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https://github.com/onyx-and-iris/grokking-algorithms.git
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add knapsack
include pipenv files
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parent
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12
Pipfile
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12
Pipfile
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[[source]]
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url = "https://pypi.org/simple"
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verify_ssl = true
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name = "pypi"
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[packages]
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tabulate = "*"
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[dev-packages]
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[requires]
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python_version = "3.11"
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30
Pipfile.lock
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30
Pipfile.lock
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{
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"_meta": {
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"hash": {
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"sha256": "5b2e934e1ca40f369f7dcd74ed36744eae3116276796320e2800026566302307"
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},
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"pipfile-spec": 6,
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"requires": {
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"python_version": "3.11"
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},
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"sources": [
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{
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"name": "pypi",
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"url": "https://pypi.org/simple",
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"verify_ssl": true
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}
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]
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},
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"default": {
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"tabulate": {
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"hashes": [
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"sha256:0095b12bf5966de529c0feb1fa08671671b3368eec77d7ef7ab114be2c068b3c",
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"sha256:024ca478df22e9340661486f85298cff5f6dcdba14f3813e8830015b9ed1948f"
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],
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"index": "pypi",
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"markers": "python_version >= '3.7'",
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"version": "==0.9.0"
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}
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},
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"develop": {}
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}
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58
chapter11/knapsack.py
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58
chapter11/knapsack.py
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import logging
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from dataclasses import dataclass
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from tabulate import tabulate
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logging.basicConfig(
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level=logging.DEBUG,
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format="%(asctime)s %(levelname)s\n\r%(message)s",
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datefmt="%H:%M:%S",
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)
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logger = logging.getLogger(__name__)
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@dataclass
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class Item:
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name: str
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value: int
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weight: int
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def dynamic(W, items, n):
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# create table and zero fill it (required for calculations)
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table = [[0 for _ in range(W + 1)] for _ in range(n + 1)]
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# calcalate all possible max values for items in knapsack
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for i in range(1, n + 1):
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for w in range(1, W + 1):
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if items[i - 1].weight <= w:
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table[i][w] = max(
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items[i - 1].value + table[i - 1][w - items[i - 1].weight],
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table[i - 1][w],
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)
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else:
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table[i][w] = table[i - 1][w]
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format_and_print(table)
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return table[-1][-1]
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def format_and_print(table):
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# enumerate first row (headings) + label each row in column0
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for i, row in enumerate(table):
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if i == 0:
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continue
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row[0] = items[i - 1].name
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table[0] = [i for i in range(W + 1)]
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table[0][0] = None
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# print tabularised 2D array
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logger.info(tabulate(table, tablefmt="pretty"))
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items = [Item("Guitar", 1500, 1), Item("Stereo", 3000, 4), Item("Laptop", 2000, 3)]
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W = 4
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greatest_value = dynamic(W, items, len(items))
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print(greatest_value)
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