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