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docs: document regular expression function arguments #1684

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23 changes: 23 additions & 0 deletions python/datafusion/functions/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1761,6 +1761,11 @@ def regexp_like(
Tests a string using a regular expression returning true if at least one match,
false otherwise.

Args:
string: Data to test against the regular expression.
regex: Regular expression to search for.
flags: Optional regular expression flags to control regex behavior.

Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello123"]})
Expand Down Expand Up @@ -1797,6 +1802,11 @@ def regexp_match(
Returns an array with each element containing the leftmost-first match of the
corresponding index in ``regex`` to string in ``string``.

Args:
string: Data to match against the regular expression.
regex: Regular expression to search for.
flags: Optional regular expression flags to control regex behavior.

Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello 42 world"]})
Expand Down Expand Up @@ -1839,6 +1849,13 @@ def regexp_replace(
Supported flags with the addition of 'g' can be found at
<https://docs.rs/regex/latest/regex/#grouping-and-flags>

Args:
string: Data to search for the regular expression match.
pattern: Regular expression to search for.
replacement: Text substituted for each match.
flags: Optional regular expression flags to control regex behavior. Add
``g`` to replace every match rather than only the first.

Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["hello 42"]})
Expand Down Expand Up @@ -1885,6 +1902,12 @@ def regexp_count(
Optional start position (the first position is 1) to search for the regular
expression.

Args:
string: Data to search for the regular expression match.
pattern: Regular expression to search for.
start: Optional position to start the search (the first position is 1).
flags: Optional regular expression flags to control regex behavior.

Examples:
>>> ctx = dfn.SessionContext()
>>> df = ctx.from_pydict({"a": ["abcabc"]})
Expand Down