Python Regular Expression

import re
my_string="Your birth day is on 24-12-2002"
dt=re.search("([0-9]{2}\-[0-9]{2}\-[0-9]{4})", my_string)
print(dt[1])

24-12-2002

Links ( URLs) from a file

import re
path='C:/dir_name/string_functions.php' # path of the file to read
fob=open(path,'r') # Open in read mode 
data=fob.read() # collect data 
fob.close() # close file object 
#print(data)     
urls1 = re.findall(r'href=[\'"]?([^\'" >]+)', data)
print(urls1)

urls1 = re.findall(r'href=[\'"]?([^\'" >]+)', data,re.IGNORECASE)

Searching string

import re
if re.search('PLUS', 'Welcome to plus2net.com', re.IGNORECASE):
    print('It is there') # True 
else:
    print('It is NOT there') # False

It is there

Additional Examples and Use Cases for Python Regular Expressions

Example: Extracting Email Addresses from Text

We can use regular expressions to identify and extract email addresses from a string. This is useful for tasks like data cleaning or web scraping.

import re
text = "Contact us at support@example.com or sales@example.co.uk"
emails = re.findall(r'\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,7}\b', text)
print(emails)

['support@example.com', 'sales@example.co.uk']

Use Case: Validating Strong Passwords

We can enhance the user experience by implementing regular expressions to validate the complexity of user-entered passwords.

import re
password = "P@ssw0rd123"
if re.match(r'^(?=.*[A-Z])(?=.*[a-z])(?=.*[0-9])(?=.*[@#$%^&+=]).{8,}$', password):
    print("Password is strong")
else:
    print("Password is weak")

Password is strong

Advanced Feature: Using `re.sub` to Replace Patterns

The re.sub() method allows us to search for patterns and replace them. This is beneficial when sanitizing or formatting text.

import re
text = "Visit https://www.example.com or http://example.org"
updated_text = re.sub(r'https?://\S+', '[LINK]', text)
print(updated_text)

Visit [LINK] or [LINK]

Example: Splitting Strings by Multiple Delimiters

Regular expressions can be used to split a string based on multiple delimiters. This is useful for parsing CSV-like strings.

import re
data = "apple;banana,orange:grape"
fruits = re.split(r'[;,:]', data)
print(fruits)

['apple', 'banana', 'orange', 'grape']