Пожалуйста, все бога, который существуют в этом мире, я надеюсь, что допишу 1 проверку и все это заработает
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@ -1,15 +1,12 @@
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import json
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from datetime import datetime, timedelta, date
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from datetime import datetime, timedelta
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import random
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from typing import Dict, List, Tuple, Any
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from fastapi import FastAPI, HTTPException, Request
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from schemas import TripRequest
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def load_graph_from_request(request: TripRequest) -> tuple[
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dict[str, dict[Any, Any]], dict[str, dict[Any, Any]], str, str, list[dict[str, datetime | str | int]], list[
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dict[str, datetime | str | int]], date, date | None]:
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def load_graph_from_request(request: TripRequest) -> Tuple[Dict[Tuple[str, str], List[Any]], Dict[Tuple[str, str], List[Any]], str, str, List[Dict], List[Dict], datetime, datetime]:
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graphTo = {}
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flightsDataTo = []
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graphBack = {}
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@ -41,14 +38,12 @@ def load_graph_from_request(request: TripRequest) -> tuple[
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"destinationTime": destination_time
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})
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# Проверка наличия вершин в графе и их создание при необходимости
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if departure_point not in graphTo:
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graphTo[departure_point] = {}
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if destination_point not in graphTo:
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graphTo[destination_point] = {}
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# Проверка наличия ребра в графе и его создание при необходимости
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if (departure_point, destination_point) not in graphTo:
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graphTo[(departure_point, destination_point)] = []
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# Добавление ребра в граф
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graphTo[departure_point][destination_point] = [flight.distance, departure_time, destination_time]
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graphTo[(departure_point, destination_point)].append([flight.distance, departure_time, destination_time])
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# Добавить каждый полет в граф
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for flight in flightsBack:
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@ -66,65 +61,54 @@ def load_graph_from_request(request: TripRequest) -> tuple[
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"destinationTime": destination_time
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})
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# Проверка наличия вершин в графе и их создание при необходимости
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if departure_point not in graphBack:
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graphBack[departure_point] = {}
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if destination_point not in graphBack:
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graphBack[destination_point] = {}
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# Проверка наличия ребра в графе и его создание при необходимости
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if (departure_point, destination_point) not in graphBack:
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graphBack[(departure_point, destination_point)] = []
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# Добавление ребра в граф
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graphBack[departure_point][destination_point] = [flight.distance, departure_time, destination_time]
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graphBack[(departure_point, destination_point)].append([flight.distance, departure_time, destination_time])
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print(graphTo)
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return graphTo,graphBack, start_point, end_point, flightsDataTo, flightsDataBack, departure_date, departure_date_return
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return graphTo, graphBack, start_point, end_point, flightsDataTo, flightsDataBack, departure_date, departure_date_return
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def path_length_and_time(path, graph, departure_date):
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def path_length_and_time(path, graph):
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length = 0
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if path[0] not in graph or path[1] not in graph[path[0]]:
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if (path[0], path[1]) not in graph:
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return float('inf'), None, None
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start_time = graph[path[0]][path[1]][1]
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start_time = graph[(path[0], path[1])][0][1]
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end_time = start_time
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for i in range(len(path) - 1):
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if path[i] not in graph or path[i + 1] not in graph[path[i]]:
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if (path[i], path[i + 1]) not in graph:
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return float('inf'), start_time, end_time
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if departure_date != start_time.date():
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return float('inf'), start_time, end_time
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if i > 0:
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print("Start time:", start_time)
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print("graph date:", graph[path[i]][path[i + 1]][1])
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if start_time + timedelta(minutes=180) > graph[path[i]][path[i + 1]][1]:
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print("Departure date and start time date do not match")
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return float('inf'), start_time, end_time
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length += graph[path[i]][path[i + 1]][0]
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end_time = graph[path[i]][path[i + 1]][2]
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start_time = end_time
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flight = graph[(path[i], path[i + 1])][0]
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length += flight[0]
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if i > 0: # Пропуск первой вершины
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if end_time + timedelta(minutes=180) > flight[1]:
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return float('inf'), start_time, end_time # Неприемлемый путь
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end_time = flight[2]
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return length, start_time, end_time
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def generate_population(size, start, end, graph, max_attempts=100):
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population = []
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nodes = list(set([k[0] for k in graph.keys()] + [k[1] for k in graph.keys()]))
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for i in range(size):
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attempts = 0
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while attempts < max_attempts:
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path = [start]
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visited = set(path)
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while path[-1] != end:
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if path[-1] not in graph or not graph[path[-1]]:
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next_nodes = [k[1] for k in graph.keys() if k[0] == path[-1]]
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if not next_nodes:
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break
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next_node = random.choice(list(graph[path[-1]].keys()))
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next_node = random.choice(next_nodes)
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if next_node in visited:
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break
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path.append(next_node)
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visited.add(next_node)
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# Если длина пути превышает количество узлов в графе, выйти из цикла
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if len(path) > len(graph):
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if len(path) > len(nodes):
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break
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if path[-1] == end:
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population.append(path)
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@ -132,9 +116,10 @@ def generate_population(size, start, end, graph, max_attempts=100):
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attempts += 1
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return population
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def select_parents(population, graph, departure_date):
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sorted_population = sorted(population, key=lambda p: path_length_and_time(p, graph, departure_date)[0])
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valid_parents = [p for p in sorted_population if path_length_and_time(p, graph, departure_date)[0] != float('inf')]
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def select_parents(population, graph):
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sorted_population = sorted(population, key=lambda p: path_length_and_time(p, graph)[0])
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valid_parents = [p for p in sorted_population if path_length_and_time(p, graph)[0] != float('inf')]
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return valid_parents[:len(valid_parents) // 2]
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@ -156,19 +141,20 @@ def mutate(child):
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return child
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def update_best_paths(best_paths, path, max_best_paths=10):
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def update_best_paths(best_paths, path, graph, max_best_paths=10):
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length, _, _ = path_length_and_time(path, graph)
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if path not in best_paths:
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best_paths[path] = None
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best_paths[path] = length
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if len(best_paths) > max_best_paths:
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worst_path = max(best_paths, key=best_paths.get)
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del best_paths[worst_path]
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def genetic_algorithm(start, end, graph, flights_data, type, departure_date, population_size=5, generations=5):
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def genetic_algorithm(start, end, graph, flights_data, type, departure_date, population_size=2000, generations=100):
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population = generate_population(population_size, start, end, graph)
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best_paths = {} # Словарь для хранения уникальных лучших маршрутов и их длин
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for generation in range(generations):
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parents = select_parents(population, graph, departure_date)
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parents = select_parents(population, graph)
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# Если не удалось выбрать родителей, завершить алгоритм
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if not parents:
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@ -183,7 +169,7 @@ def genetic_algorithm(start, end, graph, flights_data, type, departure_date, pop
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child = mutate(child)
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if child[-1] == end:
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new_population.append(child)
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update_best_paths(best_paths, tuple(child))
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update_best_paths(best_paths, tuple(child), graph)
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population = new_population
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best_paths = sorted(best_paths.items(), key=lambda item: item[1])
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@ -205,4 +191,4 @@ def genetic_algorithm(start, end, graph, flights_data, type, departure_date, pop
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type: path_data,
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})
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return result
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return result
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