Master Python’s re Module: Essential Regex Functions and Patterns

re module

The Python re module provides regular‑expression operations for pattern matching and text manipulation.

re.search

Typical usage: match = re.search(pat, str). Since a match may not be found, it is common to wrap re.search() in an if statement.

re.match

re.match

is similar to re.search but attempts to match only at the beginning of the string.

Common Regex Characters

a, X, 9 match themselves; meta‑characters such as . ^ $ * + ? { } [ ] \ | ( ) have special meanings.

. matches any character except a newline.

\w matches word characters [a‑zA‑Z0‑9_].

\W matches non‑word characters.

\b matches a word boundary.

\s matches a whitespace character (space, newline, tab, return, form‑feed).

\S matches a non‑whitespace character.

\t, \n, \r match tab, newline, and carriage return respectively.

\d matches a digit [0‑9].

^ matches the start of a string.

$ matches the end of a string.

Quantifiers

‘+’ means one or more times, ‘*’ means zero or more times, ‘?’ means zero or one time.

Square Brackets []

Square brackets define a set of characters, acting like an OR: [abc] matches ‘a’, ‘b’ or ‘c’.

Group Extraction with Parentheses ()

Parentheses create capture groups. For example, the pattern r'([\w.-]+)@([\w.-]+)' captures the username and hostname of an email address; after a successful match you can retrieve them with match.group(1) and match.group(2) while match.group() returns the entire match.

findall and Groups

When () is combined with findall(), the function returns a list of tuples containing the captured groups.

re.sub

re.sub(pat, replacement, str)

searches str for substrings matching pat and replaces them with replacement. The replacement string can include backreferences like \1 or \2 to insert captured groups, enabling selective substitution.