RegEx in Python

Regular expressions (regex or regexp) in Python are used for pattern matching and text manipulation. Python provides the re module, which allows you to work with regular expressions.

Here are some common tasks and examples of how to use regular expressions in Python:

1. Importing the re Module:

To use regex in Python, you need to import the re module first:

import re

2. Matching Patterns:

The re.match() function matches the pattern at the beginning of a string.

Example:

import re

pattern = r"Sun"
text = "Sun is the ultimate source of energy"

match = re.match(pattern, text)
if match:
    print("Pattern found:", match.group())
else:
    print("Pattern not found")

Output:

Pattern found: Sun

3. Searching for Patterns:

The re.search() function finds and returns the first occurrence of a pattern within a string.

Example:

import re

pattern = r"\d+" # pattern to match digit
text = "The first code is 9097 and the second code is 2032"

result = re.search(pattern, text)
print(result.group())

Output:

9097

4. Searching for Patterns while Ignoring Case:

To perform case-insensitive matching, you can use flags like re.IGNORECASE.

Example:

import re

pattern = r"tree"
text = "The TREE is tall."

match = re.search(pattern, text, re.IGNORECASE)
if match:
    print("Pattern found:", match.group())
else:
    print("Pattern not found.")

Output:

Pattern found: TREE

5. Finding all Matches:

The re.findall() function finds all occurrences of a pattern in a string and returns them in a list.

import re

pattern = "\d+" # match digits
text = "The first code is 9091. The second code is 2043. The third code is 7203. The fourth code is 5499."

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

Output:

['9091', '2043', '7203', '5499']

6. Replacing Matches:

The re.sub() function replaces all occurrences of a pattern with a specified string. The unchanged string is returned if the pattern is not found.

Example:

import re

pattern = "\\s+"  # Pattern for matching one or more whitespaces
text = "The     first code    is    9091."

replace_with = " "  # Replace with a single space

replaced_text = re.sub(pattern, replace_with, text)
print("Replaced text:", replaced_text)

Output:

Replaced text: The first code is 9091.

7. Splitting using a Matching Pattern:

The split() function splits the source string at every match of the pattern and returns the resulting list of substrings.

Example:

import re

pattern = "[,\\s]+" # Pattern for splitting by comma and spaces
text = "a@example.com , b@example.com, c@example.com, d@example.com"

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

Output:

['a@example.com', 'b@example.com', 'c@example.com', 'd@example.com']

Regular Expression Metacharacters

Metacharacters are characters with special meaning. Following are the list of Regular Expression metacharacters in Python:

Regular Expression Sequence Characters

Regular Expression uses the "\" character to allow special characters to be used without invoking their special meaning. Following are the list of RegEx Backslash Characters in Python: