from osm_parser import get_default_parser
from collections import defaultdict


class Node:
    def __init__(self, id, lat, lng):
        self.id = id
        self.lat = float(lat)
        self.lng = float(lng)
        self.neighbours = []

    def coord_tuple(self):
        return self.lat, self.lng


parser = None  # Have a global reusable parser object


def add_neighbours(nodes):
    for way in parser.iter_ways():
        if 'highway' not in way['tags']:
            continue

        road = way['road']

        for i in range(len(road) - 1):
            node1 = road[i]
            node2 = road[i + 1]

            nodes[node1].neighbours.append(nodes[node2])
            nodes[node2].neighbours.append(nodes[node1])

    return nodes


def extract_osm_nodes(f_name):
    global parser
    parser = get_default_parser(f_name)
    nodes = dict()
    grid = defaultdict()

    for node in parser.iter_nodes():
        new_node = Node(node['id'], node['lat'], node['lon'])
        nodes[node['id']] = new_node

    add_neighbours(nodes)

    # remove nodes without neighbours.
    for node_id, node in nodes.copy().items():
        if not node.neighbours:
            del nodes[node_id]

    # create a "grid" by grouping nearby nodes.
    for node in nodes.copy().values():

        key = (int(round(node.lat, 3) * 1000), int(round(node.lng, 3)
                                                   * 1000))

        if key in grid.keys():
            grid[key].append(node)

        else:
            grid[key] = [node]

    return nodes, grid


def select_nodes_in_rectangle(nodes, min_lat, max_lat, min_long, max_long):
    return [node for node in nodes.values()
            if min_lat <= node.lat <= max_lat
            and min_long <= node.lng <= max_long]