Regular Expressions, Hands-On

Tutorial · Programming

A regular expression looks like noise until you learn it piece by piece — each symbol does exactly one small job, and patterns are just those small jobs combined.

Literals and character classes

/cat/         matches the literal text "cat"
/[aeiou]/     matches any single vowel
/[^0-9]/      matches any character that is NOT a digit
/[a-z]/       matches any lowercase letter

Square brackets define a set of characters to match at that one position — a caret ^ inside brackets negates the set.

Shorthand classes

\d   any digit         (same as [0-9])
\w   any word character (letters, digits, underscore)
\s   any whitespace
.    any character at all (except newline, by default)

Quantifiers: how many times

a+     one or more "a"
a*     zero or more "a"
a?     zero or one "a"
a{2,4} between 2 and 4 "a"s

A phone number pattern makes this concrete: /^\d{3}-\d{3}-\d{4}$/ matches exactly "123-456-7890" — three digits, a dash, three digits, a dash, four digits, start to end.

Groups and capturing

const match = '2026-09-30'.match(/(\d{4})-(\d{2})-(\d{2})/)
// match[1] = '2026', match[2] = '09', match[3] = '30'

Parentheses create a capture group — beyond just matching, they let you pull specific pieces out of the matched text by index.

A real, practical example: validating an email

const emailPattern = /^[\w.-]+@[\w-]+\.[a-zA-Z]{2,}$/
emailPattern.test('user@example.com')  // true
emailPattern.test('not-an-email')      // false

Reading it piece by piece: one or more word characters, dots, or dashes; an @; a domain name; a dot; a top-level domain of at least two letters. No single email regex is fully RFC-compliant, but this covers the overwhelming majority of real addresses.