import numpy as np from pandas._typing import npt from pandas import MultiIndex from pandas.core.arrays import ExtensionArray multiindex_nulls_shift: int class IndexEngine: over_size_threshold: bool def __init__(self, values: np.ndarray) -> None: ... def __contains__(self, val: object) -> bool: ... # -> int | slice | np.ndarray[bool] def get_loc(self, val: object) -> int | slice | np.ndarray: ... def sizeof(self, deep: bool = ...) -> int: ... def __sizeof__(self) -> int: ... @property def is_unique(self) -> bool: ... @property def is_monotonic_increasing(self) -> bool: ... @property def is_monotonic_decreasing(self) -> bool: ... @property def is_mapping_populated(self) -> bool: ... def clear_mapping(self): ... def get_indexer(self, values: np.ndarray) -> npt.NDArray[np.intp]: ... def get_indexer_non_unique( self, targets: np.ndarray, ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ... class MaskedIndexEngine(IndexEngine): def __init__(self, values: object) -> None: ... def get_indexer_non_unique( self, targets: object ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ... class Float64Engine(IndexEngine): ... class Float32Engine(IndexEngine): ... class Complex128Engine(IndexEngine): ... class Complex64Engine(IndexEngine): ... class Int64Engine(IndexEngine): ... class Int32Engine(IndexEngine): ... class Int16Engine(IndexEngine): ... class Int8Engine(IndexEngine): ... class UInt64Engine(IndexEngine): ... class UInt32Engine(IndexEngine): ... class UInt16Engine(IndexEngine): ... class UInt8Engine(IndexEngine): ... class ObjectEngine(IndexEngine): ... class DatetimeEngine(Int64Engine): ... class TimedeltaEngine(DatetimeEngine): ... class PeriodEngine(Int64Engine): ... class BoolEngine(UInt8Engine): ... class MaskedFloat64Engine(MaskedIndexEngine): ... class MaskedFloat32Engine(MaskedIndexEngine): ... class MaskedComplex128Engine(MaskedIndexEngine): ... class MaskedComplex64Engine(MaskedIndexEngine): ... class MaskedInt64Engine(MaskedIndexEngine): ... class MaskedInt32Engine(MaskedIndexEngine): ... class MaskedInt16Engine(MaskedIndexEngine): ... class MaskedInt8Engine(MaskedIndexEngine): ... class MaskedUInt64Engine(MaskedIndexEngine): ... class MaskedUInt32Engine(MaskedIndexEngine): ... class MaskedUInt16Engine(MaskedIndexEngine): ... class MaskedUInt8Engine(MaskedIndexEngine): ... class MaskedBoolEngine(MaskedUInt8Engine): ... class BaseMultiIndexCodesEngine: levels: list[np.ndarray] offsets: np.ndarray # ndarray[uint64_t, ndim=1] def __init__( self, levels: list[np.ndarray], # all entries hashable labels: list[np.ndarray], # all entries integer-dtyped offsets: np.ndarray, # np.ndarray[np.uint64, ndim=1] ) -> None: ... def get_indexer(self, target: npt.NDArray[np.object_]) -> npt.NDArray[np.intp]: ... def _extract_level_codes(self, target: MultiIndex) -> np.ndarray: ... def get_indexer_with_fill( self, target: np.ndarray, # np.ndarray[object] of tuples values: np.ndarray, # np.ndarray[object] of tuples method: str, limit: int | None, ) -> npt.NDArray[np.intp]: ... class ExtensionEngine: def __init__(self, values: ExtensionArray) -> None: ... def __contains__(self, val: object) -> bool: ... def get_loc(self, val: object) -> int | slice | np.ndarray: ... def get_indexer(self, values: np.ndarray) -> npt.NDArray[np.intp]: ... def get_indexer_non_unique( self, targets: np.ndarray, ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]: ... @property def is_unique(self) -> bool: ... @property def is_monotonic_increasing(self) -> bool: ... @property def is_monotonic_decreasing(self) -> bool: ... def sizeof(self, deep: bool = ...) -> int: ... def clear_mapping(self): ...