Test and debug regular expressions with real-time match highlighting, group extraction, and flag support. Runs instantly in your browser.
Regex Tester processes your text in the browser, which means even sensitive strings stay private.
It's one of the free
String & Text Tools
on UseToolSuite.
Use it below, then scroll down for a step-by-step guide, answers to common questions, and related tools.
What is Regex Tester?
Regex Tester is a free online tool that lets you write, test, and debug
regular expressions in real time against any test string. It supports
all standard JavaScript regex flags including global (g),
case-insensitive (i), multiline (m), and dotAll (s), giving you full
control over matching behavior. As you type your pattern and test input,
matches are highlighted and listed instantly, providing immediate visual
feedback. Everything runs locally in your browser — no data is ever sent
to a server, so you can safely test patterns against sensitive text.
When to use it?
Use the Regex Tester whenever you're building or refining a regular
expression pattern and want to validate it against sample data before
integrating it into your code. It's especially valuable during form
validation development, log parsing, data extraction tasks, or when
you're writing patterns for search-and-replace operations. The real-time
feedback loop helps you catch edge cases and off-by-one matching errors
much faster than testing within your application code.
Common use cases
Developers and data engineers frequently use Regex Tester to craft and
validate email, phone number, and URL validation patterns, build
expressions for parsing log files and extracting structured data from
unstructured text, develop search patterns for code refactoring using
find-and-replace workflows, create patterns for input sanitization and
security filtering, and prototype data extraction rules for web scraping
or ETL pipelines. It's also a great learning tool for understanding how
regex quantifiers, groups, lookaheads, and character classes behave.
Battle-tested patterns to start from
| Target | Pattern |
|---|
| Email (pragmatic) | ^[^\s@]+@[^\s@]+\.[^\s@]+$ |
| IPv4 address | ^(\d{1,3}\.){3}\d{1,3}$ (validate octets ≤255 in code) |
| ISO date | ^\d{4}-\d{2}-\d{2}$ |
| Slug | ^[a-z0-9]+(?:-[a-z0-9]+)*$ |
| Hex color | ^#(?:[0-9a-fA-F]{3}){1,2}$ |
Treat these as starting points: the “perfect” email regex is a famous trap — RFC 5322 allows things no signup form should accept. Validate shape with a simple pattern and confirm deliverability by actually sending the email.
Capture groups: numbered, named, non-capturing
Parentheses do three jobs. (...) captures by number, (?<year>...) captures by name — far more maintainable in replacement strings ($<year>) and in code — and (?:...) groups without capturing, which keeps numbering stable and is marginally faster. A pattern littered with unnamed groups becomes write-only; naming the two or three groups you actually extract is the single highest-leverage readability habit in regex.
When the answer isn’t a bigger regex
Regular expressions match regular languages — they fundamentally cannot parse arbitrarily nested structures. If you’re matching HTML tags with their contents, balanced parentheses, or JSON substrings, the pattern that “almost works” will fail on real input forever. Reach for a real parser (DOMParser for HTML, JSON.parse for JSON) and use regex for what it excels at: tokens, line formats, log fields, and validation of flat shapes.
Anchor everything you can (^...$ lets the engine fail fast), prefer character classes over alternation ([abc] beats (a|b|c)), and be precise instead of reaching for .* — greedy dot-star forces backtracking across the whole input on failure. If a pattern runs on user-supplied text on a server, test it here against pathological inputs (long strings of almost-matches) before deploying; ReDoS is just catastrophic backtracking weaponized.
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