TaskAllocator/mongo_insert.py at master · dmdin/TaskAllocator · GitHub

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from pymongo import MongoClient
import requests as r
import bson


def mongo_inserts():
    # Замените "your_connection_string" на строку подключения к вашему MongoDB
    # Например: "mongodb://username:password@localhost:27017/mydatabase"
    mongo_url = "mongodb://root:password@193.104.57.178:27017"

    # Создайте подключение к базе данных
    client = MongoClient(mongo_url)

    # Выберите базу данных (используйте ваше собственное имя базы данных)
    db = client["task-allocator"]

    # Выберите коллекцию, в которую вы хотите добавить запись (используйте ваше собственное имя коллекции)
    collection = db["branches"]

    def get_coord(address):
        return r.get('https://geocode-maps.yandex.ru/1.x?apikey=c8ec1e5f-24db-4383-8ae8-5f597a09d4ad&'
                          f'geocode="{address}"&lang=ru&format=json&results=1').json()['response']['GeoObjectCollection']['featureMember'][0]['GeoObject']['Point']['pos']


    def formatter(a: list) -> list:
        if len(a) == 6:
            a_0,a_1,a_2,a_3,a_4,a_5 = a[:6]
            coor = get_coord(a_0+', Краснодар').split()
            lon,lat = coor
            a_1 = int(a[1] == "давно")
            a_2 = int(a[2] == "да")
        else:
            a_0 = a[0]
            coor = get_coord(a_0).split()
            lon,lat = coor
            a_1,a_2,a_3,a_4,a_5 = [None]*5
        return ({
        "address":
         { "latitude": lat,
                "longitude": lon,
                "address": u''.join(a_0)
         },
        "connectionDate": a_1,
        "cardMaterialsDelivered": a_2,
        "lastCardIssuanceDays": int(a_3) if a_3 else a_3,
        "approvedIssuesNumber": int(a_4) if a_4 else a_4,
        "issuanceCardCount": int(a_5) if a_5 else a_5,
        "is_office": False if len(a) >= 6 else True
        }, lon,lat)

