from __future__ import annotations

from ._array_object import ndarray

from typing import TYPE_CHECKING
if TYPE_CHECKING:
    from ._types import Optional, Tuple, Union, array

import numpy as np

# Note: the function name is different here
def concat(arrays: Tuple[array, ...], /, *, axis: Optional[int] = 0) -> array:
    """
    Array API compatible wrapper for :py:func:`np.concatenate <numpy.concatenate>`.

    See its docstring for more information.
    """
    arrays = tuple(a._array for a in arrays)
    return ndarray._new(np.concatenate(arrays, axis=axis))

def expand_dims(x: array, /, *, axis: int) -> array:
    """
    Array API compatible wrapper for :py:func:`np.expand_dims <numpy.expand_dims>`.

    See its docstring for more information.
    """
    return ndarray._new(np.expand_dims(x._array, axis))

def flip(x: array, /, *, axis: Optional[Union[int, Tuple[int, ...]]] = None) -> array:
    """
    Array API compatible wrapper for :py:func:`np.flip <numpy.flip>`.

    See its docstring for more information.
    """
    return ndarray._new(np.flip(x._array, axis=axis))

def reshape(x: array, /, shape: Tuple[int, ...]) -> array:
    """
    Array API compatible wrapper for :py:func:`np.reshape <numpy.reshape>`.

    See its docstring for more information.
    """
    return ndarray._new(np.reshape(x._array, shape))

def roll(x: array, /, shift: Union[int, Tuple[int, ...]], *, axis: Optional[Union[int, Tuple[int, ...]]] = None) -> array:
    """
    Array API compatible wrapper for :py:func:`np.roll <numpy.roll>`.

    See its docstring for more information.
    """
    return ndarray._new(np.roll(x._array, shift, axis=axis))

def squeeze(x: array, /, axis: Optional[Union[int, Tuple[int, ...]]] = None) -> array:
    """
    Array API compatible wrapper for :py:func:`np.squeeze <numpy.squeeze>`.

    See its docstring for more information.
    """
    return ndarray._new(np.squeeze(x._array, axis=axis))

def stack(arrays: Tuple[array, ...], /, *, axis: int = 0) -> array:
    """
    Array API compatible wrapper for :py:func:`np.stack <numpy.stack>`.

    See its docstring for more information.
    """
    arrays = tuple(a._array for a in arrays)
    return ndarray._new(np.stack(arrays, axis=axis))