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__init__.py
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119 lines (96 loc) · 2.79 KB
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# 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.
from abc import ABCMeta, abstractmethod
from typing import List
try:
import importlib.metadata as importlib_metadata
except ImportError:
import importlib_metadata
import pyarrow as pa
from ._internal import (
AggregateUDF,
Config,
DataFrame,
SessionContext,
Expression,
ScalarUDF,
)
__version__ = importlib_metadata.version(__name__)
__all__ = [
"Config",
"DataFrame",
"SessionContext",
"Expression",
"AggregateUDF",
"ScalarUDF",
"column",
"literal",
]
class Accumulator(metaclass=ABCMeta):
@abstractmethod
def state(self) -> List[pa.Scalar]:
pass
@abstractmethod
def update(self, values: pa.Array) -> None:
pass
@abstractmethod
def merge(self, states: pa.Array) -> None:
pass
@abstractmethod
def evaluate(self) -> pa.Scalar:
pass
def column(value):
return Expression.column(value)
col = column
def literal(value):
if not isinstance(value, pa.Scalar):
value = pa.scalar(value)
return Expression.literal(value)
lit = literal
def udf(func, input_types, return_type, volatility, name=None):
"""
Create a new User Defined Function
"""
if not callable(func):
raise TypeError("`func` argument must be callable")
if name is None:
name = func.__qualname__
return ScalarUDF(
name=name,
func=func,
input_types=input_types,
return_type=return_type,
volatility=volatility,
)
def udaf(accum, input_type, return_type, state_type, volatility, name=None):
"""
Create a new User Defined Aggregate Function
"""
if not issubclass(accum, Accumulator):
raise TypeError(
"`accum` must implement the abstract base class Accumulator"
)
if name is None:
name = accum.__qualname__
return AggregateUDF(
name=name,
accumulator=accum,
input_type=input_type,
return_type=return_type,
state_type=state_type,
volatility=volatility,
)