Knapsack $-$ greedy algorithm.

Write a function in python that takes a max weight as an argument, and uses backtracking to find the max value

of items and the specific items that can be selected while keeping the weight less than or equal to the

max weight. Assume that there is at most one of each item. Run your code with the items listed in

the $.$csv file posted in D$2$L and OneNote.

Optional: You may use the

KnapsackClass.py file posted in D$2$L and OneNote. It puts all the knapsack

items into a single list.

Note: Answers may vary depending on the heuristic you use.

Example $1$:

Input: posted $.$csv file with max weight $=25$

Output: $[\text{'}$platinum$\text{'},$ 'bronze', 'gold', 'silver', 'copper', 'value $=41\mathrm{.}0\text{'}]$

Example $2$:

Input: posted $.$csv file with max weight $=15$

Output: $[\text{'}$platinum$\text{'},$ 'bronze', 'gold', 'silver', 'value $=35\mathrm{.}0\text{'}]$

Example $3$:

Input: posted $.$csv file with max weight $=17$

Output: $[\text{'}$platinum$\text{'},$ 'bronze', 'gold', 'silver', 'value $=35\mathrm{.}0\text{'}]$