    # Определите данные, которые вы хотите добавить в коллекцию
    addresses = {}
    s = set()
    for i in [['ул. Ставропольская, д. 140', 'вчера', 'нет', '0', '0', '0'], ['ул. им. Максима Горького, д. 128', 'давно', 'да', '3', '15', '3'], ['ул. им. Дзержинского, д. 100', 'давно', 'да', '3', '9', '1'], ['ул. Красноармейская, д. 126', 'давно', 'да', '0', '38', '23'], ['х. Ленина, п/о. 37', 'давно', 'нет', '0', '14', '0'], ['тер. Пашковский жилой массив, ул. Крылатая, д. 2', 'давно', 'да', '12', '19', '1'], ['ул. Восточно-Кругликовская, д. 64/2', 'давно', 'да', '27', '19', '12'], ['ул. Красных Партизан, д. 439', 'давно', 'да', '33', '84', '63'], ['ул. Таманская, д. 153 к. 3, кв. 2', 'давно', 'да', '2', '15', '1'], ['ул. им. Дзержинского, д. 165', 'давно', 'да', '0', '19', '0'], ['ст-ца. Елизаветинская, ул. Широкая, д. 260', 'давно', 'да', '15', '29', '15'], ['ул. им. Тургенева, д. 174, 1 этаж', 'вчера', 'нет', '0', '0', '0'], ['ул. Уральская, д. 162', 'давно', 'да', '4', '21', '5'], ['ул. Уральская, д. 79/1', 'вчера', 'нет', '0', '5', '0'], ['ул. им. Селезнева, д. 197/5', 'давно', 'да', '7', '14', '3'], ['ул. Уральская, д. 117', 'вчера', 'нет', '0', '0', '0'], ['ул. им. 40-летия Победы, д. 20/1', 'давно', 'да', '4', '35', '15'], ['ул. им. Атарбекова, д. 24', 'вчера', 'нет', '0', '6', '0'], ['ул. им. Героя Аверкиева А.А., д. 8', 'давно', 'да', '6', '18', '6'], ['ул. им. Героя Аверкиева А.А., д. 8/1 к. мая, кв. 268', 'давно', 'да', '0', '15', '5'], ['ул. им. Тургенева, д. 106', 'давно', 'да', '2', '96', '20'], ['ул. Красных Партизан, д. 117', 'вчера', 'нет', '0', '0', '0'], ['ул. Северная, д. 389', 'давно', 'да', '0', '16', '0'], ['ул. Уральская, д. 166/3', 'давно', 'да', '3', '43', '29'], ['ул. Северная, д. 524', 'давно', 'да', '3', '13', '4'], ['ул. им. Кирилла Россинского, д. 61/1', 'давно', 'да', '6', '19', '5'], ['ул. Коммунаров, д. 258', 'давно', 'да', '16', '45', '30'], ['ул. им. Дзержинского, д. 100', 'давно', 'да', '1', '19', '4'], ['ул. Северная, д. 326', 'давно', 'да', '3', '20', '9'], ['ул. им. 40-летия Победы, д. 34', 'вчера', 'нет', '0', '19', '0'], ['ул. Красная, д. 176', 'давно', 'да', '76', '82', '72'], ['ул. Уральская, д. 79/1', 'давно', 'да', '23', '32', '21'], ['ул. Северная, д. 326', 'давно', 'да', '4', '19', '4'], ['ул. Красная, д. 149', 'давно', 'да', '9', '10', '7'], ['п. Березовый, ул. Целиноградская, д. 6/1', 'вчера', 'нет', '0', '13', '0'], ['ул. им. Дзержинского, д. 100', 'вчера', 'нет', '0', '10', '0'], ['ул. Российская, д. 418', 'давно', 'да', '6', '30', '14'], ['ул. им. Володи Головатого, д. 313', 'давно', 'да', '6', '65', '12'], ['ул. Красная, д. 145', 'давно', 'да', '3', '20', '4'], ['ул. Красная, д. 154', 'вчера', 'нет', '0', '0', '0'],
              ['Краснодар, Красная, д. 139'],['Краснодар, В.Н. Мачуги, 41'],['Краснодар, Красных Партизан, 321']]:
        if i[0] not in s:
            print(i[0])
            s.add(i[0])
            ins,lon,lat = formatter(i)
            addresses[i[0]] = (collection.insert_one(ins).inserted_id, (lon,lat))
    print()
    print(addresses)
    print(len(s))


def mongo_specialists():
    # Замените "your_connection_string" на строку подключения к вашему MongoDB
    # Например: "mongodb://username:password@localhost:27017/mydatabase"
    mongo_url = "mongodb://root:password@193.104.57.178:27017"

    # Создайте подключение к базе данных
    client = MongoClient(mongo_url)

    # Выберите базу данных (используйте ваше собственное имя базы данных)
    db = client["task-allocator"]

    # Выберите коллекцию, в которую вы хотите добавить запись (используйте ваше собственное имя коллекции)
    collection = db["specialists"]

    def get_coord(address):
            return r.get('https://geocode-maps.yandex.ru/1.x?apikey=c8ec1e5f-24db-4383-8ae8-5f597a09d4ad&'
                              f'geocode="{address}"&lang=ru&format=json&results=1').json()['response']['GeoObjectCollection']['featureMember'][0]['GeoObject']['Point']['pos']

