Regex TesterDev
Free Regex Tester - Test and debug regular expressions online in real-time with multiple matching modes and flags. Developer essential. Try it now!
Usage Guide
1. Input Regular Expression
Enter your matching pattern in the regular expression input box. The input box uses /pattern/ format with automatic slash delimiters.
2. Select Match Flags
Choose one or more regular expression flags as needed to control matching behavior:
3. Input Test Text
Enter the text content to match in the test text box. Supports multi-line text for testing complex matching scenarios.
4. View Match Results
The result area on the right displays matching status in real-time, including match count and highlighted matched text.
FAQ
Q: What is a regular expression?
A: A regular expression (Regex) is a powerful text pattern matching tool used to find, match, and replace text with specific patterns in strings. It is widely used in data validation, text search, content extraction, and is an essential skill for developers.
Q: How to match email addresses?
A: Use the pattern ^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$ to match standard email addresses. This pattern ensures the email contains an @ symbol, and the domain part includes at least one dot and a top-level domain of 2 or more characters.
Q: What is the difference between greedy and non-greedy matching?
A: Greedy matching (default) matches as many characters as possible, e.g., .* matches the longest possible string. Non-greedy matching adds ? after quantifiers to become .*?, matching as few characters as possible. For example, for text <div>test</div>, greedy pattern <.*> matches the entire string, while non-greedy pattern <.*?> only matches <div> and </div>.
Q: How to match Chinese characters?
A: Use the Unicode range [\u4e00-\u9fa5] to match common Chinese characters. The complete pattern ^[\u4e00-\u9fa5]+$ can validate if a string consists entirely of Chinese characters. We recommend enabling the u flag for proper Unicode character handling.
Q: How to optimize regular expression performance?
A: Optimization tips: ① Avoid excessive use of greedy quantifiers and backtracking ② Use non-capturing groups (?:) instead of capturing groups () ③ Place fixed strings at the pattern start ④ Use character classes [abc] instead of multiple alternatives (a|b|c) ⑤ Avoid nested quantifiers like (a+)+ ⑥ Use anchors ^ $ to limit matching scope.
Q: Is my data safe?
A: Completely safe. All calculations are performed locally in your browser, data is never uploaded to servers, completely offline processing.
Use Cases
Data Validation
Validate user input data format before form submission, such as email, phone number, ID number, etc.
- Use ^ and $ to ensure complete matching, avoiding partial matches
- Enable i flag for case-insensitive validation
- Use preset common regex patterns to get started quickly
- Test various edge cases to ensure validation accuracy
Text Search & Extraction
Search and extract content with specific patterns from large text blocks, such as extracting all URLs, email addresses, or phone numbers.
- Enable g flag for global search
- Use capturing groups () to extract needed parts
- Enable m flag for multi-line text processing
- Use non-greedy matching *? to avoid over-matching
Log Analysis
Parse and analyze log files, extracting timestamps, IP addresses, error codes, and other key information.
- Use \d{4}-\d{2}-\d{2} to match date formats
- Use IPv4 regex to match IP addresses
- Enable m flag for line-by-line log processing
- Use named capturing groups for better readability
Code Refactoring
Use regular expressions in code editors for batch find and replace, quickly refactoring code.
- Use \b word boundaries to avoid false matches
- Use capturing groups and backreferences for replacement
- Validate in testing tool first before applying to code
- Save common refactoring patterns for reuse
Data Cleaning
Clean and standardize data, such as removing extra spaces, unifying date formats, extracting structured information.
- Use \s+ to match multiple whitespace characters
- Use trim() with regex to remove leading/trailing spaces
- Use replacement function to standardize data formats
- Process complex cleaning tasks step by step
Learning Resources
- MDN Regular Expressions Guide - Comprehensive syntax reference and examples
- Regex101 - Online regex testing and debugging tool
- RegexOne - Interactive regex tutorial
- Regular Expressions 30-Minute Tutorial - Quick start guide