[new] added 0/1 knapsack python code

Author: NeerajHazarika

Dynamic Programming/0 1 Knapsack/01_knapsack.py

@@ -0,0 +1,54 @@
+# This is the memoization approach of 0 / 1 Knapsack in Python in simple
+# Method : Dynamic Programming
+# Author : Neeraj Pratap Hazarika
+
+# Problem Statement : Given a set of items, each with a weight and a value, take items to include in a knapsack such that the total weight is less than or equal to a given limit and the total value is as large as possible. Print the total value.
+
+# ------------------------------------------------------------
+
+# declare universal scope 2d matrix, dp
+dp=[[]]
+ 
+def knapsack(wt, val, W, n):
+ 
+    # base conditions
+    if n == 0 or W == 0:
+        return 0
+    if dp[n][W] != -1:
+        return dp[n][W]
+ 
+    # choice diagram code
+    if wt[n-1] <= W:
+        dp[n][W] = max(val[n-1] + knapsack(wt, val, W-wt[n-1], n-1), knapsack(wt, val, W, n-1))
+        return dp[n][W]
+    elif wt[n-1] > W:
+        dp[n][W] = knapsack(wt, val, W, n-1)
+        return dp[n][W]
+
+# Driver code
+if __name__ == '__main__':
+    # Inputs
+    W = int(input("Enter the maximum weight the knapsack can hold : "))
+    n = int(input("Enter number of items to be choosen from : "))
+    print("Enter the weights to be choosen from : ")
+    wt = list(map(int,input().strip().split()))[:n]
+    print("Enter the values corresponding to these weights : ")
+    val = list(map(int,input().strip().split()))[:n]
+
+    # Initialize 2d matrix, dp 
+    dp = [[-1 for i in range(W + 1)] for j in range(n + 1)]
+
+    print("Maximum profit : ",knapsack(wt, val, W, n))
+
+# ------------------------------------------------------------
+
+# Inputs given :
+# Enter the maximum weight the knapsack can hold : 50
+# Enter number of items to be choosen from : 3
+# Enter the weights to be choosen from : 
+# 10 20 30 
+# Enter the values corresponding to these weights : 
+# 60 100 120
+
+# Output :
+# Maximum profit : 220