    addresses = {}
    spe = {}
    specs = [['Дерягин Никита Владимирович', 'Краснодар, Красная, д. 139', 'Синьор'], ['Петрошев Валерий Павлович', 'Краснодар, Красная, д. 139', 'Мидл'], ['Евдокимов Давид Тихонович', 'Краснодар, Красная, д. 139', 'Джун'], ['Андреев Гордий Данилович', 'Краснодар, В.Н. Мачуги, 41', 'Синьор'], ['Иванов Адам Федорович', 'Краснодар, В.Н. Мачуги, 41', 'Мидл'], ['Бобылёв Ипполит Альбертович', 'Краснодар, В.Н. Мачуги, 41', 'Джун'], ['Беляева Евгения Антоновна', 'Краснодар, Красных Партизан, 321', 'Мидл'], ['Николаев Азарий Платонович', 'Краснодар, Красных Партизан, 321', 'Джун']]

    for spec in specs:
        f,i,o = spec[0].split()
        if spec[1] not in addresses:
            lon,lat = get_coord(spec[1]).split()
            addresses[spec[1]] = (lon,lat)
        else:
            lon,lat = addresses[spec[1]]
        id_ = collection.insert_one({'firstName': u''.join(i),'lastName': u''.join(f),'fatherName': u''.join(o), 'email': '-',
                               "level": ['Джун', 'Мидл', 'Синьор'].index(spec[2]),
                              "address":
         { "latitude": lat,
                "longitude": lon,
                "address": u''.join(spec[1])
         }}).inserted_id

        spe[f"{f} {i} {o}"] = id_
    print(spe)


def get_matrix(points): #lon,lat
    print(f"len_poin = {len(points)}")
    import csv
    import requests

    # Установите ваш ключ API GraphHopper
    api_key = "477b9de4-c4f2-4e05-8eb8-aaff7cd2eb2d"

    # Определите точки, между которыми вы хотите рассчитать матрицу времени проезда
    s = "https://graphhopper.com/api/1/matrix?"

    #with open('points_last.csv') as csvfile:
        #reader = csv.DictReader(csvfile)
    for i, (lon,lat) in enumerate(points):
        if not i:
            s += f"point={lat},{lon}"
        else:
            s += f"&point={lat},{lon}"

