Regex Tester

A regular expression (regex or regexp) is a sequence of characters that defines a search pattern. Originally formalized by mathematician Stephen Kleene in the 1950s, regular expressions have become an indispensable tool in programming for pattern matching, text searching, and string manipulation. Every major programming language -- JavaScript, Python, Java, Go, Ruby, and more -- includes built-in regex support.

Regular expressions use a combination of literal characters and metacharacters to describe patterns. Metacharacters like . (any character), * (zero or more), + (one or more), ? (optional), \d (digit), \w (word character), and \s (whitespace) provide powerful pattern-building capabilities. Grouping with parentheses () enables capturing substrings, while character classes [] match specific sets of characters. Anchors like ^ and $ match positions at the start and end of strings.

Mastering regex is crucial for tasks ranging from simple input validation (email addresses, phone numbers) to complex text processing (log parsing, data extraction, code refactoring). While regex syntax can appear daunting at first, a testing tool that provides visual match highlighting makes learning and debugging patterns significantly easier.

Enter your regex pattern in the "Pattern" field -- do not include the surrounding slashes. Select the desired flags: g (global, find all matches), i (case-insensitive), m (multiline, ^ and $ match line boundaries), or s(dotAll, . matches newlines). Paste or type your test string in the text area below, then click "Test" to see the results.

Matches are highlighted directly in the text with a yellow background, and a detailed table shows each match's index position, matched text, and any captured groups. Enable "Replace mode" to test substitutions -- enter a replacement pattern using $1, $2, etc. for captured group references. The replaced result is displayed in a separate section that you can copy to your clipboard.

• Validating user input formats such as email addresses, phone numbers, and postal codes
• Extracting structured data from log files, CSV records, or API responses
• Building search-and-replace patterns for code refactoring across large codebases
• Parsing and extracting URLs, IP addresses, or domain names from text
• Filtering and matching file paths or filenames using glob-like patterns
• Writing validation rules for form fields in frontend frameworks like React or Vue
• Testing web scraping selectors and text extraction patterns
• Learning and experimenting with regex syntax in a safe, visual environment