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chore: improve fancypy typehinting #82

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chore: improve fancypy typehinting #82

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921ffbf
Improve fancypy typehinting
Thijss Jul 22, 2025
5de58f5
remove dummy code
Thijss Jul 22, 2025
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14 changes: 8 additions & 6 deletions src/power_grid_model_ds/_core/fancypy.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4,17 +4,19 @@

"""A set of helper functions that mimic numpy functions but are specifically designed for FancyArrays."""

from typing import TYPE_CHECKING, Union
from typing import TYPE_CHECKING, TypeVar, Union

import numpy as np

from power_grid_model_ds._core.utils.misc import array_equal_with_nan

if TYPE_CHECKING:
from power_grid_model_ds._core.model.arrays.base.array import FancyArray
from power_grid_model_ds._core.model.arrays.base.array import FancyArray # noqa

T = TypeVar("T", bound="FancyArray")

def concatenate(fancy_array: "FancyArray", *other_arrays: Union["FancyArray", np.ndarray]) -> "FancyArray":

def concatenate(fancy_array: T, *other_arrays: Union[T, np.ndarray]) -> T:
"""Concatenate arrays."""
np_arrays = [array if isinstance(array, np.ndarray) else array.data for array in other_arrays]
try:
Expand All @@ -24,7 +26,7 @@ def concatenate(fancy_array: "FancyArray", *other_arrays: Union["FancyArray", np
return fancy_array.__class__(data=concatenated)


def unique(array: "FancyArray", **kwargs):
def unique(array: T, **kwargs):
"""Return the unique elements of the array."""
for column in array.columns:
if np.issubdtype(array.dtype[column], np.floating) and np.isnan(array[column]).any():
Expand All @@ -37,13 +39,13 @@ def unique(array: "FancyArray", **kwargs):
return array.__class__(data=unique_data)


def sort(array: "FancyArray", axis=-1, kind=None, order=None) -> "FancyArray":
def sort(array: T, axis=-1, kind=None, order=None) -> T:
"""Sort the array in-place and return sorted array."""
array.data.sort(axis=axis, kind=kind, order=order)
return array


def array_equal(array1: "FancyArray", array2: "FancyArray", equal_nan: bool = True) -> bool:
def array_equal(array1: T, array2: T, equal_nan: bool = True) -> bool:
"""Return True if two arrays are equal."""
if equal_nan:
return array_equal_with_nan(array1.data, array2.data)
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