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\d+, [a-z], (abc)).g, i, m) for global, case-insensitive, and multiline behavior.Regular expressions (regex) define search patterns for strings and are essential in data extraction, validation, and transformation. They are supported across various languages such as Python, JavaScript, PHP, and tools like grep or text editors. A well-structured regex allows developers to search, locate, extract, and manipulate specific string patterns efficiently.
Regex engines use finite automata to parse and match patterns:
Input String → Regex Engine → State Machine → Matches/Groups/FailuresPattern syntax includes quantifiers, anchors, character classes, and assertions:
\d+: Matches one or more digits[^a-z]: Matches any character except lowercase letters^, $: Anchors for line start/end(abc): Capturing groups(?=abc): Positive lookahead(...) to extract substrings, then reference them with backreferences \1, \2, etc., in replacements..* may match even blank lines due to greediness.foo(?=bar) match "foo" only if followed by "bar" but don't consume "bar".m flag to make ^ and $ operate per line, not entire input.u mode to match characters beyond ASCII reliably.A data engineer uses the pattern \(\d{3}\) \d{3}-\d{4} to extract numbers like (555) 123-4567. By testing this in the tool, they identify edge cases like varying whitespace or dashes and adjust accordingly.
A developer validating email addresses starts with ^[\w.-]+@[\w.-]+\.\w+$. Using sample test inputs, they realize subdomains like user@mail.co.uk aren't matched and refine their pattern to be more inclusive.
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| Pattern | Sample Text | Result |
|---|---|---|
\d+ | abc123def456 | 123, 456 |
[a-z]+ | ABC123def456 | def |
^Hello | Hello world | Hello |
\bword\b | A word in a sentence. | word |
(\w+)@(\w+).com | user@example.com | user@example.com (Groups: user, example) |
.* | (Empty match) | |
foo(?=bar) | foobar | foo |
^.+$ with m flag | line1\nline2 | line1, line2 |