Regular Expressions

You're cleaning a dataset and need every phone number in a document — some written 555-123-4567, others (555) 123-4567. String methods like .find() and .split() match exact text; regular expressions match patterns. Python's re module lets you describe the shape of the text you want, then search for it, extract it, validate it, or replace it.

The functions that matter

search, match, and fullmatch return a match object (truthy) or None — which is why if re.fullmatch(pattern, s): is the standard validation idiom.

Always write patterns as raw strings: r"\d+", never "\d+". In a normal string Python itself interprets backslashes, so "\b" becomes a backspace character before re ever sees the pattern. The r prefix hands your backslashes over intact.

The pattern language, condensed

\d  digit         \w  word char        \s  whitespace
[abc]  one of a, b, c                  [^@]  any char EXCEPT @
.   any single character (a LITERAL dot must be escaped: \.)
*   zero or more     +   one or more     ?   optional     {2,4}  two to four
^   start of string     $   end of string     (…)  capture group     a|b  either

Extract pieces with groups:

The traps

match is not fullmatch. re.match(r"\d+", "123abc") succeeds — it anchors the start but not the end. For validation ("is this WHOLE string an email?") use re.fullmatch, or you'll accept garbage suffixes.

. means any character. r"a.c" matches "abc" and "a@c" alike. A domain check written example.com happily accepts exampleXcom. Mean a real dot? Escape it: \..

* accepts empty. * is zero or more — [^@]* matches an empty string without complaint. When something must actually be present, that's + (one or more).

Greedy by default. .* grabs as much as possible, .*? as little as possible: re.findall(r"<.*>", "<a><b>") returns ['<a><b>'], while r"<.*?>" returns ['<a>', '<b>'].

The validation idiom for this lesson

Read it as: one-or-more non-@ characters, an @, one-or-more non-@ characters, a literal dot, one-or-more again — text before the @, and a dot somewhere after it.

Your exercise

The first input line is a count N; each of the next N lines is a candidate email. Print valid or invalid for each — lowercase, one per line, exact spelling; the grader compares stdout character-for-character. Valid means: text before the @, text after it, and a dot after the @. The mistake the grader will catch is using * instead of +: the pattern [^@]*@[^@]*\.[^@]* accepts an empty part before the @, so the hidden test's @missing.com slips through as valid when the expected answer is invalid. Use +, use re.fullmatch, and don't run the validation on the count line itself.