Python Regex Syntax [2-Minute Primer]

A regular expression is a decades-old concept in computer science. Invented in the 1950s by famous mathematician Stephen Cole Kleene, the decades of evolution brought a huge variety of operations. Collecting all operations and writing up a comprehensive list would result in a very thick and unreadable book by itself.

Related article: Python Regex Superpower – The Ultimate Guide

Fortunately, you don’t have to learn all regular expressions before you can start using them in your practical code projects. Next, you’ll get a quick and dirty overview of the most important regex operations and how to use them in Python. In follow-up chapters, you’ll then study them in detail — with many practical applications and code puzzles.

Here are the most important regex operators:

  • . The wild-card operator (‘dot’) matches any character in a string except the newline character ‘\n’. For example, the regex ‘…’ matches all words with three characters such as ‘abc’, ‘cat’, and ‘dog’.  
  • * The zero-or-more asterisk operator matches an arbitrary number of occurrences (including zero occurrences) of the immediately preceding regex. For example, the regex ‘cat*’ matches the strings ‘ca’, ‘cat’, ‘catt’, ‘cattt’, and ‘catttttttt’. 
  • ? The zero-or-one operator matches (as the name suggests) either zero or one occurrences of the immediately preceding regex. For example, the regex ‘cat?’ matches both strings ‘ca’ and ‘cat’ — but not ‘catt’, ‘cattt’, and ‘catttttttt’. 
  • + The at-least-one operator matches one or more occurrences of the immediately preceding regex. For example, the regex ‘cat+’ does not match the string ‘ca’ but matches all strings with at least one trailing character ‘t’ such as ‘cat’, ‘catt’, and ‘cattt’. 
  • ^ The start-of-string operator matches the beginning of a string. For example, the regex ‘^p’ would match the strings ‘python’ and ‘programming’ but not ‘lisp’ and ‘spying’ where the character ‘p’ does not occur at the start of the string.
  • $ The end-of-string operator matches the end of a string. For example, the regex ‘py$’ would match the strings ‘main.py’ and ‘pypy’ but not the strings ‘python’ and ‘pypi’. 
  • A|B The OR operator matches either the regex A or the regex B. Note that the intuition is quite different from the standard interpretation of the or operator that can also satisfy both conditions. For example, the regex ‘(hello)|(hi)’ matches strings ‘hello world’ and ‘hi python’. It wouldn’t make sense to try to match both of them at the same time.
  • AB  The AND operator matches first the regex A and second the regex B, in this sequence. We’ve already seen it trivially in the regex ‘ca’ that matches first regex ‘c’ and second regex ‘a’. 

Note that I gave the above operators some more meaningful names (in bold) so that you can immediately grasp the purpose of each regex. For example, the ‘^’ operator is usually denoted as the ‘caret’ operator. Those names are not descriptive so I came up with more kindergarten-like words such as the “start-of-string” operator.

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.

Let’s dive into some examples!

Examples

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.
'''

print(re.findall('.a!', text))
'''
Finds all occurrences of an arbitrary character that is
followed by the character sequence 'a!'.
['Ha!']
'''

print(re.findall('is.*and', text))
'''
Finds all occurrences of the word 'is',
followed by an arbitrary number of characters
and the word 'and'.
['is settled, and']
'''

print(re.findall('her:?', text))
'''
Finds all occurrences of the word 'her',
followed by zero or one occurrences of the colon ':'.
['her:', 'her', 'her']
'''

print(re.findall('her:+', text))
'''
Finds all occurrences of the word 'her',
followed by one or more occurrences of the colon ':'.
['her:']
'''


print(re.findall('^Ha.*', text))
'''
Finds all occurrences where the string starts with
the character sequence 'Ha', followed by an arbitrary
number of characters except for the new-line character. 
Can you figure out why Python doesn't find any?
[]
'''

print(re.findall('\n$', text))
'''
Finds all occurrences where the new-line character '\n'
occurs at the end of the string.
['\n']
'''

print(re.findall('(Life|Death)', text))
'''
Finds all occurrences of either the word 'Life' or the
word 'Death'.
['Life', 'Death']
'''

In these examples, you’ve already seen the special symbol \n which denotes the new-line character in Python (and most other languages). There are many special characters, specifically designed for regular expressions.

Where to Go From Here?

If you want to master regular expressions once and for all, I’d recommend that you read the massive regular expression tutorial on the Finxter blog — for free!

https://blog.finxter.com/python-regex/