How do I use the "Generate Regex Patterns for Text Matching" prompt?

Copy the prompt template, fill in the variables (PATTERN_DESCRIPTION, USE_CASE, REGEX_FLAVOR, SAMPLE_MATCHES, SAMPLE_NON_MATCHES, ADDITIONAL_REQUIREMENTS), and paste it into ChatGPT, Claude, or Gemini.

What AI tools work with this coding prompt?

This prompt works with chatgpt, claude, gemini. Simply copy and paste the template into any of these AI assistants.

Tips for getting the best results?

Always test your regex with edge cases and unexpected input to avoid false positives Use online regex testers like regex101.com to visualize and debug your patterns Consider performance implications - complex patterns can be slow on large datasets Document your regex patterns with comments explaining each component for future maintenance Be aware that different programming languages have slightly different regex flavors and capabilities

coding intermediate

Generate Regex Patterns for Text Matching

Create precise regex patterns with AI assistance. Generate regular expressions for data validation, text parsing, and pattern matching tasks.

Works with: chatgptclaudegemini

Prompt Template

You are a regex expert helping to create precise regular expression patterns. I need a regex pattern for the following requirement: **Target Pattern**: [PATTERN_DESCRIPTION] **Use Case**: [USE_CASE] **Programming Language/Flavor**: [REGEX_FLAVOR] **Sample Text to Match**: [SAMPLE_MATCHES] **Text That Should NOT Match**: [SAMPLE_NON_MATCHES] **Additional Requirements**: - [ADDITIONAL_REQUIREMENTS] Please provide: 1. The complete regex pattern with proper escaping 2. A breakdown explaining each component of the regex 3. Any flags or modifiers needed 4. Test cases showing matches and non-matches 5. Alternative approaches if applicable 6. Performance considerations for large datasets 7. Common edge cases to be aware of Format your response clearly with code blocks for the regex pattern and explanations for each component. If there are multiple valid approaches, explain the trade-offs between them.

Variables to Customize

[PATTERN_DESCRIPTION]

Describe what pattern you want to match

Example: Email addresses with proper validation including internationalized domain names

[USE_CASE]

Explain how you'll use this regex

Example: Form validation in a web application to ensure users enter valid email addresses

[REGEX_FLAVOR]

Specify the regex engine or programming language

Example: JavaScript (ES2018+)

[SAMPLE_MATCHES]

Examples of text that should match

Example: user@example.com, test.email+tag@domain.co.uk, name@sub.domain.org

[SAMPLE_NON_MATCHES]

Examples of text that should not match

Example: plaintext, @domain.com, user@, invalid.email, user space@domain.com

[ADDITIONAL_REQUIREMENTS]

Any specific constraints or preferences

Example: Must be case-insensitive, should allow unicode characters, maximum length 254 characters

Example Output

## Regex Pattern ```javascript /^[a-zA-Z0-9.!#$%&'*+/=?^_`{|}~-]+@[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?)*$/i ``` ## Component Breakdown - `^` - Start of string anchor - `[a-zA-Z0-9.!#$%&'*+/=?^_`{|}~-]+` - Local part: allowed characters (RFC 5322) - `@` - Literal @ symbol - `[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?` - Domain label (max 63 chars) - `(?:\.[a-zA-Z0-9](?:[a-zA-Z0-9-]{0,61}[a-zA-Z0-9])?)*` - Additional domain labels - `$` - End of string anchor - `i` flag - Case insensitive matching ## Test Cases **Matches**: ✅ user@example.com, test.email@domain.co.uk **Non-matches**: ❌ @domain.com, user@, invalid..email@domain.com ## Performance Notes This pattern uses non-capturing groups and atomic matching where possible to improve performance on large datasets.

Pro Tips for Best Results

Always test your regex with edge cases and unexpected input to avoid false positives
Use online regex testers like regex101.com to visualize and debug your patterns
Consider performance implications - complex patterns can be slow on large datasets
Document your regex patterns with comments explaining each component for future maintenance
Be aware that different programming languages have slightly different regex flavors and capabilities