A Regular Expression (RegEx) is a sequence of characters that defines a search pattern. For example,

^a...s$

The above code defines a RegEx pattern. The pattern is: any five letter string starting with a and ending with s.

A pattern defined using RegEx can be used to match against a string.

Python has a module named re to work with RegEx. Here’s an example:

import re

pattern = '^a...s$'
test_string = 'abyss'
result = re.match(pattern, test_string)

if result:
  print("Search successful.")
else:
  print("Search unsuccessful.")	

Here, we used re.match() function to search pattern within the test_string. The method returns a match object if the search is successful. If not, it returns None.

There are other several functions defined in the re module to work with RegEx. Before we explore that, let’s learn about regular expressions themselves.

If you already know the basics of RegEx, jump to Python RegEx.

Specify Pattern Using RegEx

To specify regular expressions, metacharacters are used. In the above example, ^ and $ are meta characters.

MetaCharacters

Metacharacters are characters that are interpreted in a special way by a RegEx engine. Here’s a list of meta characters:

[] . ^ $ * + ? {} ()  |

[] – Square brackets

Square brackets specifies a set of characters you wish to match.

Here, [abc] will match if the string you are trying to match contains any of the a, b or c.

You can also specify a range of characters using - inside square brackets.

• [a-e] is the same as [abcde].
• [1-4] is the same as [1234].
• [0-39] is the same as [01239].

You can complement (invert) the character set by using caret ^ symbol at the start of a square-bracket.

• [^abc] means any character except a or b or c.
• [^0-9] means any non-digit character.

. – Period

A period matches any single character (except newline 'n').

^ – Caret

The caret symbol ^ is used to check if a string starts with a certain character.

$ – Dollar

The dollar symbol $ is used to check if a string ends with a certain character.

* – Star

The star symbol * matches zero or more occurrences of the pattern left to it.

+ – Plus

The plus symbol + matches one or more occurrences of the pattern left to it.

? – Question Mark

The question mark symbol ? matches zero or one occurrence of the pattern left to it.

{} – Braces

Consider this code: {n,m}. This means at least n, and at most m repetitions of the pattern left to it.

Let’s try one more example. This RegEx [0-9]{2, 4} matches at least 2 digits but not more than 4 digits

| – Alternation

Vertical bar | is used for alternation (or operator).

Here, a|b match any string that contains either a or b

() – Group

Parentheses () is used to group sub-patterns. For example, (a|b|c)xz match any string that matches either a or b or c followed by xz

– Backslash

Backlash  is used to escape various characters including all metacharacters. For example,

$a match if a string contains $ followed by a. Here, $ is not interpreted by a RegEx engine in a special way.

If you are unsure if a character has special meaning or not, you can put  in front of it. This makes sure the character is not treated in a special way.

Special Sequences

Special sequences make commonly used patterns easier to write. Here’s a list of special sequences:

A – Matches if the specified characters are at the start of a string.

b – Matches if the specified characters are at the beginning or end of a word.

B – Opposite of b. Matches if the specified characters are not at the beginning or end of a word.

d – Matches any decimal digit. Equivalent to [0-9]

D – Matches any non-decimal digit. Equivalent to [^0-9]

s – Matches where a string contains any whitespace character. Equivalent to [ tnrfv].

S – Matches where a string contains any non-whitespace character. Equivalent to [^ tnrfv].

w – Matches any alphanumeric character (digits and alphabets). Equivalent to [a-zA-Z0-9_]. By the way, underscore _ is also considered an alphanumeric character.

W – Matches any non-alphanumeric character. Equivalent to [^a-zA-Z0-9_]

Z – Matches if the specified characters are at the end of a string.

Tip: To build and test regular expressions, you can use RegEx tester tools such as regex101. This tool not only helps you in creating regular expressions, but it also helps you learn it.

Now you understand the basics of RegEx, let’s discuss how to use RegEx in your Python code.

Python RegEx

Python has a module named re to work with regular expressions. To use it, we need to import the module.

import re

The module defines several functions and constants to work with RegEx.

re.findall()

The re.findall() method returns a list of strings containing all matches.

Example 1: re.findall()

# Program to extract numbers from a string

import re

string = 'hello 12 hi 89. Howdy 34'
pattern = 'd+'

result = re.findall(pattern, string) 
print(result)

# Output: ['12', '89', '34']

If the pattern is not found, re.findall() returns an empty list.

re.split()

The re.split method splits the string where there is a match and returns a list of strings where the splits have occurred.

