Regular expressions, or "regex" for short, are a powerful tool for working with strings and text data in Python. They allow you to match and manipulate strings based on patterns, making it easy to perform complex string operations with just a few lines of code.
[] Represent a character class
^ Matches the beginning
$ Matches the end
. Matches any character except newline
? Matches zero or one occurrence.
| Means OR (Matches with any of the characters
separated by it.
* Any number of occurrences (including 0 occurrences)
+ One or more occurrences
{} Indicate number of occurrences of a preceding RE
to match.
() Enclose a group of REs
Find list of more meta characters here - https://www.ibm.com/docs/en/rational-clearquest/9.0.1?topic=tags-meta-characters-in-regular-expressions
In Python, regular expressions are supported by the re module. The basic syntax for working with regular expressions in Python is as follows:
import re
re.search() method either returns None (if the pattern doesn’t match), or a re.MatchObject that contains information about the matching part of the string. This method stops after the first match, so this is best suited for testing a regular expression more than extracting data.
We can use re.search method like this to search for a pattern in regular expression:
# Define a regular expression pattern
pattern = r"expression"
# Match the pattern against a string
text = "Hello, world!"
match = re.search(pattern, text)
if match:
print("Match found!")
else:
print("Match not found.")
You can also use the re.findall function to find all occurrences of the pattern in a string:
import re
pattern = r"expression"
text = "The cat is in the hat."
matches = re.findall(pattern, text)
print(matches)
# Output: ['cat', 'hat']
The following example shows how to replace a pattern in a string:
import re
pattern = r"[a-z]+at"
text = "The cat is in the hat."
matches = re.findall(pattern, text)
print(matches)
# Output: ['cat', 'hat']
new_text = re.sub(pattern, "dog", text)
print(new_text)
# Output: "The dog is in the dog."
The following example shows how to extract information from a string using regular expressions:
import re
text = "The email address is example@example.com."
pattern = r"\w+@\w+\.\w+"
match = re.search(pattern, text)
if match:
email = match.group()
print(email)
# Output: example@example.com
Regular expressions are a powerful tool for working with strings and text data in Python. Whether you're matching patterns, replacing text, or extracting information, regular expressions make it easy to perform complex string operations with just a few lines of code. With a little bit of practice, you'll be able to use regular expressions to solve all sorts of string-related problems in Python.