8a3b1cd811
The following code should type-check:
```python3
import uuid
import pyspark.sql.functions as F
my_udf = F.udf(lambda: str(uuid.uuid4())).asNondeterministic()
```
### What changes were proposed in this pull request?
The `udf` function should return a more specific type.
### Why are the changes needed?
Right now, `mypy` will throw spurious errors, such as for the code given above.
### Does this PR introduce _any_ user-facing change?
No
### How was this patch tested?
This was not tested. Sorry, I am not very familiar with this repo -- are there any typing tests?
Closes #33399 from luranhe/patch-1.
Lead-authored-by: Luran He <luranjhe@gmail.com>
Co-authored-by: Luran He <luran.he@compass.com>
Signed-off-by: zero323 <mszymkiewicz@gmail.com>
(cherry picked from commit ede1bc6b51)
Signed-off-by: zero323 <mszymkiewicz@gmail.com>
64 lines
2 KiB
Python
64 lines
2 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 (
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Any,
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Callable,
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List,
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Optional,
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Tuple,
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TypeVar,
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Union,
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)
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from typing_extensions import Protocol
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import datetime
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import decimal
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from pyspark._typing import PrimitiveType
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import pyspark.sql.types
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from pyspark.sql.column import Column
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ColumnOrName = Union[Column, str]
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DecimalLiteral = decimal.Decimal
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DateTimeLiteral = Union[datetime.datetime, datetime.date]
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LiteralType = PrimitiveType
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AtomicDataTypeOrString = Union[pyspark.sql.types.AtomicType, str]
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DataTypeOrString = Union[pyspark.sql.types.DataType, str]
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OptionalPrimitiveType = Optional[PrimitiveType]
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RowLike = TypeVar("RowLike", List[Any], Tuple[Any, ...], pyspark.sql.types.Row)
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class SupportsOpen(Protocol):
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def open(self, partition_id: int, epoch_id: int) -> bool: ...
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class SupportsProcess(Protocol):
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def process(self, row: pyspark.sql.types.Row) -> None: ...
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class SupportsClose(Protocol):
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def close(self, error: Exception) -> None: ...
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class UserDefinedFunctionLike(Protocol):
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func: Callable[..., Any]
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evalType: int
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deterministic: bool
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@property
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def returnType(self) -> pyspark.sql.types.DataType: ...
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def __call__(self, *args: ColumnOrName) -> Column: ...
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def asNondeterministic(self) -> UserDefinedFunctionLike: ...
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