More challenging it would be if you must understand (and debug) RegEx by someone else! Tools for development, testing and debuggingĪlthough RegEx is powerful but it can get complicated for non-trivial tasks. It can be replaced with a “” hyper link to actual judgment it refers to. The pattern is : text “U.S.C.”, another space, a § mark, another space, a set of numbers, and optionally, a year inside a parenthetical. It is possible to append the hyperlink information by replacing the citation text.įor example, US legal judgments citation looks like “17 U.S.C. Finding email “^ within emailįinding telephone number “(”Ĭitations in search papers or judgments have pre-defined formats and they refer to an external document. In most of the examples, expressive and simplistic patterns are used here just for clarity and understandability. Please note that the examples shown could have alternate ways of getting same results, especially by using meta characters such as “/d” for “” representing digits. But with RegEx, it’s just about 2/3 of lines of code, and with high customizability.įollowing are some of the frequently occurring scenarios where RegEx can offer substantial help.
#Python text extractor separate phone from fax code
With validations, the code will typically be surely more than 10 lines (sample here ). Imagine writing code for searching telephone numbers like +91-9890251406 in a document, with multiple variations in format. More information about RegEx usage in Python can be found at Regex One and in this AV article. For performance reasons, it is recommended to compile the pattern first using “re.compile” and then use the RegEx object for searching, as shown below. “re.sub” is used to substitute another pattern as a replacement for the given search pattern. Instead of “re.search”, which returns all the exact matches, “re.findall()” can be used to return all captured groups.
Go through the following Python sample code for usage of RegEx. Go through the following table of basic syntax. Instead of regular strings, search patterns are specified using raw strings “r”, so that backslashes and meta characters are not interpreted by python but sent to RegEx directly. Python supports regular expressions by the library called “re”(though it’s not fully Perl-compatible). ‘ Regular expression (RegEx)’ is one of the ‘rules’ based pattern search method. Whereas in ‘statistical’ approach supervised-unsupervised methods are used to extract the information. In ‘rules’ based approach, pattern searches are made to find key information. In ‘lookup’ based approaches, words from input documents are searched against pre-defined data dictionary. Such entity extraction uses approaches like ‘lookup’, ‘rules’ and ‘statistical/machine learning’. These extractions are part of Text Mining and are essential in converting unstructured data to a structured form which are later used for applying analytics/machine learning. For example names of companies – prices from financial reports, names of judges – jurisdiction from court judgments, account numbers from customer complaints, etc.
Many times it is necessary to extract key information from reports, articles, papers, etc.
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