在Python中反转二维列表（矩阵）与`zip`函数的使用

def invert_matrix(matrix: list[list[int]]) -> list[list[int]]:
    new_matrix = []
    for i in range(len(matrix[0])):
        new_row = []
        for row in matrix:
            new_row.append(row[i])
        new_matrix.append(new_row)
    return new_matrix

def invert_matrix(matrix: list[list[int]]) -> list[list[int]]:
    return [[row[i] for row in matrix] for i in range(len(matrix[0]))]

Init signature: zip(self, /, *args, **kwargs)
Docstring:
zip(*iterables, strict=False) --> Yield tuples until an input is exhausted.

>>> list(zip('abcdefg', range(3), range(4)))
[('a', 0, 0), ('b', 1, 1), ('c', 2, 2)]

The zip object yields n-length tuples, where n is the number of iterables
passed as positional arguments to zip().  The i-th element in every tuple
comes from the i-th iterable argument to zip().  This continues until the
shortest argument is exhausted.

If strict is true and one of the arguments is exhausted before the others,
raise a ValueError.
Type:           type
Subclasses:

def gen_fib() -> Generator[int, None, None]:
    a, b = 1, 1
    while True:
        yield a
        a, b = b, a + b

assert [num for _, num in zip(range(5), gen_fib())] == [1, 1, 2, 3, 5]

assert dict(zip('abcde', range(5))) == {'a': 0, 'b': 1, 'c': 2, 'd': 3, 'e': 4}

def invert_matrix(matrix: list[list[int]]) -> list[list[int]]:
    return [list(t) for t in zip(*matrix)]

import numpy as np
matrix = np.arange(9).reshape((3,3))
assert matrix.transpose() == np.array([[0, 3, 6], [1, 4, 7], [2, 5, 8]])