Example 2: re.split()

import re

string = 'Twelve:12 Eighty nine:89.'
pattern = 'd+'

result = re.split(pattern, string) 
print(result)

# Output: ['Twelve:', ' Eighty nine:', '.']

If the pattern is not found, re.split() returns a list containing the original string.

You can pass maxsplit argument to the re.split() method. It’s the maximum number of splits that will occur.

import re

string = 'Twelve:12 Eighty nine:89 Nine:9.'
pattern = 'd+'

# maxsplit = 1
# split only at the first occurrence
result = re.split(pattern, string, 1) 
print(result)

# Output: ['Twelve:', ' Eighty nine:89 Nine:9.']

By the way, the default value of maxsplit is 0; meaning all possible splits.

re.sub()

The syntax of re.sub() is:

re.sub(pattern, replace, string)

The method returns a string where matched occurrences are replaced with the content of replace variable.

Example 3: re.sub()

# Program to remove all whitespaces
import re

# multiline string
string = 'abc 12
de 23 n f45 6'

# matches all whitespace characters
pattern = 's+'

# empty string
replace = ''

new_string = re.sub(pattern, replace, string) 
print(new_string)

# Output: abc12de23f456

If the pattern is not found, re.sub() returns the original string.

You can pass count as a fourth parameter to the re.sub() method. If omited, it results to 0. This will replace all occurrences.

import re

# multiline string
string = 'abc 12
de 23 n f45 6'

# matches all whitespace characters
pattern = 's+'
replace = ''

new_string = re.sub(r's+', replace, string, 1) 
print(new_string)

# Output:
# abc12de 23
# f45 6

re.subn()

The re.subn() is similar to re.sub() expect it returns a tuple of 2 items containing the new string and the number of substitutions made.

Example 4: re.subn()

# Program to remove all whitespaces
import re

# multiline string
string = 'abc 12
de 23 n f45 6'

# matches all whitespace characters
pattern = 's+'

# empty string
replace = ''

new_string = re.subn(pattern, replace, string) 
print(new_string)

# Output: ('abc12de23f456', 4)

re.search()

The re.search() method takes two arguments: a pattern and a string. The method looks for the first location where the RegEx pattern produces a match with the string.

If the search is successful, re.search() returns a match object; if not, it returns None.

match = re.search(pattern, str)

Example 5: re.search()

import re

string = "Python is fun"

# check if 'Python' is at the beginning
match = re.search('APython', string)

if match:
  print("pattern found inside the string")
else:
  print("pattern not found")  

# Output: pattern found inside the string

Here, match contains a match object.

Match object

You can get methods and attributes of a match object using dir() function.

Some of the commonly used methods and attributes of match objects are:

match.group()

The group() method returns the part of the string where there is a match.

Example 6: Match object

import re

string = '39801 356, 2102 1111'

# Three digit number followed by space followed by two digit number
pattern = '(d{3}) (d{2})'

# match variable contains a Match object.
match = re.search(pattern, string) 

if match:
  print(match.group())
else:
  print("pattern not found")

# Output: 801 35

Here, match variable contains a match object.

Our pattern (d{3}) (d{2}) has two subgroups (d{3}) and (d{2}). You can get the part of the string of these parenthesized subgroups. Here’s how:

>>> match.group(1)
'801'

>>> match.group(2)
'35'
>>> match.group(1, 2)
('801', '35')

>>> match.groups()
('801', '35')

match.start(), match.end() and match.span()

The start() function returns the index of the start of the matched substring. Similarly, end() returns the end index of the matched substring.

>>> match.start()
2
>>> match.end()
8

The span() function returns a tuple containing start and end index of the matched part.

>>> match.span()
(2, 8)

match.re and match.string

The re attribute of a matched object returns a regular expression object. Similarly, string attribute returns the passed string.

>>> match.re
re.compile('(\d{3}) (\d{2})')

>>> match.string
'39801 356, 2102 1111'

We have covered all commonly used methods defined in the re module. If you want to learn more, visit Python 3 re module.

Using r prefix before RegEx

When r or R prefix is used before a regular expression, it means raw string. For example, 'n' is a new line whereas r'n' means two characters: a backslash  followed by n.

Backlash  is used to escape various characters including all metacharacters. However, using r prefix makes  treat as a normal character.

Example 7: Raw string using r prefix

import re

string = 'n and r are escape sequences.'

result = re.findall(r'[nr]', string) 
print(result)

# Output: ['n', 'r']