⚡ Pattern Presets
Click a preset to load a common regex pattern
🧪 Regex Pattern Tester
📝 Example Patterns
Click an example to see it in action
📚 Understanding Regular Expressions
Regular expressions (regex) are powerful patterns used to match, search and manipulate text. They're supported in virtually every programming language and are essential for text processing, validation and data extraction.
Basic Syntax:
- Literals - Normal characters match themselves (abc matches "abc")
- . (dot) - Matches any single character except newline
- * (star) - Matches 0 or more of the preceding element
- + (plus) - Matches 1 or more of the preceding element
- ? (question) - Matches 0 or 1 of the preceding element (optional)
- ^ (caret) - Matches the start of a line or string
- $ (dollar) - Matches the end of a line or string
Character Classes:
- [abc] - Matches any character in the set (a, b or c)
- [^abc] - Matches any character not in the set
- [a-z] - Matches any character in the range (a through z)
- \d - Matches any digit (0-9), equivalent to [0-9]
- \w - Matches word characters (letters, digits, underscore)
- \s - Matches whitespace (spaces, tabs, newlines)
- \D, \W, \S - Negated versions (non-digit, non-word, non-whitespace)
Quantifiers:
- {n} - Matches exactly n occurrences
- {n,} - Matches n or more occurrences
- {n,m} - Matches between n and m occurrences
- *? - Lazy star (matches as few as possible)
- +? - Lazy plus (non-greedy version)
Groups and Capture:
- (pattern) - Capturing group (saves match for extraction)
- (?:pattern) - Non-capturing group (groups without saving)
- (?<name>pattern) - Named capturing group
- (a|b) - Alternation (matches a or b)
Common Use Cases:
- Form Validation - Validate email addresses, phone numbers, passwords
- Data Extraction - Extract URLs, emails, dates from text
- Text Processing - Find and replace patterns in documents
- Log Parsing - Extract specific data from log files
- Input Sanitization - Clean user input, remove unwanted characters
- URL Routing - Match URL patterns in web applications
Best Practices:
- Start simple and test incrementally - build complex patterns step by step
- Use non-capturing groups (?:) when you don't need to extract data
- Escape special characters with backslash when matching literally
- Use anchors (^ and $) for full string validation
- Test your patterns with edge cases and invalid input
- Consider using lazy quantifiers (*?, +?) to avoid over-matching
❓ Frequently Asked Questions
A regex tester (regular expression tester) is a tool for creating, testing and debugging regex patterns. You need it to validate text patterns, extract data from strings, test pattern matching before deploying code and learn regex syntax interactively. Our tool highlights matches, shows capture groups, provides instant feedback and includes common pattern presets for emails, URLs, phone numbers and more.
Enter your regex pattern in the pattern field (without delimiters), paste or type your test text in the test string area and click 'Test Pattern'. The tool will highlight all matches, show capture groups, display match count and provide detailed results. Use flags (global, case-insensitive, multiline, etc.) to modify pattern behavior.
Regex flags modify pattern matching behavior. 'g' (global) finds all matches instead of just the first. 'i' (case-insensitive) ignores letter case. 'm' (multiline) treats ^ and $ as line boundaries. 's' (dotAll) makes . match newlines. 'u' (unicode) enables full unicode support. Combine flags by checking multiple boxes to customize pattern behavior.
Capture groups are portions of a regex pattern enclosed in parentheses that extract specific parts of a match. For example, in pattern '(\w+)@(\w+\.\w+)', group 1 captures the username and group 2 captures the domain. Our tool displays each capture group separately with its index and value, making it easy to extract structured data from text.
Absolutely! All regex pattern testing and matching happens locally in your browser using JavaScript. No data is ever transmitted to our servers or any third party. You can use this tool completely offline. Your test strings, patterns and sensitive data remain 100% private.
Yes! Click the 'Save Pattern' button to store your regex pattern and test string in browser local storage. Saved patterns appear in the history section below the tester. You can quickly reload saved patterns, copy them to clipboard or delete them. All data is stored locally in your browser.
Common regex use cases include: validating email addresses, phone numbers and URLs; extracting data from logs and text files; finding and replacing text patterns; parsing structured data (CSV, JSON, etc.); validating user input in forms; searching code for specific patterns; data cleaning and transformation.
Use a pattern like '^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$' for basic email validation. This checks for username characters, @ symbol and domain with TLD. Click our 'Email Address' preset to load this pattern and test it with examples. Note: Perfect email validation is complex - this pattern covers most common cases.
Greedy matching (default) matches as much text as possible. For example, '.+' in 'hello world' matches the entire string. Lazy matching (using ? after quantifiers like .+?, .*?) matches as little as possible. '.+?' in '<div>content</div>' matches just '<div>' instead of the entire string. Use lazy matching when you want minimal, non-overlapping matches.
Yes! Our tool is perfect for learning regex. Try the preset patterns to see working examples, modify them to understand how changes affect matching, view capture groups to learn pattern structure and use the instant feedback to experiment. The tool shows exactly what matches and why, making regex learning interactive and visual.