31a16fbb40
### What changes were proposed in this pull request? This PR proposes migration of [`pyspark-stubs`](https://github.com/zero323/pyspark-stubs) into Spark codebase. ### Why are the changes needed? ### Does this PR introduce _any_ user-facing change? Yes. This PR adds type annotations directly to Spark source. This can impact interaction with development tools for users, which haven't used `pyspark-stubs`. ### How was this patch tested? - [x] MyPy tests of the PySpark source ``` mypy --no-incremental --config python/mypy.ini python/pyspark ``` - [x] MyPy tests of Spark examples ``` MYPYPATH=python/ mypy --no-incremental --config python/mypy.ini examples/src/main/python/ml examples/src/main/python/sql examples/src/main/python/sql/streaming ``` - [x] Existing Flake8 linter - [x] Existing unit tests Tested against: - `mypy==0.790+dev.e959952d9001e9713d329a2f9b196705b028f894` - `mypy==0.782` Closes #29591 from zero323/SPARK-32681. Authored-by: zero323 <mszymkiewicz@gmail.com> Signed-off-by: HyukjinKwon <gurwls223@apache.org>
74 lines
3.1 KiB
Python
74 lines
3.1 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 pyspark import shuffle as shuffle
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from pyspark.broadcast import Broadcast as Broadcast
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from pyspark.files import SparkFiles as SparkFiles
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from pyspark.java_gateway import local_connect_and_auth as local_connect_and_auth
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from pyspark.rdd import PythonEvalType as PythonEvalType
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from pyspark.resource import ResourceInformation as ResourceInformation
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from pyspark.serializers import (
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BatchedSerializer as BatchedSerializer,
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PickleSerializer as PickleSerializer,
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SpecialLengths as SpecialLengths,
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UTF8Deserializer as UTF8Deserializer,
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read_bool as read_bool,
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read_int as read_int,
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read_long as read_long,
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write_int as write_int,
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write_long as write_long,
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write_with_length as write_with_length,
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)
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from pyspark.sql.pandas.serializers import (
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ArrowStreamPandasUDFSerializer as ArrowStreamPandasUDFSerializer,
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CogroupUDFSerializer as CogroupUDFSerializer,
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)
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from pyspark.sql.pandas.types import to_arrow_type as to_arrow_type
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from pyspark.sql.types import StructType as StructType
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from pyspark.taskcontext import (
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BarrierTaskContext as BarrierTaskContext,
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TaskContext as TaskContext,
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)
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from pyspark.util import fail_on_stopiteration as fail_on_stopiteration
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from typing import Any
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has_resource_module: bool
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pickleSer: Any
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utf8_deserializer: Any
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def report_times(outfile: Any, boot: Any, init: Any, finish: Any) -> None: ...
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def add_path(path: Any) -> None: ...
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def read_command(serializer: Any, file: Any): ...
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def chain(f: Any, g: Any): ...
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def wrap_udf(f: Any, return_type: Any): ...
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def wrap_scalar_pandas_udf(f: Any, return_type: Any): ...
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def wrap_pandas_iter_udf(f: Any, return_type: Any): ...
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def wrap_cogrouped_map_pandas_udf(f: Any, return_type: Any, argspec: Any): ...
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def wrap_grouped_map_pandas_udf(f: Any, return_type: Any, argspec: Any): ...
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def wrap_grouped_agg_pandas_udf(f: Any, return_type: Any): ...
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def wrap_window_agg_pandas_udf(
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f: Any, return_type: Any, runner_conf: Any, udf_index: Any
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): ...
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def wrap_unbounded_window_agg_pandas_udf(f: Any, return_type: Any): ...
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def wrap_bounded_window_agg_pandas_udf(f: Any, return_type: Any): ...
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def read_single_udf(
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pickleSer: Any, infile: Any, eval_type: Any, runner_conf: Any, udf_index: Any
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): ...
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def read_udfs(pickleSer: Any, infile: Any, eval_type: Any): ...
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def main(infile: Any, outfile: Any) -> None: ...
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