# Regex Generator

> Describe a text pattern in plain English and get the matching regular expression

**Category:** Dev
**Keywords:** regex, regular expression, pattern, match, text, generator, regexp, search, replace, validate
**URL:** https://complete.tools/regex-generator

## Understanding regular expression syntax

Regular expressions are built from several categories of syntax elements that combine to form powerful patterns:

**Character classes** define sets of characters to match. `\d` matches any digit (0-9), `\w` matches word characters (letters, digits, underscore), `\s` matches whitespace, and `[abc]` matches any character inside the brackets. Negated classes like `\D`, `\W`, and `\S` match the opposite of their lowercase counterparts.

**Quantifiers** control how many times a pattern element repeats. `*` means zero or more, `+` means one or more, `?` means zero or one, and `{n,m}` matches between n and m occurrences. Adding `?` after a quantifier (like `*?` or `+?`) makes it lazy, matching as few characters as possible.

**Anchors** match positions rather than characters. `^` matches the start of a string or line, `$` matches the end, and `\b` matches a word boundary. These are essential for ensuring patterns match complete tokens rather than substrings.

**Groups and alternation** add structure. Parentheses `()` create capturing groups that extract matched substrings. `(?:...)` creates a non-capturing group for grouping without extraction. The pipe `|` acts as logical OR, matching the pattern on either side.

**Lookaheads and lookbehinds** match positions based on what comes before or after without consuming characters. `(?=...)` is a positive lookahead, `(?!...)` is a negative lookahead, `(?<=...)` is a positive lookbehind, and `(?<!...)` is a negative lookbehind. These are powerful for complex validation like password rules.

## Common regex patterns

Some of the most frequently needed regular expression patterns include:

**Email addresses:** A basic email pattern matches a local part (letters, digits, dots, hyphens) followed by `@`, a domain name, and a top-level domain. The RFC-compliant version is extremely complex, but practical patterns like `[\w.+-]+@[\w-]+\.[\w.]+` handle most real-world cases.

**URLs:** URL patterns typically match an optional protocol (`https?://`), domain name, optional port, path, query parameters, and fragment. A common pattern starts with `https?://[\w.-]+(?:/[\w./?%&=-]*)?`.

**Phone numbers:** US phone patterns need to handle formats like `(555) 123-4567`, `555-123-4567`, `555.123.4567`, and `5551234567`. International formats add country codes and varying digit counts.

**Dates:** Date patterns vary by format. `YYYY-MM-DD` uses `\d{4}-\d{2}-\d{2}`, while `MM/DD/YYYY` uses `\d{2}/\d{2}/\d{4}`. More precise patterns validate month and day ranges.

**IP addresses (IPv4):** Each octet matches 0-255, typically validated with a pattern like `(?:25[0-5]|2[0-4]\d|[01]?\d\d?)` repeated four times with dots between them.

**Hex color codes:** These match patterns like `#fff` or `#ff0000` with `#(?:[0-9a-fA-F]{3}){1,2}`.

## Regex flavors explained

Different programming languages implement regular expressions with subtle but important differences:

**JavaScript** uses the `RegExp` object and literal syntax (`/pattern/flags`). It supports lookaheads and (since ES2018) lookbehinds, named groups with `(?<name>...)`, and Unicode property escapes with the `u` flag. The `g` flag enables global matching, and `s` makes `.` match newlines.

**Python** provides the `re` module with `re.compile()`, `re.search()`, `re.match()`, and `re.findall()`. Python uses raw strings (`r'pattern'`) to avoid double-escaping backslashes. It supports named groups with `(?P<name>...)` syntax, which differs from other flavors.

**Java** uses `java.util.regex.Pattern` and `Matcher`. Backslashes in string literals need double-escaping (`\\d` instead of `\d`). Java supports possessive quantifiers (`++`, `*+`) and atomic groups, which can improve performance on complex patterns.

**PHP** uses PCRE (Perl Compatible Regular Expressions) via `preg_match()` and `preg_replace()`. PHP patterns are enclosed in delimiters (typically `/pattern/flags`). PCRE is one of the most feature-rich engines, supporting recursive patterns and conditional subpatterns.

**Go** uses the `regexp` package, which implements RE2 syntax. Notably, Go does not support lookaheads or lookbehinds, making it more limited but guaranteeing linear-time matching performance.

**.NET** provides the `System.Text.RegularExpressions` namespace with one of the most powerful regex engines available. It supports balancing groups for matching nested structures, right-to-left matching, and unlimited-length lookbehinds.

## How to use

1. Describe the pattern you need in plain English. Be specific about what should and should not match. For example, "Match a US phone number with optional country code and area code in parentheses."
2. Optionally paste example text in the test text field. This helps verify the generated regex works on real data.
3. Select your programming language's regex flavor from the dropdown. This ensures the generated pattern uses syntax compatible with your language's regex engine.
4. Click "Generate Regex" to send your description to the AI engine.
5. Review the generated pattern, its explanation, and the breakdown table that explains each component.
6. Check the example matches to verify the pattern handles both matching and non-matching cases correctly.
7. If you provided test text and selected JavaScript, review the live matches section to see exactly what was found in your text.
8. Copy the regex pattern or the code snippets directly into your project.

## FAQs

**Q:** What regex flavors are supported?


**A:** JavaScript, Python, Java, PHP, Go, and .NET. Each flavor generates syntax compatible with that language's regex engine, accounting for differences in feature support and escaping rules.


**Q:** Can I test the regex against sample text?


**A:** Yes. Paste example text into the test text field before generating. The AI will consider your test text when creating the pattern, and for JavaScript flavor, the tool runs the regex locally to show exactly which parts of your text match.


**Q:** How complex can my pattern description be?


**A:** You can describe complex patterns including lookaheads, optional groups, alternations, and specific character constraints. The more specific your description, the more accurate the generated regex will be. For example, "Match a password with at least 8 characters, one uppercase letter, one digit, and one special character" produces a pattern with multiple lookaheads.


**Q:** Why does the same description produce different patterns for different flavors?


**A:** Different regex engines support different features. For instance, Go does not support lookaheads, so the generator uses alternative approaches. Python uses a different syntax for named groups than JavaScript. The AI adapts the pattern to each engine's capabilities.


**Q:** Can I use the generated regex in production code?


**A:** The generated patterns are a strong starting point, but you should always test them against edge cases specific to your application. Regex edge cases can be subtle, especially with international characters, unusual formatting, or extremely long inputs.


**Q:** Is there a limit to how many times I can generate patterns?


**A:** The AI API has a rate limit of 10 requests per IP address per minute. This is sufficient for normal use but prevents abuse.

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*Generated from [complete.tools/regex-generator](https://complete.tools/regex-generator)*