#!/usr/bin/env python3

from functools import reduce
from typing import Callable, Iterator
import sys

import networkx as nx

class Edge:
    def __init__(self, source, destination):
        self.source = source
        self.destination = destination

    def __eq__(self, other):
        return (
            isinstance(other, Edge)
            and self.source == other.source
            and self.destination == other.destination
        )

    def __hash__(self):
        return hash((self.source, self.destination))

    def __repr__(self):
        return f'Edge({self.source}, {self.destination})'

class Node:
    def __init__(self, node, rank: float):
        self.node = node
        self.rank = rank

    def with_rank(self, new_rank: float):
        return Node(self.node, new_rank)

    def __eq__(self, other):
        """
        Equality only compares the `Node`, not the rank value
        """
        return (
            isinstance(other, Node)
            and self.node == other.node
        )

    def __hash__(self):
        """
        Equality only hashes the `Node`, not the rank value
        """
        return hash((self.node))

    def __repr__(self):
        return f'Node({self.node}, {self.rank})'

def build_graph(edges: Iterator[Edge], initial_rank: float = 0.25) -> nx.DiGraph:
    """
    Create a graph from an iterator over `Edge`s
    """
    graph = nx.DiGraph()
    for edge in edges:
        source = Node(edge.source, initial_rank)
        destination = Node(edge.destination, initial_rank)
        graph.add_node(source)
        graph.add_node(destination)
        graph.add_edge(source, destination)

    return graph

def parse_edge(line: str) -> Edge:
    """
    Parse a line into an edge. The line is expected to be of the format source_ip:source_port->destination_ip:destination_port,
    e.g. `1.1.1.1:1337->2.2.2.2:1337`

    :param line: (str) the line
    :return: the parsed edge
    """
    # remove spaces and potential leading semicolon. then split at ->
    split = line.strip().strip(';').split("->")
    return Edge(split[0].strip(), split[1].strip())

def file_loader(path: str) -> Iterator[Edge]:
    """
    Load a list of edges from a file.

    :param path: (str) filepath
    :return: iterator over the edges
    """
    with open(path, "r") as file:
        return map(
            parse_edge,
            # filter only edges
            filter(
                lambda line: '->' in line,
                file.readlines()
            )
        )

def page_ranker(
    graph: nx.DiGraph, node: Node, dampingFactor: float = 1.0
) -> float:
    return (
        reduce(
            lambda x, y: x + y,
            map(
                lambda pred: pred.rank / len(list(graph.successors(pred))),
                graph.predecessors(node),
            ),
            0.0,
        )
        * dampingFactor
        + (1 - dampingFactor) / graph.number_of_nodes()
    )

def page_rank(graph: nx.DiGraph, dampingFactor: float = 1.0) -> nx.DiGraph:
    return rank(graph, lambda g, node: page_ranker(g, node, dampingFactor))

def sensor_rank(graph: nx.DiGraph) -> nx.DiGraph:
    number_of_nodes = graph.number_of_nodes()
    return rank(
        graph,
        lambda g, node: (node.rank / len(list(g.successors(node)))) * (len(list(g.predecessors(node))) / number_of_nodes),
    )


def rank(
    graph: nx.DiGraph, rank_fn: Callable[[nx.DiGraph, Node], float]
) -> nx.DiGraph:
    ranked_graph = nx.DiGraph()
    # number_of_nodes = graph.number_of_nodes()
    for node in graph.nodes:
        rank = rank_fn(graph, node)

        ranked_graph.add_node(node.with_rank(rank))

    for u, v in graph.edges:
        ranked_graph.add_edge(u, v)

    return ranked_graph

def main():
    arg = sys.argv
    if len(arg) != 2:
        print(f'Usage: {arg[0]} graph.dot')
        sys.exit(1)

    edges = file_loader(arg[1])
    graph = build_graph(edges)
    page_ranked = page_rank(graph)
    print("PageRank: ")
    for node in page_ranked:
        print(node)

    print()
    sensor_ranked = sensor_rank(page_ranked)
    print("SensorRank: ")
    for node in sensor_ranked:
        print(node)


if __name__ == '__main__':
    main()