    #times = [ [ 0, 408, 549, 1524, 1339, 985, 777, 232, 1279, 1587, 1038, 952, 517, 905, 336, 885, 840, 796, 1012, 917, 950, 778, 978, 481, 954, 474, 1499, 583, 815, 614, 651, 656, 684, 1984, 1505, 1114, 623, 636, 574 ], [ 467, 0, 190, 1980, 1795, 1002, 459, 699, 961, 1269, 720, 1132, 840, 1085, 565, 870, 522, 588, 694, 934, 967, 460, 660, 272, 1134, 407, 1334, 265, 606, 296, 831, 338, 367, 1666, 1187, 954, 305, 318, 215 ], [ 604, 153, 0, 1888, 1704, 886, 276, 731, 778, 1086, 537, 1041, 749, 994, 474, 727, 339, 476, 511, 843, 875, 277, 477, 217, 1043, 316, 1151, 147, 495, 113, 740, 155, 184, 1483, 1004, 771, 122, 135, 134 ], [ 1579, 1825, 1940, 0, 727, 2161, 2118, 1512, 2595, 2928, 2379, 1160, 1171, 1178, 1458, 2061, 2116, 2058, 2353, 2093, 2126, 2119, 2319, 1758, 1126, 1651, 2176, 1924, 2074, 1955, 1546, 1997, 2026, 2602, 2781, 2291, 1964, 1977, 1965 ], [ 1398, 1644, 1759, 698, 0, 1980, 1938, 1331, 2414, 2747, 2198, 912, 990, 929, 1277, 1880, 1935, 1877, 2172, 1912, 1945, 1938, 2139, 1577, 877, 1470, 1927, 1744, 1894, 1774, 1366, 1817, 1845, 2354, 2346, 2110, 1784, 1796, 1784 ], [ 1085, 1062, 965, 2197, 2012, 0, 1009, 1040, 1130, 1818, 999, 1349, 1058, 1302, 782, 224, 672, 578, 1209, 433, 465, 1012, 1210, 858, 1352, 742, 679, 865, 531, 847, 1049, 1005, 796, 1417, 1085, 375, 972, 842, 963 ], [ 923, 520, 414, 2255, 2070, 1056, 0, 1098, 651, 809, 475, 1407, 1116, 1361, 840, 897, 509, 646, 235, 1081, 1114, 144, 201, 584, 1410, 682, 1321, 492, 665, 390, 1107, 302, 339, 1494, 908, 940, 386, 385, 412 ], [ 240, 486, 627, 1535, 1350, 1063, 855, 0, 1357, 1665, 1116, 973, 528, 947, 415, 963, 918, 875, 1090, 995, 1028, 856, 1056, 559, 975, 553, 1578, 661, 893, 692, 729, 734, 763, 2062, 1583, 1193, 701, 714, 652 ], [ 1286, 843, 737, 2565, 2380, 1127, 571, 1408, 0, 1380, 393, 1717, 1425, 1670, 1150, 968, 580, 717, 658, 1152, 1185, 585, 772, 884, 1719, 945, 1117, 666, 736, 619, 1416, 743, 568, 919, 333, 737, 744, 613, 735 ], [ 1575, 1172, 1065, 2907, 2722, 1705, 793, 1750, 1351, 0, 1175, 2059, 1768, 2012, 1492, 1546, 1158, 1296, 878, 1731, 1763, 793, 576, 1236, 2061, 1334, 1970, 1156, 1314, 1040, 1758, 954, 989, 1998, 1516, 1590, 1038, 1034, 1064 ], [ 1105, 662, 556, 2384, 2199, 946, 422, 1227, 417, 1231, 0, 1536, 1245, 1489, 969, 787, 399, 536, 509, 971, 1004, 436, 623, 703, 1538, 764, 1211, 485, 555, 438, 1235, 540, 387, 1259, 673, 831, 563, 433, 554 ], [ 1044, 1157, 1139, 1178, 993, 1360, 1317, 972, 1794, 2127, 1578, 0, 663, 156, 760, 1260, 1315, 1257, 1552, 1292, 1325, 1318, 1518, 957, 34, 850, 1874, 1123, 1273, 1154, 514, 1196, 1224, 2233, 1980, 1490, 1163, 1176, 1164 ], [ 562, 808, 806, 1204, 1019, 1027, 984, 495, 1461, 1794, 1245, 629, 0, 603, 324, 927, 982, 924, 1219, 959, 992, 985, 1185, 624, 631, 517, 1542, 790, 940, 821, 412, 863, 892, 2126, 1647, 1157, 