Update best_time_to_buy_and_sell_stock.py

greedy_methods/best_time_to_buy_and_sell_stock.py

@@ -1,19 +1,17 @@
 """
-Given a list of stock prices,
-This program calculates the maximum profit that can be made from a single buy and sell.
-We can only complete one transaction (buy one and sell one share of the stock).
-We must buy before we can sell.
+Given a list of stock prices calculate the maximum profit that can be made from a
+single buy and sell of one share of stock.  We only allowed to complete one buy
+transaction and one sell transaction but must buy before we sell.
 
 Example : prices = [7, 1, 5, 3, 6, 4]
 max_profit will return 5 - which is by buying at price 1 and selling at price 6.
 
 This problem can be solved using the concept of "GREEDY ALGORITHM".
 
 We iterate over the price array once, keeping track of the lowest price point
-(buy) and the maximum profit we can get at each point.
-The greedy choice at each point is to either buy at the current price if
-it's less than our current buying price, or sell at the current price if the profit
-is more than our current maximum profit.
+(buy) and the maximum profit we can get at each point.  The greedy choice at each point
+is to either buy at the current price if it's less than our current buying price, or
+sell at the current price if the profit is more than our current maximum profit.
 """
 
 
@@ -31,10 +29,8 @@ def max_profit(prices: list[int]) -> int:
     max_profit: int = 0
 
     for price in prices:
-        if price < min_price:
-            min_price = price
-        elif price - min_price > max_profit:
-            max_profit = price - min_price
+        min_price = min(price, min_price)
+        max_profit = max(price - min_price, max_profit)
 
     return max_profit
 
@@ -43,5 +39,4 @@ def max_profit(prices: list[int]) -> int:
     import doctest
 
     doctest.testmod()
-
     print(max_profit([7, 1, 5, 3, 6, 4]))