Interviewcake.com algorithmic pattern practice #1, Parker's solution.

greedy2.py

def get_max_profit(stock_prices):
    if len(stock_prices) < 2:
        raise ValueError('Getting a profit requires at least 2 prices')
    # We'll greedily update min_price and max_profit, so we initialize
    # them to the first price and the first possible profit
    min_price = stock_prices[0]
    max_profit = stock_prices[1] - stock_prices[0]
    # Start at the second (index 1) time
    # We can't sell at the first time, since we must buy first,
    # and we can't buy and sell at the same time! # If we started at index 0,
    #we'd try to buy *and* sell at time 0.
    # This would give a profit of 0, which is a problem if our
    # max_profit is supposed to be *negative* - we'd return 0.
    for current_time in xrange(1, len(stock_prices)):
        current_price = stock_prices[current_time]
    # See what our profit would be if we bought at the
    # min price and sold at the current price potential_profit = current_price - min_price
    # Update max_profit if we can do better
    max_profit = max(max_profit, potential_profit)
    # Update min_price so it's always # the lowest price we've seen so far
    min_price = min(min_price, current_price) return max_profit