830, 843, 831 ], [ 997, 1110, 1092, 1200, 1015, 1313, 1270, 946, 1747, 2080, 1531, 154, 637, 0, 734, 1213, 1268, 1210, 1505, 1245, 1278, 1271, 1471, 910, 120, 803, 1828, 1076, 1226, 1107, 467, 1149, 1178, 2412, 1933, 1443, 1116, 1129, 1117 ], [ 467, 643, 624, 1415, 1230, 846, 803, 400, 1280, 1612, 1064, 714, 276, 685, 0, 746, 801, 743, 1038, 778, 811, 803, 1004, 442, 716, 335, 1360, 609, 759, 640, 431, 682, 710, 1945, 1466, 975, 649, 661, 649 ], [ 912, 838, 781, 2024, 1839, 159, 826, 867, 973, 1635, 816, 1176, 884, 1129, 609, 0, 448, 354, 1026, 259, 292, 828, 1027, 684, 1178, 557, 622, 682, 307, 664, 875, 822, 612, 1320, 928, 278, 789, 658, 780 ], [ 947, 496, 395, 2132, 1947, 608, 439, 975, 614, 1248, 429, 1284, 993, 1237, 717, 449, 0, 284, 639, 708, 741, 441, 640, 475, 1286, 512, 908, 295, 303, 277, 983, 435, 226, 1240, 761, 528, 402, 271, 393 ], [ 969, 616, 597, 2081, 1896, 518, 638, 924, 814, 1448, 629, 1233, 942, 1186, 666, 359, 335, 0, 838, 469, 501, 641, 839, 469, 1235, 461, 899, 495, 52, 476, 932, 634, 425, 1479, 1000, 519, 601, 471, 593 ], [ 1051, 648, 542, 2383, 2198, 1167, 269, 1226, 688, 926, 512, 1535, 1244, 1489, 968, 1008, 620, 757, 0, 1192, 1225, 270, 318, 712, 1538, 810, 1432, 632, 776, 516, 1235, 430, 465, 1530, 944, 1051, 514, 511, 540 ], [ 945, 918, 899, 2057, 1872, 315, 979, 900, 1154, 1788, 969, 1209, 918, 1162, 642, 215, 662, 472, 1179, 0, 52, 981, 1180, 717, 1211, 601, 829, 835, 425, 817, 908, 957, 766, 1535, 1142, 493, 924, 811, 924 ], [ 973, 946, 927, 2084, 1900, 342, 1006, 927, 1182, 1816, 996, 1237, 945, 1190, 669, 242, 690, 500, 1206, 52, 0, 1009, 1207, 745, 1239, 629, 856, 863, 453, 844, 936, 985, 793, 1562, 1170, 520, 952, 839, 952 ], [ 831, 428, 322, 2163, 1979, 964, 38, 1006, 558, 847, 382, 1316, 1024, 1269, 749, 805, 417, 554, 272, 989, 1022, 0, 239, 492, 1318, 591, 1229, 401, 573, 299, 1015, 210, 247, 1400, 815, 849, 295, 293, 320 ], [ 1027, 624, 518, 2359, 2174, 1157, 245, 1202, 803, 623, 628, 1511, 1220, 1464, 944, 998, 610, 748, 330, 1183, 1215, 246, 0, 688, 1513, 786, 1422, 608, 766, 492, 1210, 406, 441, 1646, 1060, 1042, 490, 487, 516 ], [ 652, 201, 182, 1875, 1690, 820, 361, 718, 862, 1170, 621, 1027, 736, 980, 460, 662, 423, 380, 595, 771, 804, 361, 562, 0, 1029, 302, 1201, 167, 398, 197, 726, 240, 268, 1567, 1088, 821, 207, 219, 207 ], [ 1033, 1160, 1141, 1144, 959, 1362, 1319, 966, 1796, 2129, 1580, 34, 657, 121, 754, 1262, 1317, 1259, 1554, 1294, 1327, 1320, 1520, 959, 0, 852, 1877, 1125, 1275, 1156, 516, 1198, 1227, 2199, 1982, 1492, 1165, 1178, 1166 ], [ 511, 345, 327, 1623, 1438, 645, 505, 466, 994, 1315, 766, 775, 483, 728, 208, 545, 515, 457, 740, 577, 609, 506, 706, 145, 777, 0, 1110, 311, 473, 342, 474, 384, 412, 1659, 1180, 730, 351, 364, 351 ], [ 1529, 1345, 1243, 2171, 1986, 732, 1287, 1484, 1105, 2097, 