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| """ define generic base classes for pandas objects """
| from __future__ import annotations
|
| from typing import (
| TYPE_CHECKING,
| Type,
| cast,
| )
|
| if TYPE_CHECKING:
| from pandas import (
| Categorical,
| CategoricalIndex,
| DataFrame,
| DatetimeIndex,
| Index,
| IntervalIndex,
| MultiIndex,
| PeriodIndex,
| RangeIndex,
| Series,
| TimedeltaIndex,
| )
| from pandas.core.arrays import (
| DatetimeArray,
| ExtensionArray,
| PandasArray,
| PeriodArray,
| TimedeltaArray,
| )
| from pandas.core.generic import NDFrame
|
|
| # define abstract base classes to enable isinstance type checking on our
| # objects
| def create_pandas_abc_type(name, attr, comp):
| def _check(inst) -> bool:
| return getattr(inst, attr, "_typ") in comp
|
| # https://github.com/python/mypy/issues/1006
| # error: 'classmethod' used with a non-method
| @classmethod # type: ignore[misc]
| def _instancecheck(cls, inst) -> bool:
| return _check(inst) and not isinstance(inst, type)
|
| @classmethod # type: ignore[misc]
| def _subclasscheck(cls, inst) -> bool:
| # Raise instead of returning False
| # This is consistent with default __subclasscheck__ behavior
| if not isinstance(inst, type):
| raise TypeError("issubclass() arg 1 must be a class")
|
| return _check(inst)
|
| dct = {"__instancecheck__": _instancecheck, "__subclasscheck__": _subclasscheck}
| meta = type("ABCBase", (type,), dct)
| return meta(name, (), dct)
|
|
| ABCRangeIndex = cast(
| "Type[RangeIndex]",
| create_pandas_abc_type("ABCRangeIndex", "_typ", ("rangeindex",)),
| )
| ABCMultiIndex = cast(
| "Type[MultiIndex]",
| create_pandas_abc_type("ABCMultiIndex", "_typ", ("multiindex",)),
| )
| ABCDatetimeIndex = cast(
| "Type[DatetimeIndex]",
| create_pandas_abc_type("ABCDatetimeIndex", "_typ", ("datetimeindex",)),
| )
| ABCTimedeltaIndex = cast(
| "Type[TimedeltaIndex]",
| create_pandas_abc_type("ABCTimedeltaIndex", "_typ", ("timedeltaindex",)),
| )
| ABCPeriodIndex = cast(
| "Type[PeriodIndex]",
| create_pandas_abc_type("ABCPeriodIndex", "_typ", ("periodindex",)),
| )
| ABCCategoricalIndex = cast(
| "Type[CategoricalIndex]",
| create_pandas_abc_type("ABCCategoricalIndex", "_typ", ("categoricalindex",)),
| )
| ABCIntervalIndex = cast(
| "Type[IntervalIndex]",
| create_pandas_abc_type("ABCIntervalIndex", "_typ", ("intervalindex",)),
| )
| ABCIndex = cast(
| "Type[Index]",
| create_pandas_abc_type(
| "ABCIndex",
| "_typ",
| {
| "index",
| "rangeindex",
| "multiindex",
| "datetimeindex",
| "timedeltaindex",
| "periodindex",
| "categoricalindex",
| "intervalindex",
| },
| ),
| )
|
|
| ABCNDFrame = cast(
| "Type[NDFrame]",
| create_pandas_abc_type("ABCNDFrame", "_typ", ("series", "dataframe")),
| )
| ABCSeries = cast(
| "Type[Series]",
| create_pandas_abc_type("ABCSeries", "_typ", ("series",)),
| )
| ABCDataFrame = cast(
| "Type[DataFrame]", create_pandas_abc_type("ABCDataFrame", "_typ", ("dataframe",))
| )
|
| ABCCategorical = cast(
| "Type[Categorical]",
| create_pandas_abc_type("ABCCategorical", "_typ", ("categorical")),
| )
| ABCDatetimeArray = cast(
| "Type[DatetimeArray]",
| create_pandas_abc_type("ABCDatetimeArray", "_typ", ("datetimearray")),
| )
| ABCTimedeltaArray = cast(
| "Type[TimedeltaArray]",
| create_pandas_abc_type("ABCTimedeltaArray", "_typ", ("timedeltaarray")),
| )
| ABCPeriodArray = cast(
| "Type[PeriodArray]",
| create_pandas_abc_type("ABCPeriodArray", "_typ", ("periodarray",)),
| )
| ABCExtensionArray = cast(
| "Type[ExtensionArray]",
| create_pandas_abc_type(
| "ABCExtensionArray",
| "_typ",
| # Note: IntervalArray and SparseArray are included bc they have _typ="extension"
| {"extension", "categorical", "periodarray", "datetimearray", "timedeltaarray"},
| ),
| )
| ABCPandasArray = cast(
| "Type[PandasArray]",
| create_pandas_abc_type("ABCPandasArray", "_typ", ("npy_extension",)),
| )
|
|
