Regular Expression

 

Regular Expression?

A regular expression (regex) is a special string used to describe a pattern for searching or matching text.

Think of it as a search formula for strings.

📦 The re Module

Python has a built-in module called re for working with regular expressions.

✅ Importing:

import re

Common Functions in re Module
Function
Description
re.match()
Matches pattern at the beginning of string
re.search()
Searches pattern anywhere in string
re.findall()
Returns all matching substrings
re.finditer()
Returns iterator of matches
re.sub()
Replaces pattern with another string
re.split()
Splits string based on pattern
re.compile()
Compiles a regex pattern into an object

Basic Pattern Examples
Pattern
Meaning
.
Any character except newline
^
Start of string
$
End of string
*
0 or more times
+
1 or more times
?
0 or 1 time
{m}
Exactly m times
{m,n}
Between m and n times
[...]
Match any one of the characters
\d
Digit (0–9)
\D
Not a digit
\w
Word character (a-z, A-Z, 0-9, _)
\W
Not a word character
\s
Whitespace
\S
Not whitespace

Basic Pattern Examples
Pattern
Meaning
.
Any character except newline
^
Start of string
$
End of string
*
0 or more times
+
1 or more times
?
0 or 1 time
{m}
Exactly m times
{m,n}
Between m and n times
[...]
Match any one of the characters
\d
Digit (0–9)
\D
Not a digit
\w
Word character (a-z, A-Z, 0-9, _)
\W
Not a word character
\s
Whitespace
\S
Not whitespace
✅ Examples
1. re.match()
import re
result = re.match("Hello", "Hello World")
print(result.group())  # Output: Hello
2. re.search()
result = re.search("World", "Hello World")
print(result.group())  # Output: World
3. re.findall()
text = "My number is 9876543210 and 1234567890"
numbers = re.findall(r'\d{10}', text)
print(numbers)  # Output: ['9876543210', '1234567890']
4. re.sub()
text = "abc abc abc"
replaced = re.sub("abc", "xyz", text)
print(replaced)  # Output: xyz xyz xyz
5. re.split()
text = "apple,banana,grapes"
fruits = re.split(",", text)
print(fruits)  # Output: ['apple', 'banana', 'grapes']

🎯 Using re.compile() for Better Reuse
pattern = re.compile(r'\d+')
result = pattern.findall("There are 2 apples and 10 bananas")
print(result)  # Output: ['2', '10']

📌 Practical Example: Email Validation
email = "user@example.com"
if re.match(r'^[\w\.-]+@[\w\.-]+\.\w+$', email):
    print("Valid email")
else:
    print("Invalid email")

Best Practices
Use raw strings r"pattern" to avoid escape issues.
Test regex patterns using online tools like regex101.com.
Use compile() when using a pattern multiple times.

📚 Summary Table
Function
Use
re.match()
    Checks beginning of a string
re.search()
    Searches for pattern
re.findall()
    Returns all matches
re.sub()
    Replace substrings
re.split()
    Split by pattern
re.compile()    
    Precompile pattern
Write a function using regex to check if a password meets the following rules: minimum 8 
characters, includes at least one uppercase letter, onenumber, and one special character. 
( university question)

import re

def is_valid_password(password):
    # Check minimum length
    if len(password) < 8:
        return False

    # Regex checks
    has_uppercase = re.search(r'[A-Z]', password)
    has_digit = re.search(r'\d', password)
    has_special = re.search(r'[!@#$%^&*(),.?":{}|<>]', password)

    if has_uppercase and has_digit and has_special:
        return True
    else:
        return False
# Test cases
passwords = [
    "Password1!",     # Valid
    "password1!",     # Missing uppercase
    "Password!",      # Missing number
    "Password1",      # Missing special character
    "Pass1!",         # Less than 8 characters
]

for pwd in passwords:
    print(f"{pwd}: {'Valid' if is_valid_password(pwd) else 'Invalid'}")

Output
Password1!: Valid
password1!: Invalid
Password!: Invalid
Password1: Invalid
Pass1!: Invalid

From a multi-line string containing log entries like "User: John, ID: 001", extract all user names
using regular expressions. Convert the extracted names into a NumPy array. Assume you now 
want to sort them alphabetically and count how many start with each letter. 
Write code to do this and return the results. ( University Question)

Below is a step-by-step solution to: 
 
Extract all user names from a multiline log string using regex 
Convert them into a NumPy array 
Sort the names alphabetically 
Count how many names start with each letter
import re
import numpy as np
from collections import Counter

# Multiline log string
log_data = """
User: John, ID: 001
User: Alice, ID: 002
User: Bob, ID: 003
User: David, ID: 004
User: Charlie, ID: 005
User: Anna, ID: 006
"""

# Step 1: Extract all user names using regex
user_names = re.findall(r'User:\s*(\w+)', log_data)
print("Extracted names:", user_names)

# Step 2: Convert to NumPy array
names_array = np.array(user_names)

# Step 3: Sort the array alphabetically
sorted_names = np.sort(names_array)
print("Sorted names:", sorted_names)

# Step 4: Count how many names start with each letter
first_letters = [name[0].upper() for name in sorted_names]
letter_counts = Counter(first_letters)

# Convert to a sorted dictionary for neat output
sorted_counts = dict(sorted(letter_counts.items()))

# Final Output
print("Counts by starting letter:", sorted_counts)

Output
Extracted names: ['John', 'Alice', 'Bob', 'David', 'Charlie', 'Anna'] 
Sorted names: ['Alice' 'Anna' 'Bob' 'Charlie' 'David' 'John'] 
Counts by starting letter: {'A': 2, 'B': 1, 'C': 1, 'D': 1, 'J': 1}