Data Extraction

Data extraction methods are essential for testing environments. Regular expressions provide a powerful targeting tool for validating and extracting specific data patterns.

Common Regular Expression Patterns

Email Validation

Ensures valid characters before the @ symbol and proper domain structure:

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

UK National Insurance Number (NINO)

Targets UK National Insurance Numbers in the format QQ123456C:

^[A-CEGHJ-PR-TW-Z]{2}[0-9]{6}[A-D]$

Whitespace Trimming

Removes leading and trailing spaces from lines:

^\s+|\s+$

Strong Password Validation

Requires lowercase, uppercase, numbers, special characters, and a minimum of 8 characters:

^(?=.*[a-z])(?=.*[A-Z])(?=.*\d)(?=.*[@$!%*?&])[A-Za-z\d@$!%*?&]{8,}$

Date Format (YYYY-MM-DD)

Validates date structure:

^\d{4}-(0[1-9]|1[0-2])-(0[1-9]|[12]\d|3[01])$

Username Validation

Allows underscores and hyphens, 3-16 character length:

^[a-zA-Z0-9_-]{3,16}$

IPv4 Address

Validates IPv4 address format:

^(?:(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(?:25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$

IPv6 Address

Validates IPv6 addresses in formats like 2001:cdba:0000:0000:0000:0000:3257:9652:

^([0-9a-fA-F]{1,4}:){7}[0-9a-fA-F]{1,4}$

Time Format (12-hour)

Validates time in HH:MM format:

^(0?[1-9]|1[0-2]):[0-5][0-9]$

Time Format (24-hour)

Validates time in HH:MM:SS format:

^([01]?[0-9]|2[0-3]):[0-5][0-9]:[0-5][0-9]$

International Phone Numbers

Supports country codes and extensions:

^\+?[1-9]\d{1,14}$

Using Regular Expressions

Regular expressions can be used in various contexts:

• JMeter - Regular Expression Extractor and Boundary Extractor
• Programming languages - Python, Java, JavaScript all have regex support
• Text editors - VS Code, Sublime Text, and others support regex search
• Command line - grep, sed, and awk utilities

Testing Your Patterns

Before using regex patterns in production tests, validate them using online tools:

1. Create test cases for both valid and invalid inputs
2. Test edge cases specific to your data
3. Consider performance for large datasets

Further Reading

• Regular Expressions Cookbook
• Regex101 - Online Regex Tester