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String functions are used in computer programming languages to manipulate a string or query information about a string (some do both).. Most programming languages that have a string datatype will have some string functions although there may be other low-level ways within each language to handle strings directly.
Blue highlights show the match results of the regular expression pattern: /r[aeiou]+/ g (lower case r followed by one or more lower-case vowels). A regular expression (shortened as regex or regexp ), [ 1 ] sometimes referred to as rational expression , [ 2 ] [ 3 ] is a sequence of characters that specifies a match pattern in text .
The x must be lowercase in XML documents. The nnnn or hhhh may be any number of digits and may include leading zeros. The hhhh may mix uppercase and lowercase, though uppercase is the usual style. In contrast, a character entity reference refers to a character by the name of an entity which has the desired character as its replacement text.
Snake case (sometimes stylized autologically as snake_case) is the naming convention in which each space is replaced with an underscore (_) character, and words are written in lowercase. It is a commonly used naming convention in computing , for example for variable and subroutine names, and for filenames .
In Python, if a name is intended to be "private", it is prefixed by one or two underscores. Private variables are enforced in Python only by convention. Names can also be suffixed with an underscore to prevent conflict with Python keywords. Prefixing with double underscores changes behaviour in classes with regard to name mangling.
Simplistic hash functions may add the first and last n characters of a string along with the length, or form a word-size hash from the middle 4 characters of a string. This saves iterating over the (potentially long) string, but hash functions that do not hash on all characters of a string can readily become linear due to redundancies ...
The most common superscript digits (1, 2, and 3) were included in ISO-8859-1 and were therefore carried over into those code points in the Latin-1 range of Unicode. The remainder were placed along with basic arithmetical symbols, and later some Latin subscripts, in a dedicated block at U+2070 to U+209F.
In information theory, linguistics, and computer science, the Levenshtein distance is a string metric for measuring the difference between two sequences. The Levenshtein distance between two words is the minimum number of single-character edits (insertions, deletions or substitutions) required to change one word into the other.