• I need help in python Thanks

• Online BPP - Next Fit

• Online BPP - First Fit

• Online BPP - Best Fit

• Offline BPP - First Fit Decreasing (presorted)

• Offline BPP - Best Fit Decreasing (presorted)

Implement each of the five approximation algorithms mentioned above. For the two "offline" versions that require presorting the data in non-increasing (decreasing) order, you may use Python's built-in sorting function or call any other sorting algorithm of your choosing. You may also use your choice of data structure for finding a bin with a suitable or best-fit capacity

My code :

import math import random import sys import time from os import listdir from os.path import isfile, join import pandas as pd import matplotlib.pyplot as plt from copy import deepcopy from heapq import heappop, heappush cap = 100 def process_file(file_name, my_path): with open(my_path + file_name, 'r') as file: weights = [] lines = file.readlines() for line in lines: weights.append(int(line)) nbins = BPP_nextFit(weights) opt_bins = sum(weights) / cap print(file_name, ' Number of weights: ', len(weights), "Bins for BPP next fit: ", nbins, 'Opt bins: ', opt_bins) def BPP_nextFit(weights): nBins = 0 remCap = cap for weight in weights: if weight > remCap: nBins += 1 remCap = cap remCap -= weight return nBins def main(): my_path = 'C:\\Users\\faruk\\PycharmProjects\\Projects' files = [f for f in listdir(my_path) if isfile(join(my_path, f))] for file in files: process_file(file, my_path) if __name__ == '__main__': main()