plugins/spark_upgrade/calculator_signature_change.py (47 lines of code) (raw):

# Copyright (c) 2023 Uber Technologies, Inc. # <p>Licensed 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 # <p>http://www.apache.org/licenses/LICENSE-2.0 # <p>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. from typing import Any, List, Dict from execute_piranha import ExecutePiranha from polyglot_piranha import ( Rule, ) class CalculatorSignatureChange(ExecutePiranha): def __init__(self, paths_to_codebase: List[str]): super().__init__( paths_to_codebase=paths_to_codebase, substitutions={ "entropy_calculator": "EntropyCalculator", "gini_calculator": "GiniCalculator", "variance_calculator": "VarianceCalculator", }, language="scala", ) def step_name(self) -> str: return "Calculator Signature Change" def get_rules(self) -> List[Rule]: # Rule to transform EntropyCalculator() arguments transform_EntropyCalculator_args = Rule( name="transform_EntropyCalculator_args", query="cs EntropyCalculator(:[stats])", replace_node="*", replace="EntropyCalculator(:[stats], :[stats].sum.toLong)", holes={"entropy_calculator"}, ) # Rule to transform GiniCalculator() arguments transform_GiniCalculator_args = Rule( name="transform_GiniCalculator_args", query="cs GiniCalculator(:[stats])", replace_node="*", replace="GiniCalculator(:[stats], :[stats].sum.toLong)", holes={"gini_calculator"}, ) transform_VarianceCalculator_args = Rule( name="transform_VarianceCalculator_args", query="cs VarianceCalculator(:[stats])", replace_node="*", replace="VarianceCalculator(:[stats], :[stats].sum.toLong)", holes={"variance_calculator"}, ) return [ transform_VarianceCalculator_args, transform_GiniCalculator_args, transform_EntropyCalculator_args, ] def summaries_to_custom_dict(self, _) -> Dict[str, Any]: return {}