def maxSpending(values: List[List[int]]) -> int:
    """
    You are given a 0-indexed m * n integer matrix values, representing the values of m * n different items in m different shops. Each shop has n items where the jth item in the ith shop has a value of values[i][j]. Additionally, the items in the ith shop are sorted in non-increasing order of value. That is, values[i][j] >= values[i][j + 1] for all 0 <= j < n - 1.
    On each day, you would like to buy a single item from one of the shops. Specifically, On the dth day you can:
    
    Pick any shop i.
    Buy the rightmost available item j for the price of values[i][j] * d. That is, find the greatest index j such that item j was never bought before, and buy it for the price of values[i][j] * d.
    
    Note that all items are pairwise different. For example, if you have bought item 0 from shop 1, you can still buy item 0 from any other shop.
    Return the maximum amount of money that can be spent on buying all  m * n products.
    
    Example 1:
    
    >>> maxSpending(values = [[8,5,2],[6,4,1],[9,7,3]])
    >>> 285
    Explanation: On the first day, we buy product 2 from shop 1 for a price of values[1][2] * 1 = 1.
    On the second day, we buy product 2 from shop 0 for a price of values[0][2] * 2 = 4.
    On the third day, we buy product 2 from shop 2 for a price of values[2][2] * 3 = 9.
    On the fourth day, we buy product 1 from shop 1 for a price of values[1][1] * 4 = 16.
    On the fifth day, we buy product 1 from shop 0 for a price of values[0][1] * 5 = 25.
    On the sixth day, we buy product 0 from shop 1 for a price of values[1][0] * 6 = 36.
    On the seventh day, we buy product 1 from shop 2 for a price of values[2][1] * 7 = 49.
    On the eighth day, we buy product 0 from shop 0 for a price of values[0][0] * 8 = 64.
    On the ninth day, we buy product 0 from shop 2 for a price of values[2][0] * 9 = 81.
    Hence, our total spending is equal to 285.
    It can be shown that 285 is the maximum amount of money that can be spent buying all m * n products.
    
    Example 2:
    
    >>> maxSpending(values = [[10,8,6,4,2],[9,7,5,3,2]])
    >>> 386
    Explanation: On the first day, we buy product 4 from shop 0 for a price of values[0][4] * 1 = 2.
    On the second day, we buy product 4 from shop 1 for a price of values[1][4] * 2 = 4.
    On the third day, we buy product 3 from shop 1 for a price of values[1][3] * 3 = 9.
    On the fourth day, we buy product 3 from shop 0 for a price of values[0][3] * 4 = 16.
    On the fifth day, we buy product 2 from shop 1 for a price of values[1][2] * 5 = 25.
    On the sixth day, we buy product 2 from shop 0 for a price of values[0][2] * 6 = 36.
    On the seventh day, we buy product 1 from shop 1 for a price of values[1][1] * 7 = 49.
    On the eighth day, we buy product 1 from shop 0 for a price of values[0][1] * 8 = 64
    On the ninth day, we buy product 0 from shop 1 for a price of values[1][0] * 9 = 81.
    On the tenth day, we buy product 0 from shop 0 for a price of values[0][0] * 10 = 100.
    Hence, our total spending is equal to 386.
    It can be shown that 386 is the maximum amount of money that can be spent buying all m * n products.
    """