add knapsack

include pipenv files

chapter11/knapsack.py

@@ -0,0 +1,58 @@
+import logging
+from dataclasses import dataclass
+
+from tabulate import tabulate
+
+logging.basicConfig(
+    level=logging.DEBUG,
+    format="%(asctime)s %(levelname)s\n\r%(message)s",
+    datefmt="%H:%M:%S",
+)
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class Item:
+    name: str
+    value: int
+    weight: int
+
+
+def dynamic(W, items, n):
+    # create table and zero fill it (required for calculations)
+    table = [[0 for _ in range(W + 1)] for _ in range(n + 1)]
+
+    # calcalate all possible max values for items in knapsack
+    for i in range(1, n + 1):
+        for w in range(1, W + 1):
+            if items[i - 1].weight <= w:
+                table[i][w] = max(
+                    items[i - 1].value + table[i - 1][w - items[i - 1].weight],
+                    table[i - 1][w],
+                )
+            else:
+                table[i][w] = table[i - 1][w]
+
+    format_and_print(table)
+
+    return table[-1][-1]
+
+
+def format_and_print(table):
+    # enumerate first row (headings) + label each row in column0
+    for i, row in enumerate(table):
+        if i == 0:
+            continue
+        row[0] = items[i - 1].name
+    table[0] = [i for i in range(W + 1)]
+    table[0][0] = None
+
+    # print tabularised 2D array
+    logger.info(tabulate(table, tablefmt="pretty"))
+
+
+items = [Item("Guitar", 1500, 1), Item("Stereo", 3000, 4), Item("Laptop", 2000, 3)]
+W = 4
+greatest_value = dynamic(W, items, len(items))
+
+print(greatest_value)