Merge pull request #77 from jaydev-431/patch-1

Refactor stock profit calculation methods

Author: SamirPaulb

02_Dynamic-Programming/11. Buy and Sell Stock Problems/02. As Many Transactions As You Like.py

@@ -1,44 +1,63 @@
 # https://leetcode.com/problems/best-time-to-buy-and-sell-stock-ii/
 # https://www.youtube.com/watch?v=nGJmxkUJQGs
 
+# --------------------------------------------------------------------------------------------
+# 1) TOP-DOWN DP (Memoization)
+# --------------------------------------------------------------------------------------------
+
 class Solution:
     def maxProfit(self, prices: List[int]) -> int:
         memo = {}
+
         def solve(i, can_sell):
-            if i == len(prices): 
+            if i == len(prices):
                 return 0
-            if (i, can_sell) in memo: 
+            if (i, can_sell) in memo:
                 return memo[(i, can_sell)]
+
             if can_sell == 1:
                 profit = max(prices[i] + solve(i+1, 0), solve(i+1, 1))
             else:
                 profit = max(-prices[i] + solve(i+1, 1), solve(i+1, 0))
+
             memo[(i, can_sell)] = profit
             return profit
+
         return solve(0, 0)
 
-# Time: O(2 * N)
-# Space: O(N + N)
+# Time: O(2N)
+# Space: O(N)
+
 
-################################################################################################
+# --------------------------------------------------------------------------------------------
+# 2) BOTTOM-UP DP (Tabulation)
+# --------------------------------------------------------------------------------------------
 
 class Solution:
     def maxProfit(self, prices: List[int]) -> int:
         n = len(prices)
         dp = [[0]*2 for _ in range(n+1)]
         dp[0][0] = -2**31
+
         for i in range(1, n+1):
             for can_sell in range(2):
                 if can_sell == 1:
                     dp[i][can_sell] = max(prices[i-1] + dp[i-1][0], dp[i-1][1])
                 else:
                     dp[i][can_sell] = max(-prices[i-1] + dp[i-1][1], dp[i-1][0])
+
         return dp[-1][1]
 
-################################################################################################
+
+# --------------------------------------------------------------------------------------------
+# 3) GREEDY (Optimized)
+#  Tiny PR change: Added type hints
+# --------------------------------------------------------------------------------------------
+
+from typing import List
 
 class Solution:
-    def maxProfit(self, prices):
+    def maxProfit(self, prices: List[int]) -> int:
         res = 0
 
         for i in range(len(prices) - 1):