The expression we've used above works well for the majority of cases and will work well for any reasonable application. This method returns a match object only if the whole string matches the pattern, in any other case it returns None.ĭownload the eBook isValid( " ")Īwesome, we've got a functioning system! Robust Email Regular Expression The method that we will be using is re.fullmatch(pattern, string, flags). The re module contains classes and methods to represent and work with Regular Expressions in Python, so we'll import it into our script. Yet again, it can probably fail to properly validate some edge case that we haven't thought of. Obviously, this regex is more complicated than the first one, but it covers all of the rules we have defined for the email format. Accounting for those cases as well, we can put these rules down into a concrete expression that takes in a few more cases into account than the first representation: (+)* +(\.)+Ī special character in the prefix cannot be just before the symbol, nor can the prefix start with it, so we made sure that there is at least one alphanumeric character before and after every special character.Īs for the domain, an email can contain a few top-level domains divided with a dot. Additionally, the top-level domain can't be. It's worth noting that the strings shouldn't contain certain special characters, lest they break the form again. We need to define what kind of email address format are we looking for. Although, there are expressions that can match most valid email addresses. It's worth noting that there is no such regular expression that matches every possible valid email address. If you would like to learn more about Python's interface with Regular Expressions, read our Guide to Regular Expressions in Python! General-Purpose Email Regular Expression
In this article, we will take a look at how to validate email addresses in Python, using Regular Expressions. Regular Expressions are widely used for pattern-matching, and various programming languages have interfaces for representing them, as well as interacting with the matches results.
These patterns consist of characters, digits and special characters, in such a form that the pattern matches certain segments of text we're searching through. Regular Expressions, or RegEx for short, are expressions of patterns that can be used for text search and replace actions, validations, string splitting, and much more.