Need an alternative to brute force optimization loop

[Pedroski55]

Why so cagey?

Tell us what the functions and variables are!

As the guys said, np is faster than Python.

It is sometimes said that Python, compared to low-level languages such as C++, improves development time at the expense of runtime.

For this example, from realpython.com, numpy is nearly 100 times faster:

import numpy as np
from timeit import timeit

def profit(prices):
    max_px = 0
    min_px = prices[0]
    for px in prices[1:]:
        min_px = min(min_px, px)
        max_px = max(px - min_px, max_px)
    return max_px

def profit_with_numpy(prices):
    """Price minus cumulative minimum price, element-wise."""
    prices = np.asarray(prices)
    return np.max(prices - cummin(prices))

cummin = np.minimum.accumulate
# compare speeds
seq = np.random.randint(0, 100, size=100000)
setup = ('from __main__ import profit_with_numpy, profit, seq;' ' import numpy as np')
num = 250
pytime = timeit('profit(seq)', setup=setup, number=num)
nptime = timeit('profit_with_numpy(seq)', setup=setup, number=num)
print('Speed difference: {:0.1f}x'.format(pytime / nptime))

Output:
Speed difference: 93.5x