cloud-fan commented on code in PR #39068:
URL: https://github.com/apache/spark/pull/39068#discussion_r1051941366
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python/pyspark/sql/connect/functions.py:
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@@ -80,6 +84,78 @@ def _invoke_binary_math_function(name: str, col1: Any, col2:
Any) -> Column:
return _invoke_function(name, *_cols)
+def _get_lambda_parameters(f: Callable) -> ValuesView[inspect.Parameter]:
+ signature = inspect.signature(f)
+ parameters = signature.parameters.values()
+
+ # We should exclude functions that use, variable args and keyword argument
+ # names, as well as keyword only args.
+ supported_parameter_types = {
+ inspect.Parameter.POSITIONAL_OR_KEYWORD,
+ inspect.Parameter.POSITIONAL_ONLY,
+ }
+
+ # Validate that the function arity is between 1 and 3.
+ if not (1 <= len(parameters) <= 3):
+ raise ValueError(
+ "f should take between 1 and 3 arguments, but provided function
takes {}".format(
+ len(parameters)
+ )
+ )
+
+ # Verify that all arguments can be used as positional arguments.
+ if not all(p.kind in supported_parameter_types for p in parameters):
+ raise ValueError("All arguments of f must be usable as POSITIONAL
arguments")
+
+ return parameters
+
+
+def _create_lambda(f: Callable) -> LambdaFunction:
+ """
+ Create `o.a.s.sql.expressions.LambdaFunction` corresponding
+ to transformation described by f
+
+ :param f: A Python of one of the following forms:
+ - (Column) -> Column: ...
+ - (Column, Column) -> Column: ...
+ - (Column, Column, Column) -> Column: ...
+ """
+ parameters = _get_lambda_parameters(f)
+
+ arg_names = ["x", "y", "z"]
+ arg_cols = [column(arg) for arg in arg_names[: len(parameters)]]
+
+ result = f(*arg_cols)
+
+ if not isinstance(result, Column):
+ raise ValueError(f"Callable {f} should return Column, got
{type(result)}")
+
+ return LambdaFunction(result._expr, [arg_col._expr for arg_col in
arg_cols])
+
+
+def _invoke_higher_order_function(
+ name: str,
+ cols: List["ColumnOrName"],
+ funs: List[Callable],
+) -> Column:
+ """
+ Invokes expression identified by name,
+ (relative to ```org.apache.spark.sql.catalyst.expressions``)
+ and wraps the result with Column (first Scala one, then Python).
+
+ :param name: Name of the expression
+ :param cols: a list of columns
+ :param funs: a list of((*Column) -> Column functions.
+
+ :return: a Column
+ """
+ assert len(funs) == 1
+ _cols = [_to_col(c) for c in cols]
+ _funs = [_create_lambda(f) for f in funs]
+
+ return _invoke_function(name, *_cols, *_funs)
Review Comment:
This looks like a hacky way to create lambda function...
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