vibhatha commented on code in PR #12590: URL: https://github.com/apache/arrow/pull/12590#discussion_r859899992
########## python/pyarrow/tests/test_udf.py: ########## @@ -0,0 +1,502 @@ +# Licensed to the Apache Software Foundation (ASF) under one +# or more contributor license agreements. See the NOTICE file +# distributed with this work for additional information +# regarding copyright ownership. The ASF licenses this file +# to you under the Apache License, Version 2.0 (the +# "License"); you may not use this file except in compliance +# with the License. You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, +# software distributed under the License is distributed on an +# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY +# KIND, either express or implied. See the License for the +# specific language governing permissions and limitations +# under the License. + + +import pytest + +import pyarrow as pa +from pyarrow import compute as pc + +# UDFs are all tested with a dataset scan +pytestmark = pytest.mark.dataset + + +try: + import pyarrow.dataset as ds +except ImportError: + ds = None + +global_batch_length = 10 + + +def mock_udf_context(batch_length=global_batch_length): + from pyarrow._compute import _get_scalar_udf_context + return _get_scalar_udf_context(pa.default_memory_pool(), batch_length) + + [email protected](scope="session") +def unary_func_fixture(): + def unary_function(ctx, scalar1): + return pc.call_function("add", [scalar1, 1]) + func_name = "y=x+k" + unary_doc = {"summary": "add function", + "description": "test add function"} + pc.register_scalar_function(unary_function, + func_name, + unary_doc, + {"array": pa.int64()}, + pa.int64()) + return unary_function, func_name + + [email protected](scope="session") +def binary_func_fixture(): + def binary_function(ctx, m, x): + return pc.call_function("multiply", [m, x]) + func_name = "y=mx" + binary_doc = {"summary": "y=mx", + "description": "find y from y = mx"} + pc.register_scalar_function(binary_function, + func_name, + binary_doc, + {"m": pa.int64(), + "x": pa.int64(), + }, + pa.int64()) + return binary_function, func_name + + [email protected](scope="session") +def ternary_func_fixture(): + def ternary_function(ctx, m, x, c): + mx = pc.call_function("multiply", [m, x]) + return pc.call_function("add", [mx, c]) + ternary_doc = {"summary": "y=mx+c", + "description": "find y from y = mx + c"} + func_name = "y=mx+c" + pc.register_scalar_function(ternary_function, + func_name, + ternary_doc, + { + "array1": pa.int64(), + "array2": pa.int64(), + "array3": pa.int64(), + }, + pa.int64()) + return ternary_function, func_name + + [email protected](scope="session") +def varargs_func_fixture(): + def varargs_function(ctx, *values): + base_val = values[:2] + res = pc.call_function("add", base_val) + for other_val in values[2:]: + res = pc.call_function("add", [res, other_val]) + return res + func_name = "z=ax+by+c" + varargs_doc = {"summary": "z=ax+by+c", + "description": "find z from z = ax + by + c" + } + pc.register_scalar_function(varargs_function, + func_name, + varargs_doc, + { + "array1": pa.int64(), + "array2": pa.int64(), + "array3": pa.int64(), + "array4": pa.int64(), + "array5": pa.int64(), + }, + pa.int64()) + return varargs_function, func_name + + [email protected](scope="session") +def random_with_udf_ctx_func_fixture(): + def random_with_udf_ctx(context, one, two): + proxy_pool = pa.proxy_memory_pool(context.memory_pool) + ans = pc.add(one, two, memory_pool=proxy_pool) + res = pa.array([ans.as_py()], memory_pool=proxy_pool) + return res + in_types = {"one": pa.int64(), + "two": pa.int64(), + } + func_doc = { + "summary": "test udf context", + "description": "udf context test" + } + func_name = "test_udf_context" + pc.register_scalar_function(random_with_udf_ctx, + func_name, func_doc, + in_types, + pa.int64()) + return random_with_udf_ctx, func_name + + [email protected](scope="session") +def output_check_func_fixture(): + # The objective of this fixture is to evaluate, + # how the UDF interface respond to unexpected + # output types. The types chosen at the test + # end are either of different Arrow data type + # or non-Arrow type. + def output_check(ctx, array): + ar = pc.call_function("add", [array, 1]) + ar = ar.cast(pa.int32()) + return ar + func_name = "test_output_value" + in_types = {"array": pa.int64()} + out_type = pa.int64() + doc = { + "summary": "add function scalar", + "description": "add function" + } + pc.register_scalar_function(output_check, func_name, doc, + in_types, out_type) + return output_check, func_name + + [email protected](scope="session") +def nullary_check_func_fixture(): + # this needs to return array values + def nullary_check(context): + return pa.array([42] * context.batch_length, type=pa.int64(), + memory_pool=context.memory_pool) + + func_doc = { + "summary": "random function", + "description": "generates a random value" + } + func_name = "test_random_func" + pc.register_scalar_function(nullary_check, + func_name, + func_doc, + {}, + pa.int64()) + + return nullary_check, func_name + + +def add_const(ctx, scalar): Review Comment: Ah yes. -- This is an automated message from the Apache Git Service. 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