How to get started with "Regular Expressions" in Python
Tags: python, webdev, programming
Published: 2023-03-14 02:38:10

Regular expressions (often abbreviated as "regex" or "re") are a powerful tool for working with text in Python. Whether you're parsing text files, searching for specific patterns, or validating user input, regular expressions can help you save time and reduce errors. In this blog post, we'll cover the basics of how to use re in Python.

What is a Regular Expression?

At its simplest, a regular expression is a pattern that matches a specific sequence of characters in a string. For example, the regular expression "cat" matches any string that contains the letters "c", "a", and "t" in that order. Regular expressions can be used to match more complex patterns as well, such as email addresses, phone numbers, or URLs.

Using re in Python

Python provides a built-in module called "re" for working with regular expressions. The re module provides a variety of functions for working with regular expressions, including:

re.search(): Searches a string for a match to a regular expression and returns the first match.
re.findall(): Searches a string for all matches to a regular expression and returns a list of all matches.
re.sub(): Searches a string for matches to a regular expression and replaces them with a specified string.
Let's take a look at each of these functions in more detail.

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**re.search()**

The re.search() function searches a string for a match to a regular expression and returns the first match. Here's an example:

![re.search()](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/hlaklglxm6ezbk5jp41d.png)

In this example, we import the re module and define a string called "text". We then use the re.search() function to search for the regular expression "fox" in the text string. The function returns a match object if a match is found, which we can then check for using an if statement.

Note that the regular expression is defined using the "r" prefix, which tells Python to treat the string as a raw string literal. This is important because regular expressions often contain special characters that have special meanings in Python, such as backslashes and quotation marks.

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**re.findall()**

The re.findall() function searches a string for all matches to a regular expression and returns a list of all matches. Here's an example:
![re.findall()](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/f0iuha97aaeq39slq0ow.png)

Here we use the re.findall() function to search for all words in the text string. The regular expression "\w+" matches any sequence of one or more word characters, which includes letters, digits, and underscores. The function returns a list of all matches, which we then print to the console.

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**re.sub()**

The re.sub() function searches a string for matches to a regular expression and replaces them with a specified string. Here's an example:

![re.sub()](https://dev-to-uploads.s3.amazonaws.com/uploads/articles/p0hg13b73xx1z4eyj6ho.png)

Similar to the re.findall() example, we use the re.sub() function to replace all occurrences of "fox" in the text string with "cat". The function returns a new string with the replacements made, which we then print to the console.

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Regular Expression Syntax

Regular expressions can be quite complex, and there are many resources available online for learning more about regular expression syntax. However, here are a few basic patterns that you might find useful:

. : Matches any single character except newline.
\d : Matches any digit character (equivalent to [0-9]).
\w : Matches any word character (equivalent to [a-zA-Z0-9_]).
\s : Matches any whitespace character (equivalent to [\t\n\r\f\v]).
 : Matches any character inside the brackets. For example, [abc] matches "a", "b", or "c".
[^ ] : Matches any character not inside the brackets. For example, [^abc] matches any character that is not "a", "b", or "c".
: Matches zero or more occurrences of the preceding character or group.
: Matches one or more occurrences of the preceding character or group.
? : Matches zero or one occurrences of the preceding character or group.
{m} : Matches exactly m occurrences of the preceding character or group.
{m,n} : Matches between m and n occurrences of the preceding character or group.
and These are just a few of the many regular expression syntax patterns available. Although this seems like a lot, there's so many more helpful places you can implement *re* in your code, so [check out pythons documentation to get the full rundown.](https://docs.python.org/3/howto/regex.html)