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from __future__ import annotations
from datetime import datetime
from typing import Any, Callable, Literal
from . import DataType, MemoryPool, Scalar, _PandasConvertible
class Expression: ...
class ScalarAggregateOptions: ...
class CastOptions:
def __init__(
self,
target_type: DataType | None = None,
allow_int_overflow: bool | None = None,
allow_time_truncate: bool | None = None,
allow_time_overflow: bool | None = None,
allow_decimal_truncate: bool | None = None,
allow_float_truncate: bool | None = None,
allow_invalid_utf8: bool | None = None,
) -> None: ...
def max( # noqa: A001
array: _PandasConvertible,
/,
*,
skip_nulls: bool = True,
min_count: int = 1,
options: ScalarAggregateOptions | None = None,
memory_pool: MemoryPool | None = None,
) -> Scalar: ...
def min( # noqa: A001
array: _PandasConvertible,
/,
*,
skip_nulls: bool = True,
min_count: int = 1,
options: ScalarAggregateOptions | None = None,
memory_pool: MemoryPool | None = None,
) -> Scalar: ...
def utf8_length(
strings: _PandasConvertible, /, *, memory_pool: MemoryPool | None = None
) -> _PandasConvertible: ...
def register_scalar_function(
func: Callable,
function_name: str,
function_doc: dict[Literal["summary", "description"], str],
in_types: dict[str, DataType],
out_type: DataType,
func_registry: Any | None = None,
) -> None: ...
def call_function(
function_name: str, target: list[_PandasConvertible]
) -> _PandasConvertible: ...
def assume_timezone(
timestamps: _PandasConvertible | Scalar | datetime,
/,
timezone: str,
*,
ambiguous: Literal["raise", "earliest", "latest"] = "raise",
nonexistent: Literal["raise", "earliest", "latest"] = "raise",
options: Any | None = None,
memory_pool: MemoryPool | None = None,
) -> _PandasConvertible: ...
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