icexelloss commented on code in PR #35514:
URL: https://github.com/apache/arrow/pull/35514#discussion_r1195548097
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python/pyarrow/_compute.pyx:
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@@ -2743,6 +2749,84 @@ def register_scalar_function(func, function_name,
function_doc, in_types, out_ty
out_type, func_registry)
+def register_aggregate_function(func, function_name, function_doc, in_types,
out_type,
+ func_registry=None):
+ """
+ Register a user-defined scalar function.
+
+ A scalar function is a function that executes elementwise
+ operations on arrays or scalars, i.e. a scalar function must
+ be computed row-by-row with no state where each output row
+ is computed only from its corresponding input row.
+ In other words, all argument arrays have the same length,
+ and the output array is of the same length as the arguments.
+ Scalar functions are the only functions allowed in query engine
+ expressions.
+
+ Parameters
+ ----------
+ func : callable
+ A callable implementing the user-defined function.
+ The first argument is the context argument of type
+ ScalarUdfContext.
+ Then, it must take arguments equal to the number of
+ in_types defined. It must return an Array or Scalar
+ matching the out_type. It must return a Scalar if
+ all arguments are scalar, else it must return an Array.
+
+ To define a varargs function, pass a callable that takes
+ varargs. The last in_type will be the type of all varargs
+ arguments.
+ function_name : str
+ Name of the function. This name must be globally unique.
+ function_doc : dict
+ A dictionary object with keys "summary" (str),
+ and "description" (str).
+ in_types : Dict[str, DataType]
+ A dictionary mapping function argument names to
+ their respective DataType.
+ The argument names will be used to generate
+ documentation for the function. The number of
+ arguments specified here determines the function
+ arity.
+ out_type : DataType
+ Output type of the function.
+ func_registry : FunctionRegistry
+ Optional function registry to use instead of the default global one.
+
+ Examples
+ --------
+ >>> import pyarrow as pa
+ >>> import pyarrow.compute as pc
+ >>>
+ >>> func_doc = {}
+ >>> func_doc["summary"] = "simple udf"
+ >>> func_doc["description"] = "add a constant to a scalar"
+ >>>
+ >>> def add_constant(ctx, array):
+ ... return pc.add(array, 1, memory_pool=ctx.memory_pool)
+ >>>
+ >>> func_name = "py_add_func"
+ >>> in_types = {"array": pa.int64()}
+ >>> out_type = pa.int64()
+ >>> pc.register_scalar_function(add_constant, func_name, func_doc,
+ ... in_types, out_type)
+ >>>
+ >>> func = pc.get_function(func_name)
+ >>> func.name
+ 'py_add_func'
+ >>> answer = pc.call_function(func_name, [pa.array([20])])
+ >>> answer
+ <pyarrow.lib.Int64Array object at ...>
+ [
+ 21
+ ]
+ """
+ return _register_scalar_like_function(get_register_aggregate_function(),
Review Comment:
Rename this - "scalar like" is no longer accurate
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