Postgres regex5/8/2023 ![]() ![]() For starters, I will discuss POSIX-style regular expressions and see some basic uses. This post is first in the series of blogs I plan to write on the RE topic with respect to PostgreSQL. ![]() POSIX regular expressions provide a more powerful means for pattern matching than the LIKE and SIMILAR TO operators. There are some more advanced techniques for advanced pattern matching requirements but those will very likely involve writing some user defined functions using Perl or Tcl. POSIX-style regular expressions (BREs and EREs).PostgreSQL’s regular expressions supports three separate approaches to pattern matching: PostgreSQL 9 Cookbook – Chinese EditionĪ regular expression is a special text string used to describe a search pattern.PostgreSQL Server Programming Cookbook – 2nd Edition.PostgreSQL 9 Administration Cookbook – 3rd Edition.PostgreSQL High Availability Cookbook – 2nd Edition.There are others, but those are the most commonly used. ] any alphanumeric, ] any white space character. This is the NOT operator in regular expressions so for example will match any character that is not in the alphabet. They define a specific sequence of characters. A subexpression can be composed of multiple classes etc and can be backreferenced. ![]() (123) 456-7890 or 456-7890 or 123.456.7890 UPDATE notes SET description = regexp_replace (description,Į ' means you can have between 1 and 5 alpha characters in and expression for it to be a match. remove phone numbers if description - has phone numbers e.g. remove website urls if description has website urls - matches things like or UPDATE notes SET description = regexp_replace (description, remove email addresses if description has email address UPDATE notes SET description = regexp_replace (description, Every database programmer should be versed in the art of information destruction. The power of databases is not only do they allow you to store/retrieve information quickly, but they allow you to destroy information just as quickly. The ~ operator is like the LIKE statement, but for regular expressions. Occurrence is replaced or returned in the regexp_replace, regexp_matches constructs. If you leave the flag out, only the first The g flag is the greedy flag that returns, replaces all occurrences of the pattern. We use the PostgreSQL g flag in our use more often than not. The ones we commonly use are ~, regexp_replace, and regexp_matches. PostgreSQL has a rich set of functions and operators for working with regular expressions. INSERT INTO notes (description ) VALUES ( ' I like ` # marks and other stuff that annoys Militant if you have issues, give someone who gives a damn a call at (999) 666-6666. She also manages the site and can be reached at 345.678.9999 She can be reached at (123) 456-7890 and her email address is or ' ) INSERT INTO notes (description ) VALUES ( ' John ' ' s email address is Priscilla manages the site. We'll just focus on their use in PostgreSQL, though these lessonsĬREATE TABLE notes (note_id serial primary key, description text ) The problem with regular expressions is that they are slightly different depending on what language environment you are Makes that much easier than any other DBMS we can think of.įor more details on using regular expressions in PostgreSQL, check out the manual pages Pattern Matching in PostgreSQL Embrace the power of domain languages and mix it up. When you mix the two domain languages, you can do enchanting things with a flip of a wrist that You can use them in SQL statements, domain definitions and check constraints. You have them in PostgreSQL as well where In ASP.NET validators and javascript for checking correctness of input. You see it in sed, grep, perl, PHP, Python, VB.NET, C#, Just like SQL they are embedded in many places. Regular expressions are a domain language just like SQL. Why write 20 lines of code when you can write 1. There are many places where regular expressions can be used to reduce a 20 line piece of code into aġ liner. Every programmer should embrace and use regular expressions (INCLUDING Database programmers). ![]()
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