Regular expression matching

Find all occurrences of a pattern in a text and retain detailed match information.

Scanning logs for error codes; extracting all dates from a document; validating user input against a regex.

Python scripts that use the re module for text processing, data cleaning, or parsing.

list(re.finditer(pattern, string))

list(re.finditer(..., ...))

pattern: str (regex pattern), string: str (target string)

• re.search
• re.findall
• match.group
• match.start
• match.end

• re.findall for substrings
• iterating over re.finditer directly without list
• pre‑compiling the pattern with re.compile

Treating the result as a list of strings; assuming overlapping matches are returned; forgetting to handle an empty list.

re.findall returns a list of matched strings; re.finditer returns an iterator of match objects for lazy processing.

Coming from JavaScript where String.match returns an array of strings or null, expecting similar behavior from Python’s re.finditer.

• re.finditer
• re.findall
• re.search
• re.match

Materializing all matches with list() can be memory‑heavy for large inputs; consider iterating directly. The pattern is recompiled each call; reuse re.compile for performance.

Enables collection of all match objects for further inspection, such as extracting groups or positions, enabling detailed pattern analysis.

Think of dragging a fine net through a stream to capture every fish that matches the pattern.

Note that re.finditer does not return overlapping matches; to find overlapping matches use a lookahead pattern such as "(?=(sub))".

Using re.finditer directly for lazy iteration when only sequential processing is needed.