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A regular expression (regex) is a pattern for finding, extracting, replacing, or splitting text. Start with literal characters, add special symbols only when the task needs them, and choose an API that matches whether you want a match anywhere, at the start, or across the entire input. The examples below name their flavor: Python’s re or JavaScript’s RegExp.
What regex does—and when to use it
Regex describes rules for sequences of characters. It is useful when the text you want varies in a predictable way, such as a run of digits or a date-shaped value. Python’s documentation describes regex as a small, specialized language embedded in Python for searching, modifying, and splitting strings. Python’s Regular Expression HOWTO
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For a fixed literal, an ordinary string method is often clearer. For structured formats such as HTML or XML, use a parser: nested markup is not reliably handled by a simple pattern. Regex is a tool for text patterns, not a universal replacement for string operations or parsing.
Start with literal text and character choices
Literal characters
Python re: the pattern r"cat" matches the consecutive characters “cat” anywhere in a string when used with re.search(). It does not match “act” or “cats” as an exact whole string, though it can match the “cat” substring inside “cats.”
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JavaScript RegExp: /cat/ likewise finds that sequence within a string when used with .test() or a matching method. The surrounding API determines how you retrieve matches.
One character from a set
Python re: r"[abc]" matches one character: “a,” “b,” or “c.” r"[0-9]" matches one digit in that range. Put a character class in a quantifier to match a run, as in r"[0-9]+".
JavaScript RegExp: /[abc]/ and /[0-9]+/ express the same basic choices and repetition. Shorthand classes such as d, w, and s can have flavor-specific details; check the engine when portability matters instead of assuming every language treats them identically. MDN: HTML input element
Use quantifiers to describe repetition
A quantifier applies to the token immediately before it. In these common forms, ? means zero or one, * means zero or more, and + means one or more. A bounded quantifier such as {2,4} means between two and four repetitions.
| Flavor and pattern | Meaning | Example match |
|---|---|---|
Python re: r"ab?c" |
“a,” optional “b,” then “c” | ac or abc |
JavaScript RegExp: /ab*c/ |
“a,” zero or more “b” characters, then “c” | ac, abc, or abbbc |
Python re: r"[0-9]{2,4}" |
Two to four digits | 42 or 2026 |
Quantifiers are usually greedy: they take as much matching text as possible while allowing the rest of the pattern to succeed. Learn that behavior when a pattern unexpectedly captures more than intended; for basic matching, first make sure the token being repeated is the one you mean.
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Find digits, then extract them
To find a run of digits inside a sentence, use r"[0-9]+" in Python or /[0-9]+/ in JavaScript. In “Order 583 is ready,” this finds “583.” A capture group uses parentheses to retain a portion of a match for extraction.
Python re: re.search(r"Order ([0-9]+)", text) finds the phrase and makes the digits available as group 1, for example with match.group(1). To collect every digit run instead, Python’s re.findall(r"[0-9]+", text) returns the matched strings. Google’s Python regular expressions tutorial
When writing Python patterns with backslashes, raw string literals such as r"d+" avoid confusion between Python’s string escaping and regex escaping. Raw strings are the usual choice for patterns, except for the simplest expressions. Python re reference
Use alternation and groups for small choices
The vertical bar means “or.” Python re: r"cat|dog" matches either term. JavaScript RegExp: /(cat|dog)/ also matches either; here the parentheses group the alternatives and capture the selected word. Grouping matters when alternatives are part of a larger pattern, for example r"(cat|dog)s?" in Python matches either word with an optional final “s.”
Use capturing parentheses when you need the matched portion later. If grouping is only for structure and the text need not be extracted, many engines provide non-capturing groups, but syntax and APIs vary; check the specific flavor before relying on it.
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Match a date-shaped string without claiming it is a real date
Python re: r"[0-9]{4}-[0-9]{2}-[0-9]{2}" matches a four-digit, two-digit, two-digit shape such as 2026-10-07. That pattern does not establish that the month exists or that the day is valid for that month. Parse the components and validate them as a calendar date when semantic correctness matters.
