Random Flip Matrix Python Solution with Tests

lcpy gen -n 519   # by problem number
lcpy gen -s random_flip_matrix   # by problem name

Input
["Solution", "flip", "flip", "flip", "reset", "flip"]
[[3, 1], [], [], [], [], []]
Output
[null, [1, 0], [2, 0], [0, 0], null, [2, 0]]

Explanation
Solution solution = new Solution(3, 1);
solution.flip();  // return [1, 0], [0,0], [1,0], and [2,0] should be equally likely to be returned.
solution.flip();  // return [2, 0], Since [1,0] was returned, [2,0] and [0,0]
solution.flip();  // return [0, 0], Based on the previously returned indices, only [0,0] can be returned.
solution.reset(); // All the values are reset to 0 and can be returned.
solution.flip();  // return [2, 0], [0,0], [1,0], and [2,0] should be equally likely to be returned.

import random


class Solution:
    # Time: __init__ O(1), flip O(1), reset O(1)
    # Space: O(k) where k is the number of flips since the last reset
    def __init__(self, m: int, n: int) -> None:
        self.m = m
        self.n = n
        self.total = m * n
        self.available = self.total
        self.swapped: dict[int, int] = {}

    def flip(self) -> list[int]:
        idx = random.randrange(self.available)
        self.available -= 1
        picked = self.swapped.get(idx, idx)
        self.swapped[idx] = self.swapped.get(self.available, self.available)
        return [picked // self.n, picked % self.n]

    def reset(self) -> None:
        self.available = self.total
        self.swapped = {}