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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: ...
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): ...
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