When I first learned about regular expressions, I didn’t really appreciate their power. But there’s a reason regular expressions have survived seven decades of technological disruption: coders who understand regular expressions have a massive advantage when working with textual data. They can write in a single line of code what takes others dozens!
This article is all about the findall() method of Python’s re library. The findall() method is the most basic way of using regular expressions in Python: If you want to master them, start here!
Related article: Python Regex Superpower – The Ultimate Guide
Do you want to master the regex superpower? Check out my new book The Smartest Way to Learn Regular Expressions in Python with the innovative 3-step approach for active learning: (1) study a book chapter, (2) solve a code puzzle, and (3) watch an educational chapter video.
So how does the re.findall() method work? Let’s study the specification.
How Does the findall() Method Work in Python?
The re.findall(pattern, string) method finds all occurrences of the pattern in the string and returns a list of all matching substrings.
re.findall(pattern, string, flags=0)
The re.findall() method has up to three arguments.
- pattern: the regular expression pattern that you want to match.
- string: the string which you want to search for the pattern.
- flags (optional argument): a more advanced modifier that allows you to customize the behavior of the function. Want to know how to use those flags? Check out this detailed article on the Finxter blog.
We will have a look at each of them in more detail.
The re.findall() method returns a list of strings. Each string element is a matching substring of the string argument.
Let’s check out a few examples!
First, you import the re module and create the text string to be searched for the regex patterns:
import re text = ''' Ha! let me see her: out, alas! he's cold: Her blood is settled, and her joints are stiff; Life and these lips have long been separated: Death lies on her like an untimely frost Upon the sweetest flower of all the field. '''
Let’s say, you want to search the text for the string ‘her’:
>>> re.findall('her', text) ['her', 'her', 'her']
The first argument is the pattern you look for. In our case, it’s the string ‘her’. The second argument is the text to be analyzed. You stored the multi-line string in the variable text—so you take this as the second argument. You don’t need to define the optional third argument flags of the findall() method because you’re fine with the default behavior in this case.
Also note that the findall() function returns a list of all matching substrings. In this case, this may not be too useful because we only searched for an exact string. But if we search for more complicated patterns, this may actually be very useful:
>>> re.findall('\\bf\w+\\b', text) ['frost', 'flower', 'field']
The regex ‘\\bf\w+\\b’ matches all words that start with the character ‘f’.
You may ask: why to enclose the regex with a leading and trailing ‘\\b’? This is the word boundary character that matches the empty string at the beginning or at the end of a word. You can define a word as a sequence of characters that are not whitespace characters or other delimiters such as ‘.:,?!’.
In the previous example, you need to escape the boundary character ‘\b’ again because in a Python string, the default meaning of the character sequence ‘\b’ is the backslash character.
Where to Go From Here?
This article has introduced the re.findall(pattern, string) method that attempts to match all occurrences of the regex pattern in a given string—and returns a list of all matches as strings.
Python is growing rapidly and the world is more and more divided into two classes: those who understand coding and those who don’t. The latter will have larger and larger difficulties participating in the era of massive adoption and penetration of digital content. Do you want to increase your Python skills on a daily basis without investing a lot of time?