CTCC1 commented on code in PR #46045: URL: https://github.com/apache/spark/pull/46045#discussion_r1566772319
########## python/pyspark/sql/connect/functions/builtin.py: ########## @@ -2476,8 +2476,26 @@ def repeat(col: "ColumnOrName", n: Union["ColumnOrName", int]) -> Column: repeat.__doc__ = pysparkfuncs.repeat.__doc__ -def split(str: "ColumnOrName", pattern: str, limit: int = -1) -> Column: - return _invoke_function("split", _to_col(str), lit(pattern), lit(limit)) +def split( + str: "ColumnOrName", + pattern: Union[Column, str], + limit: Union["ColumnOrName", int] = -1, +) -> Column: + # work around shadowing of str in the input variable name + from builtins import str as py_str + + if isinstance(pattern, py_str): + _pattern = lit(pattern) + elif isinstance(pattern, Column): + _pattern = pattern + else: + raise PySparkTypeError( + error_class="NOT_COLUMN_OR_STR", + message_parameters={"arg_name": "pattern", "arg_type": type(pattern).__name__}, + ) + + limit = lit(limit) if isinstance(limit, int) else _to_col(limit) + return _invoke_function("split", _to_col(str), _pattern, limit) Review Comment: Thanks for the suggestion, this is simpler for sure! The only concern is that we will not raise `PySparkTypeError` if `pattern` is passed in for a type other than `Column` or `str`, and it will form a UnresolvedFunction. Is raising such error early a requirement for connect? -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org --------------------------------------------------------------------- To unsubscribe, e-mail: reviews-unsubscr...@spark.apache.org For additional commands, e-mail: reviews-h...@spark.apache.org