#!/usr/bin/env python3

from collections import defaultdict
import hashlib
import matplotlib.pyplot as plt
import numpy as np

# int(ipaddress.IPv4Address("192.168.0.1"))

def load_ips(path):
    with open(path, 'r') as f:
        return f.readlines()


def partition(crawlers, ips):
    mod = len(crawlers)
    result = defaultdict(list)
    for ip in ips:
        h = hashlib.md5(ip.encode('utf-8'), usedforsecurity=False).digest()
        num = int.from_bytes(h, 'big')
        pos = num % mod
        c = crawlers[pos]
        result[c].append(ip)

    return result


def main():
    ips = load_ips('./ips.csv')
    c2 = ['c0', 'c1']
    c4 = ['c0', 'c1', 'c2', 'c3']
    c6 = ['c0', 'c1', 'c2', 'c3', 'c4', 'c5']
    c10 = ['c0', 'c1', 'c2', 'c3', 'c4', 'c5', 'c6', 'c7', 'c8', 'c9']

    for cs in [c2, c4, c6, c10]:
        print(f'{len(cs)} crawlers')

        part = partition(cs, ips)

        ind = np.arange(len(cs))
        fig, ax = plt.subplots()
        crawlers = sorted(cs)

        ax.invert_yaxis()
        ax.set_ylabel('Crawlers')
        ax.set_xlabel('Peers')
        ax.set_title(f'IP Partitioning for {len(cs)} crawlers')
        ax.set_yticks(ind)

        # ax.set_xticks(ind) #, labels=cs)

        ns = []

        for c, i in sorted(part.items(), key=lambda kv: kv[0]):
            print(f'\t{c}: {len(i)}')
            ns.append(len(i))

        # p1 = ax.bar(ind, ns, 0.35)
        hbars = ax.barh(ind, ns)
        ax.bar_label(hbars, label_type='center')
        # plt.show()
        plt.savefig(f'./ip_part_c{len(cs):02}.png')


            # p1 = ax.bar(ind, i, 0.35, label=c)


        # people = ('Tom', 'Dick', 'Harry', 'Slim', 'Jim')



#         hbars = ax.barh(y_pos, performance, xerr=error, align='center')
#         ax.set_yticks(y_pos, labels=people)
#         ax.invert_yaxis()  # labels read top-to-bottom
#         ax.set_xlabel('Performance')
#         ax.set_title('How fast do you want to go today?')

#         # Label with specially formatted floats
#         ax.bar_label(hbars, fmt='%.2f')
#         ax.set_xlim(right=15)  # adjust xlim to fit labels

        # plt.show()

        print()
        print()
        print()
        print()


if __name__ == '__main__':
    main()