So, you need to fill the order with the packages such that the total price is maximal? This is known as Knapsack problem. In that Wikipedia article you'll find several solutions written in Python.
To be more precise, you need a solution for the unbounded knapsack problem, in contrast to popular 0/1 knapsack problem (where each item can be packed only once). Here is working code from Rosetta:
from itertools import product
NAME, SIZE, VALUE = range(3)
items = (
# NAME, SIZE, VALUE
('A', 3, 5),
('B', 5, 9),
('C', 9, 16))
capacity = 13
def knapsack_unbounded_enumeration(items, C):
# find max of any one item
max1 = [int(C / item[SIZE]) for item in items]
itemsizes = [item[SIZE] for item in items]
itemvalues = [item[VALUE] for item in items]
# def totvalue(itemscount, =itemsizes, itemvalues=itemvalues, C=C):
def totvalue(itemscount):
# nonlocal itemsizes, itemvalues, C
totsize = sum(n * size for n, size in zip(itemscount, itemsizes))
totval = sum(n * val for n, val in zip(itemscount, itemvalues))
return (totval, -totsize) if totsize <= C else (-1, 0)
# Try all combinations of bounty items from 0 up to max1
bagged = max(product(*[range(n + 1) for n in max1]), key=totvalue)
numbagged = sum(bagged)
value, size = totvalue(bagged)
size = -size
# convert to (iten, count) pairs) in name order
bagged = ['%dx%d' % (n, items[i][SIZE]) for i, n in enumerate(bagged) if n]
return value, size, numbagged, bagged
if __name__ == '__main__':
value, size, numbagged, bagged = knapsack_unbounded_enumeration(items, capacity)
print(value)
print(bagged)
Output is:
23
['1x3', '2x5']
Keep in mind that this is a NP-hard problem, so it will blow as you enter some large values :)
