Regular Expressions, commonly called Regex, are patterns used to search, match, and manipulate text.
Python provides the built-in re module for working with regular expressions.
A regular expression is a sequence of characters that defines a search pattern.
For example, the pattern cat can be used to search for the word "cat".
import re
text = "The cat is sleeping."
result = re.search("cat", text)
print(result)<re.Match object ...>
Python's regular expression functionality is provided by the built-in re module.
import reAfter importing the module, you can use functions such as:
re.search()re.match()re.findall()re.finditer()re.sub()re.split()re.fullmatch()
The re.search() function searches the entire string for the first location where the pattern matches.
import re
text = "I am learning Python."
result = re.search("Python", text)
if result:
print("Pattern found")Pattern found
The re.match() function checks for a match at the beginning of the string.
import re
text = "Python is easy."
result = re.match("Python", text)
if result:
print("Match found")Match found
If the pattern does not occur at the beginning, re.match() returns None.
The re.fullmatch() function succeeds only when the entire string matches the pattern.
import re
text = "Python"
result = re.fullmatch("Python", text)
if result:
print("Full match")Full match
The re.findall() function returns all non-overlapping matches as a list.
import re
text = "Python is easy. Python is powerful."
result = re.findall("Python", text)
print(result)['Python', 'Python']
The re.finditer() function returns an iterator containing match objects.
import re
text = "Python is easy. Python is powerful."
matches = re.finditer("Python", text)
for match in matches:
print(match.group())Python Python
The re.sub() function replaces matches with another string.
import re
text = "I like Java."
new_text = re.sub("Java", "Python", text)
print(new_text)I like Python.
The re.split() function splits a string wherever the pattern matches.
import re
text = "apple,banana,orange"
result = re.split(",", text)
print(result)['apple', 'banana', 'orange']
Character classes allow you to match specific types or groups of characters.
| Pattern | Meaning |
|---|---|
[abc] |
Matches a, b, or c |
[^abc] |
Matches a character other than a, b, or c |
[a-z] |
Matches lowercase letters from a to z |
[A-Z] |
Matches uppercase letters from A to Z |
[0-9] |
Matches a digit from 0 to 9 |
The \d pattern matches a Unicode decimal digit by default.
import re
text = "My age is 25."
result = re.findall(r"\d", text)
print(result)['2', '5']
The + quantifier means one or more occurrences.
import re
text = "My age is 25 and my pin is 1234."
result = re.findall(r"\d+", text)
print(result)['25', '1234']
The \w pattern matches Unicode word characters by default, including letters, digits, and underscore.
import re
text = "Python_123"
result = re.findall(r"\w", text)
print(result)['P', 'y', 't', 'h', 'o', 'n', '_', '1', '2', '3']
The \s pattern matches whitespace characters such as spaces and line breaks.
import re
text = "Hello World"
result = re.findall(r"\s", text)
print(result)[' ']
The dot . matches almost any character except a newline by default.
import re
text = "cat"
result = re.findall(r".", text)
print(result)['c', 'a', 't']
The ^ symbol matches the beginning of a string, while $ matches the end.
import re
text = "Python"
result = re.search(r"^Python$", text)
if result:
print("Exact match")Exact match
Quantifiers specify how many times a pattern can occur.
| Quantifier | Meaning |
|---|---|
* |
Zero or more |
+ |
One or more |
? |
Zero or one |
{n} |
Exactly n times |
{n,} |
At least n times |
{n,m} |
Between n and m times |
import re
text = "I have 123 apples."
result = re.findall(r"\d+", text)
print(result)['123']
The + combines consecutive matching digits into one match.
import re
text = "color colour"
result = re.findall(r"colou*r", text)
print(result)['color', 'colour']
The * allows the character before it to occur zero or more times.
import re
text = "color colour"
result = re.findall(r"colou?r", text)
print(result)['color', 'colour']
The ? means that the preceding character or group is optional and may occur zero or one time.
Parentheses () are used to create groups in regular expressions.
import re
text = "My phone is 9876543210"
result = re.search(r"(\d{10})", text)
if result:
print(result.group(1))9876543210
import re
text = "Name: Rahul, Age: 25"
pattern = r"Name: (\w+), Age: (\d+)"
result = re.search(pattern, text)
if result:
print(result.group(1))
print(result.group(2))Rahul 25
The | symbol means "or".
import re
text = "I like Python"
result = re.search(r"Python|Java", text)
if result:
print(result.group())Python
Raw strings are commonly used when writing regular expressions because backslashes do not need to be escaped in the same way as ordinary Python strings.
pattern = r"\d+"
print(pattern)\d+
Using r"..." makes regex patterns easier to read, especially when they contain many backslashes.
import re
text = "Contact us at hello@example.com"
pattern = r"[\w.-]+@[\w.-]+\.\w+"
result = re.search(pattern, text)
if result:
print(result.group())hello@example.com
import re
text = "Call me at 9876543210"
pattern = r"\b\d{10}\b"
result = re.search(pattern, text)
if result:
print(result.group())9876543210
The re.IGNORECASE flag can be used when uppercase and lowercase differences should be ignored.
import re
text = "Python is powerful."
result = re.search("python", text, re.IGNORECASE)
if result:
print("Found")Found
The re.compile() function creates a compiled regular expression pattern that can be reused.
import re
pattern = re.compile(r"\d+")
text = "Age 25, PIN 1234"
result = pattern.findall(text)
print(result)['25', '1234']
| Pattern | Meaning |
|---|---|
\d |
Digit |
\w |
Word character |
\s |
Whitespace |
. |
Any character except newline by default |
^ |
Beginning of string |
$ |
End of string |
* |
Zero or more |
+ |
One or more |
? |
Zero or one |
| |
OR |
() |
Group |
[] |
Character class |
re module.re.search() searches for a pattern anywhere in the string.re.match() checks for a match at the beginning.re.fullmatch() requires the entire string to match.re.findall() returns all non-overlapping matches.re.sub() replaces matching text.re.split() splits text using a regular expression.*, +, and ? control repetition.\d, \w, and \s simplify pattern matching.Question: Which Python module is used for regular expressions?