Regular Expressions (Regex) Explained for Beginners

Regex is a way to define patterns for finding or matching text. It looks intimidating at first, but a handful of building blocks cover most of what you’ll ever need.

What Is Regex?

A regular expression (regex, for short) is a sequence of characters that defines a search pattern. Instead of searching for one exact piece of text, a regex describes a shape that text can match, for example “any sequence of digits” or “a run of repeated spaces.” Regex shows up anywhere text needs to be searched, matched, validated, or replaced:

• Finding text patterns: locating every phone number or date in a document.
• Validating input: checking that a field looks like a reasonable email address or postcode.
• Searching text: powering “find” features in code editors and command-line tools.
• Replacing text: swapping every match of a pattern with something else in one pass.

Simple Regex Patterns

The simplest regex is just literal text. The pattern:

hello

matches the exact text “hello” wherever it appears. Most regex features build on top of this by adding special characters that stand in for “any character,” “zero or more,” and so on, rather than matching literally.

Common Regex Symbols

A small set of symbols covers most everyday regex use. Exact behavior can vary slightly between programming languages and regex engines, but the core ideas below are shared almost universally:

Character Classes

Square brackets define a character class: a set of characters where any one of them counts as a match.

• [abc]: matches exactly one character, as long as it’s a, b, or c
• [a-z]: matches any single lowercase letter, using a hyphen to define a range
• [0-9]: matches any single digit

Combined with + or *, a character class can match a whole run of characters. For example, [0-9]+ matches one or more digits in a row.

Common Regex Examples

Real-world patterns can get much more elaborate: a “fully correct” email-matching regex, for instance, is notoriously long and still doesn’t perfectly cover every technically valid address. For everyday validation, a simpler pattern combined with an actual confirmation step, like sending a verification email, is usually more reliable than chasing a perfect regex. Regex is often combined with other data-handling tasks, such as validating a value before storing it in What Is JSON?, or matching a specific pattern within a URL: see What Is URL Encoding? if you’re working with URLs specifically.

Regex Flags

Flags change how a pattern is applied, without changing the pattern itself. The exact names vary by language, but three are especially common:

• Global: find all matches in the text, not just the first one.
• Case insensitive: treat uppercase and lowercase letters as equivalent.
• Multiline: make ^ and $ match the start and end of each line, rather than only the start and end of the whole text.

In JavaScript, for example, these are written as g, i, and m after the pattern. Other languages expose the same ideas through differently named options or constants.

Common Regex Mistakes

• Forgetting to escape special characters. Characters like ., *, and ? have special meaning in regex. To match them literally, they usually need a backslash in front, like \.
• Making patterns too broad. A pattern like .* matches almost anything, which can accidentally match far more text than intended.
• Making patterns too complex. A dense, unreadable pattern is hard to maintain and easy to get subtly wrong. Breaking a problem into smaller patterns keeps regex manageable.
• Assuming regex behaves identically everywhere. Small details, such as how ^ and $ behave, what counts as a “word character,” or how flags are named, can differ between programming languages and regex engines. Always test a pattern in the actual environment it will run in.

Testing Regular Expressions

The best way to learn regex is to experiment with real patterns against real text. The Regex Tester lets you try a pattern against sample text and see exactly what it matches, without writing any code. Once you’re comfortable with patterns, tools like Find and Replace Text and Duplicate Line Remover put that pattern matching to practical use.