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Choose the right matching scope
Finding a substring, checking only the start, and requiring the whole input to match are different tasks. In Python, these distinctions are explicit in the API:
re.search(pattern, text)looks for a match anywhere.re.match(pattern, text)checks from the beginning of the string.re.fullmatch(pattern, text)succeeds only if the entire string matches.
For example, re.fullmatch(r"[0-9]{4}-[0-9]{2}-[0-9]{2}", value) requires the whole value to have the date-shaped form. For “find a date somewhere in a note,” use re.search() instead. Python’s HOWTO cautions against imitating a search by adding .* to the front; select the operation that states your intent. Python’s Regular Expression HOWTO
JavaScript RegExp: /^[0-9]{4}-[0-9]{2}-[0-9]{2}$/ uses ^ and $ to express a start-to-end check in common cases. Anchor behavior can interact with flags and line boundaries, so use a flavor’s documented API and semantics when exact whole-input validation is important. JavaScript also offers the ^ and $ anchors in patterns, but does not have Python’s fullmatch() method.
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Before depending on a pattern, try inputs it should accept and inputs it should reject. For a date-shaped pattern, test 2026-10-07 as a positive example, and 26-10-07 and 2026-1-7 as negatives. Then separately check whether a shape-valid value is semantically valid if that matters.
Python re: bool(re.fullmatch(r"[0-9]{4}-[0-9]{2}-[0-9]{2}", value)) makes the whole-string requirement explicit. JavaScript RegExp: test the analogous anchored expression with /^[0-9]{4}-[0-9]{2}-[0-9]{2}$/.test(value). Include boundaries and near-misses in tests, not just examples that match.
Case sensitivity, whitespace, and readability
Ignore letter case when appropriate
Case-insensitive matching is usually an option or flag rather than a different core pattern. Python re: re.search(r"cat", text, re.IGNORECASE) ignores case for this search. JavaScript RegExp: /cat/i uses the i flag. Case rules can depend on the engine and character set, so this is not a guarantee of identical behavior across all flavors.
Clean up repeated whitespace
Python re: re.sub(r"s+", " ", text) replaces each run of whitespace with one ordinary space. For a narrower, fixed operation such as replacing a known literal substring, str.replace() is often simpler than regex. If the exact scope includes tabs, newlines, or non-ASCII whitespace, verify the engine’s definition of s.
Make complex patterns readable
For a longer Python pattern, re.VERBOSE permits whitespace and comments in the expression, making its parts easier to inspect. Python re: re.compile(r"""[0-9]{4} # yearn- [0-9]{2} # monthn- [0-9]{2} # day""", re.VERBOSE) expresses the same date shape across lines. Verbose mode has syntax rules of its own; escape literal spaces or comment characters when they are intended as pattern content. Python’s Regular Expression HOWTO
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Use regex for a narrow line format, not an entire document
A regular expression can be useful for extracting fields from a known, consistent line. For example, a log line with a fixed prefix, bracketed date, and message can be matched with a pattern tailored to that exact format; capture the fields you need and test lines that differ in spacing or punctuation.
That is different from attempting to parse a complete HTML or XML document. Those formats can nest elements and include escaping and other structure that a short regex does not robustly model. Use a parser for markup and other structured data.
Email fields need more than a compact regex
A short email pattern may look convincing but should not be presented as a complete standards-compliant validator. Python’s re reference itself labels one email-style example a poor pattern. Python re reference
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Quick Recap
A quick decision guide
- Known literal text: use a string search or replacement method unless pattern features are genuinely useful.
- Variable text with a consistent shape: use regex, name the flavor, and test both matches and near-misses.
- Need only a substring: choose a search operation; for input beginning only, use a start match; for an exact format, require a whole-string match.
- Need a real date or other semantic value: parse and validate it after checking the character shape.
- Need nested or structured content: use the relevant parser instead of expanding a regex into an opaque rule.
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