Regular-Expressions_regex

The ReadyRegex 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.

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To test regular expressions use regex101.

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

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