Regular-Expressions_regex

The Ready to use Regex repository is a comprehensive collection of ready-to-use regular expressions (regex) for various common tasks. This repository aims to provide a valuable resource for developers, data analysts, and anyone working with text data, by offering a wide range of regex patterns specifically designed for tasks such as email validation, phone number parsing, credit card number recognition, and more.

1. Whitespaces
2. Phone Number (various formats)
   1. Validating phone numbers in various formats
   2. Normalizing phone numbers to a consistent format:
3. Email Addresses
   1. Validating email addresses:
   2. Extracting domain names from email addresses:
4. URLs
   1. Validating URLs:
   2. Extract Protocol
   3. Extract Domain
   4. Extract Path
   5. Extract Query Parameters
5. Data Extraction
   1. To extract dates:
   2. To extract time:
   3. To extract address:
   4. To extract values from XML:
6. Credit Card
   1. Validating credit card numbers:
   2. Extracting credit card expiration dates:
   3. Matching CVV (Card Verification Value) codes:

Whitespace

• Regex:

  \s+
  

Phone Numbers

• Validating phone numbers in different formats-
  • Regex pattern:

    ^(?:\+\d{1,3}\s?)?(?:\(\d{1,4}\)\s?)?(?:\d{1,4}[\s-])?\d{1,10}$
    

  • Example formats:
    • +1 (123) 456-7890
    • 5551234567
    • (999) 9999-9999
    • +1 5551234567
    • +1 (416) 555 7890
    • +33 123456789
    • +91 9876543210

• Normalizing phone numbers to a consistent format:

  • Regex pattern:

    ^(\+?\d{1,3}\s?)?(\(?\d{1,4}\)?\s?)?(\d{1,})[-\s]?(\d{1,})$
    

  • Example formats:
    • +1 (123) 456-7890 (normalizes to +11234567890)
    • 555 123 4567 (normalizes to 5551234567)
    • +55 (11) 98765-4321 (normalizes to 5511987654321)
    • +86 10 1234 5678 (normalizes to +861012345678
    • +91 98765 43210 (normalizes to +919876543210)

Email Addresses

• Validating email addresses:
  • Regex pattern:

    ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$
    

  • Example formats:
    • john.doe@example.com
    • jane_smith123@gmail.com
• Extracting domain names from email addresses:
  • Regex pattern:

    @[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$
    

  • Example formats:
    • john.doe@example.com (extracts example.com)
    • jane_smith123@gmail.com (extracts gmail.com)

URLs

• Validating URLs:
  • Regex pattern:

    https?:\/\/[\w.-]+\.[\w.-]+[^\s]*
    

  • Example formats:
    • https://www.example.com
    • http://ftp.example.com/file.txt

• Extracting different components of a URL(https://www.example.com/path/file.html?param1=value1&param2=value2):
  • Extracting protocol:
    • Regex pattern:

      ^(https?):\/\/
      

    • Example format:
      • https://
      • http://
  • Extracting domain:
    • Regex pattern:

      (https?):\/\/([a-zA-Z0-9.-]+)
      

    • Example format:
      • www.example.com
      • www.google.com
  • Extracting path:
    • Regex pattern:

      (https?):\/\/[a-zA-Z0-9.-]+(\/[^?\s]*)?
      

    • Example format:
      • /path/file.html
  • Extracting query parameters:
    • Regex pattern:

      (https?):\/\/[a-zA-Z0-9.-]+(\/[^?\s]*)?(\?[^#\s]*)?$
      

    • Example format:
      • ?param1=value1&param2=value2
    • Extracted Groups:
      • https
      • /path/file.html
      • ?param1=value1&param2=value2

Data Extraction

• Extracting specific patterns from unstructured text:

  • To extract dates:

    (\d{1,2})\/(\d{1,2})\/(\d{4})
    

    • Example:
      • Extract "12/31/2023" from a text.
  • To extract times:

    ([01]\d|2[0-3]):([0-5]\d)
    

    • Example:
      • Extract "18:45" from a text.
  • To extract addresses:

    \d+\s[A-Za-z]+\s[A-Za-z]+,\s[A-Za-z]+\s\d+
    

    • Example:
      • Extract "123 Main St, New York 10001" from a text.

• Extracting values from structured data formats:

  • To extract values from XML:

    <(.*?)>([^<]+)<\/\1>
    

    • Example:
      • Extract values between XML tags, such as

      # data
      <person>
        <name>John Doe</name>
        <age>25</age>
        <email>johndoe@example.com</email>
      </person>
      
      # Expected  Results 
      name John Doe
      age 25
      email johndoe@example.com
      

Credit Card

• Validating credit card numbers:
  • Regex Pattern:

    ^(?:\d{4}[ -]?){3}\d{4}$
    

    • Example Credit Card Numbers:
      • 4111 1111 1111 1111
      • 5555-5555-5555-4444
      • 3782822463100058
• Extracting credit card expiration dates:
  • Regex Pattern:

    (?:0[1-9]|1[0-2])\/20[2-9][0-9]
    

    • Example Expiration Dates:
      • 12/2023
      • 05/2025
      • 09/2030
• Matching CVV (Card Verification Value) codes:
  • Regex Pattern:

    ^\d{3,4}$
    

    • Example CVV Codes:
      • 123
      • 7890
      • 4321