665817bd4f
### What changes were proposed in this pull request? This pull request: - Adds following flags to the main mypy configuration: - [`strict_optional`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-strict_optional) - [`no_implicit_optional`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-no_implicit_optional) - [`disallow_untyped_defs`](https://mypy.readthedocs.io/en/stable/config_file.html#confval-disallow_untyped_calls) These flags are enabled only for public API and disabled for tests and internal modules. Additionally, these PR fixes missing annotations. ### Why are the changes needed? Primary reason to propose this changes is to use standard configuration as used by typeshed project. This will allow us to be more strict, especially when interacting with JVM code. See for example https://github.com/apache/spark/pull/29122#pullrequestreview-513112882 Additionally, it will allow us to detect cases where annotations have unintentionally omitted. ### Does this PR introduce _any_ user-facing change? Annotations only. ### How was this patch tested? `dev/lint-python`. Closes #30382 from zero323/SPARK-33457. Authored-by: zero323 <mszymkiewicz@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
132 lines
4.6 KiB
Python
132 lines
4.6 KiB
Python
#
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# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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from typing import overload
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from typing import Any, Iterable, List, Optional, Tuple, Type, TypeVar, Union
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from types import TracebackType
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from py4j.java_gateway import JavaObject # type: ignore[import]
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from pyspark.sql._typing import DateTimeLiteral, LiteralType, DecimalLiteral, RowLike
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from pyspark.sql.pandas._typing import DataFrameLike
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from pyspark.conf import SparkConf
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from pyspark.context import SparkContext
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from pyspark.rdd import RDD
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from pyspark.sql.catalog import Catalog
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from pyspark.sql.conf import RuntimeConfig
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from pyspark.sql.dataframe import DataFrame
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from pyspark.sql.pandas.conversion import SparkConversionMixin
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from pyspark.sql.types import AtomicType, StructType
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from pyspark.sql.readwriter import DataFrameReader
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from pyspark.sql.streaming import DataStreamReader, StreamingQueryManager
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from pyspark.sql.udf import UDFRegistration
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T = TypeVar("T")
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class SparkSession(SparkConversionMixin):
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class Builder:
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@overload
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def config(self, *, conf: SparkConf) -> SparkSession.Builder: ...
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@overload
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def config(self, key: str, value: Any) -> SparkSession.Builder: ...
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def master(self, master: str) -> SparkSession.Builder: ...
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def appName(self, name: str) -> SparkSession.Builder: ...
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def enableHiveSupport(self) -> SparkSession.Builder: ...
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def getOrCreate(self) -> SparkSession: ...
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builder: SparkSession.Builder
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def __init__(
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self, sparkContext: SparkContext, jsparkSession: Optional[JavaObject] = ...
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) -> None: ...
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def newSession(self) -> SparkSession: ...
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@classmethod
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def getActiveSession(cls) -> SparkSession: ...
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@property
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def sparkContext(self) -> SparkContext: ...
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@property
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def version(self) -> str: ...
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@property
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def conf(self) -> RuntimeConfig: ...
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@property
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def catalog(self) -> Catalog: ...
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@property
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def udf(self) -> UDFRegistration: ...
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def range(
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self,
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start: int,
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end: Optional[int] = ...,
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step: int = ...,
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numPartitions: Optional[int] = ...,
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) -> DataFrame: ...
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@overload
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def createDataFrame(
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self,
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data: Union[RDD[RowLike], Iterable[RowLike]],
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samplingRatio: Optional[float] = ...,
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) -> DataFrame: ...
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@overload
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def createDataFrame(
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self,
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data: Union[RDD[RowLike], Iterable[RowLike]],
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schema: Union[List[str], Tuple[str, ...]] = ...,
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verifySchema: bool = ...,
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) -> DataFrame: ...
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@overload
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def createDataFrame(
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self,
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data: Union[
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RDD[Union[DateTimeLiteral, LiteralType, DecimalLiteral]],
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Iterable[Union[DateTimeLiteral, LiteralType, DecimalLiteral]],
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],
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schema: Union[AtomicType, str],
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verifySchema: bool = ...,
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) -> DataFrame: ...
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@overload
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def createDataFrame(
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self,
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data: Union[RDD[RowLike], Iterable[RowLike]],
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schema: Union[StructType, str],
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verifySchema: bool = ...,
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) -> DataFrame: ...
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@overload
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def createDataFrame(
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self, data: DataFrameLike, samplingRatio: Optional[float] = ...
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) -> DataFrame: ...
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@overload
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def createDataFrame(
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self,
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data: DataFrameLike,
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schema: Union[StructType, str],
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verifySchema: bool = ...,
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) -> DataFrame: ...
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def sql(self, sqlQuery: str) -> DataFrame: ...
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def table(self, tableName: str) -> DataFrame: ...
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@property
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def read(self) -> DataFrameReader: ...
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@property
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def readStream(self) -> DataStreamReader: ...
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@property
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def streams(self) -> StreamingQueryManager: ...
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def stop(self) -> None: ...
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def __enter__(self) -> SparkSession: ...
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def __exit__(
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self,
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exc_type: Optional[Type[BaseException]],
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exc_val: Optional[BaseException],
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exc_tb: Optional[TracebackType],
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) -> None: ...
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