#!/usr/bin/env python3

from datetime import datetime
from random import sample, seed
import rank_with_churn
import glob
from node_ranking import (
    # page_rank,
    # sensor_rank,
    # find_rank,
    parse_csv,
    # csv_loader,
    build_graph,
    # Node,
    # RankedNode,
)

def load_data(path):
    data = []
    with open(path, 'r') as f:
        for line in f.readlines():
            data.append(parse_csv(line))

    return data

def edges_from(g, node):
    return list(filter(lambda e: e[1] == node, g.edges()))

def remove_edges(path, percentage):
    when = datetime.fromtimestamp(float(path.split('/')[-1][:-4]))
    print(f'{when=}, {percentage=}')
    edges = load_data(path)
    g = build_graph(edges)
    edges = edges_from(g, rank_with_churn.KNOWN)
    for_removal = sample(edges, int(len(edges) * percentage))
    for edge in for_removal:
        g.remove_edge(edge[0], edge[1])
    with open(f'./edges_reduced/{percentage:.02f}/{when.timestamp()}.txt', 'w') as f:
        for [s, d] in g.edges():
            row = f'{s.node.ip},{s.node.port},{d.node.ip},{d.node.port}\n'
            f.write(row)

percentages = [0.0, 0.3, 0.5, 0.75]
# percentages = [0.0]
def main():
    for percentage in percentages:
        for file in glob.glob('./edges/*.txt'):
            remove_edges(file, percentage)


if __name__ == '__main__':
    main()