HTML tags (\s*?) [^>]*>.*?| < *? /> This can only match the part, there is still nothing for complex nested tags
A regular expression that matches the last and last whitespace character: ^\s*|\s*$ can be used to delete white space characters (including spaces, tabs, page breaks, and so on) at the end of a line, very useful expressions
Regular expression matching an email address: \w+ ([-+.] \w+) *@\w+ ([-.] \w+) *\.\w+ ([-.] \w+) * Form verification is practical
A regular expression that matches the URL of the URL: [a-za-z]+://[^\s]* this basic to meet the requirements
Match account number is legal (start of letter, allow 5-16 bytes, allow alphanumeric underline) ^[a-za-z][a-za-z0-9_]{4,15}$ form validation is useful
Match domestic phone number: \d{3}-\d{8}|\d{4}-\d{7} match form such as 0511-4405222 or 021-87888822
Matching Tencent QQ Number: [1-9][0-9]{4,} Tencent QQ number starting from 10000
Match China ZIP Code: [1-9]\d{5} (?! \d) China postal Code is 6 digits
Matching ID: \d{15}|\d{18} China's ID card is 15-digit or 18-digit number (excluding X)
^\d*\.? [0-9]\d*$//matching digits (including decimals)
^[1-9]\d*$//Matching positive integer
^-[1-9]\d*$//matching negative integers
^-? [1-9]\d*$//matching integer
^[1-9]\d*|0$//matching nonnegative integer (positive integer + 0)
^-[1-9]\d*|0$//matching non positive integer (negative integer + 0)
^[1-9]\d*\.\d*|0\.\d*[1-9]\d*$//matching positive floating-point numbers
^-([1-9]\d*\.\d*|0\.\d*[1-9]\d*) $//matching negative floating-point number
^-? ([1-9]\d*\.\d*|0\.\d*[1-9]\d*|0?\.0+|0) $//matching floating-point number
^[1-9]\d*\.\d*|0\.\d*[1-9]\d*|0?\.0+|0$//matching nonnegative floating-point number (positive floating-point number + 0)
^ (-([1-9]\d*\.\d*|0\.\d*[1-9]\d*)) |0?\.0+|0$//matching non-positive floating-point numbers (negative floating-point number + 0)
^[a-za-z]+$//Match a string of 26 English letters
^[a-z]+$//Match a string of 26 uppercase letters
^[a-z]+$//Match string consisting of 26 lowercase letters
^[a-za-z0-9]+$//Match a string of numbers and 26 English letters
^\w+$//Match A string of numbers, 26 English letters, or underscores
The following is actually a code fragment of an enumeration class, I am a bit lazy, do not do meticulous finishing:
The regular expression of/** scientific counting method * *
Regex_scien ("^" (\\d+. \\d+) [Ee]{1} (\\d+)) $ "," scientific notation Regular expression "),
/** Mobile phone number verification regular expression * *
Regex_mobile ("^1 (3|5|8) [0-9]{9}$", "mobile number validation Regular expression"),
/** amount Format Regular Expression * *
Regex_amount ("^[-]?[ \\d]{1,10} ([.] {1} [\\d] {1,2})? $ "," amount format Regular expression "),
/**-YYYYMM Regular Expression * *
Regex_month ("^" [1-9]\\d{3}) ([0][1-9]) | ( [1] [0-2])) $ "," yyyymm Regular expression "),
/** YYYYMMDD Date format Regular Expression * *
Regex_date (
"([0-9]{3}[1-9]| [0-9] {2} [1-9] [0-9] {1}| [0-9] {1} [1-9] [0-9] {2}| [1-9] [0-9] {3}) (((0[13578]|1[02]) (0[1-9]|[ 12][0-9]|3[01]) | ((0[469]|11) (0[1-9]|[ 12][0-9]|30)) | (02 (0[1-9]|[ 1][0-9]|2[0-8])) | (([0-9]{2}) (0[48]|[ 2468][048]| [13579] [26]) | ((0[48]| [2468] [048]| [3579] [26]) 00)) 0229) ",
"YYYYMMDD date format Regular expression"),
/** Email Verification Regular expression * *
Regex_email (
"^ ([_\\w-\\.] +) @ (\\[[0-9]{1,3}\\. [0-9] {1,3}\\. [0-9] {1,3}\\.) | (([_\\w-]+\\.) +)) ([a-za-z]{2,4}| [0-9] {1,3}) (\\]?)) $",
"Email verification of regular expression");