spark-instrumented-optimizer/python/pyspark/sql/pandas/conversion.pyi
zero323 31a16fbb40 [SPARK-32714][PYTHON] Initial pyspark-stubs port
### 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>
2020-09-24 14:15:36 +09:00

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Python

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from typing import overload
from typing import Optional, Union
from pyspark.sql.pandas._typing import DataFrameLike
from pyspark import since as since # noqa: F401
from pyspark.rdd import RDD # noqa: F401
import pyspark.sql.dataframe
from pyspark.sql.pandas.serializers import ( # noqa: F401
ArrowCollectSerializer as ArrowCollectSerializer,
)
from pyspark.sql.types import ( # noqa: F401
BooleanType as BooleanType,
ByteType as ByteType,
DataType as DataType,
DoubleType as DoubleType,
FloatType as FloatType,
IntegerType as IntegerType,
IntegralType as IntegralType,
LongType as LongType,
ShortType as ShortType,
StructType as StructType,
TimestampType as TimestampType,
)
from pyspark.traceback_utils import SCCallSiteSync as SCCallSiteSync # noqa: F401
class PandasConversionMixin:
def toPandas(self) -> DataFrameLike: ...
class SparkConversionMixin:
@overload
def createDataFrame(
self, data: DataFrameLike, samplingRatio: Optional[float] = ...
) -> pyspark.sql.dataframe.DataFrame: ...
@overload
def createDataFrame(
self,
data: DataFrameLike,
schema: Union[StructType, str],
verifySchema: bool = ...,
) -> pyspark.sql.dataframe.DataFrame: ...