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 {}