Extract Regex

Data mining and parser for regular expressions. Extract Regex allows extraction of terms from text based on a regular expression. You can create your own Regex expression, use the built in expressions (emails, uri, url, US Address, US Postal code, credit card, phone numbers, dates, and many others) or get regex expressions from many sites. In computing, a regular expression provides a concise and flexible means for "matching" (specifying and recognizing) strings of text, such as particular characters, words, or patterns of characters. Abbreviations for "regular expression" include "regex" and "regexp". A regular expression is written in a formal language that can be interpreted by a regular expression processor, which is a program that either serves as a parser generator or examines text and identifies parts that match the provided specification. Historically, the concept of regular expressions is associated with Kleene's formalism of regular sets, introduced in the 1950s.

Here are examples of specifications that could be expressed in a regular expression:

the sequence of characters "car" appearing consecutively in any context, such as in "car", "cartoon", or "bicarbonate" the sequence of characters "car" occurring in that order with other characters between them, such as in "Icelander" or "chandler" the word "car" when it appears as an isolated word the word "car" when preceded by the word "blue" or "red" the word "car" when not preceded by the word "motor" a dollar sign immediately followed by one or more digits, and then optionally a period and exactly two more digits (for example, "$100" or "$245.99").

These examples are simple. Specifications of great complexity can be conveyed by regular expressions.

Regular expressions are used by many languages, including Perl, Ruby, AWK, and Tcl, integrate regular expressions into the syntax of the core language itself. Other programming languages like .NET languages, Java, and Python instead pr