1277, 1689, 1502, 1746, 1226, 622, 948, 937, 1487, 880, 912, 1290, 1488, 1274, 1654, 1140, 0, 1144, 890, 1125, 1493, 1283, 1074, 1392, 1060, 519, 1250, 1120, 1241 ], [ 652, 201, 183, 1914, 1729, 840, 361, 757, 739, 1170, 512, 1066, 775, 1019, 499, 682, 294, 431, 596, 854, 886, 362, 562, 224, 1068, 341, 1105, 0, 449, 199, 765, 240, 148, 1438, 959, 725, 207, 193, 207 ], [ 943, 626, 607, 2055, 1870, 492, 649, 898, 824, 1458, 639, 1207, 915, 1160, 640, 333, 345, 142, 848, 442, 475, 651, 850, 479, 1209, 435, 873, 505, 0, 486, 906, 644, 435, 1489, 1010, 493, 611, 481, 603 ], [ 713, 269, 163, 1990, 1805, 791, 229, 833, 683, 1039, 442, 1142, 850, 1095, 575, 632, 244, 382, 464, 817, 849, 232, 430, 310, 1144, 417, 1056, 161, 400, 0, 841, 203, 89, 1388, 909, 676, 170, 40, 161 ], [ 674, 787, 769, 1611, 1426, 990, 947, 664, 1424, 1757, 1208, 566, 472, 519, 414, 890, 945, 887, 1182, 922, 955, 948, 1148, 587, 568, 480, 1504, 753, 903, 784, 0, 826, 854, 2089, 1610, 1120, 793, 806, 793 ], [ 661, 218, 112, 1953, 1768, 913, 245, 796, 770, 1054, 529, 1105, 814, 1059, 538, 754, 366, 503, 479, 907, 940, 245, 446, 282, 1108, 380, 1178, 190, 522, 140, 805, 0, 199, 1510, 1027, 798, 84, 162, 110 ], [ 719, 275, 169, 1995, 1811, 824, 235, 838, 688, 1044, 447, 1148, 856, 1101, 581, 665, 277, 414, 470, 849, 882, 238, 436, 316, 1150, 423, 1089, 167, 433, 51, 847, 209, 0, 1421, 945, 709, 176, 46, 167 ], [ 1819, 1368, 1266, 2404, 2219, 1173, 1254, 1851, 684, 1750, 1076, 1922, 1868, 1939, 1593, 1028, 971, 1156, 1342, 1287, 1320, 1269, 1455, 1346, 1887, 1384, 1149, 1166, 1170, 1148, 1859, 1306, 1097, 0, 808, 768, 1273, 1142, 1264 ], [ 1625, 1182, 1076, 2616, 2431, 1137, 910, 1683, 339, 1507, 732, 1992, 1700, 1945, 1425, 978, 808, 992, 997, 1237, 1270, 924, 1111, 1182, 1994, 1220, 1135, 1005, 1006, 958, 1691, 1082, 907, 938, 0, 755, 1083, 952, 1074 ], [ 1170, 943, 841, 2282, 2097, 447, 886, 1125, 755, 1695, 876, 1434, 1142, 1387, 867, 302, 547, 535, 1085, 561, 594, 888, 1087, 872, 1436, 739, 422, 742, 489, 723, 1133, 881, 672, 1042, 710, 0, 848, 718, 840 ], [ 693, 250, 143, 1985, 1800, 961, 347, 828, 853, 1156, 612, 1137, 846, 1090, 570, 802, 414, 551, 581, 939, 972, 347, 548, 314, 1139, 412, 1226, 238, 570, 188, 836, 223, 258, 1558, 1079, 846, 0, 210, 142 ], [ 777, 333, 227, 2054, 1869, 877, 225, 897, 679, 1035, 438, 1206, 914, 1159, 639, 718, 330, 468, 460, 902, 935, 228, 426, 374, 1208, 481, 1142, 242, 486, 160, 905, 211, 109, 1474, 936, 762, 201, 0, 225 ], [ 649, 198, 45, 1933, 1748, 931, 321, 776, 823, 1130, 582, 1085, 794, 1038, 518, 772, 384, 521, 556, 887, 920, 321, 522, 262, 1088, 360, 1196, 192, 540, 158, 785, 200, 228, 1528, 1049, 815, 167, 179, 0 ] ]

    times_matrix = {}

    #for i in range(len(points)):
    #    for j in range(i+1, len(points)):
    #        times_matrix[(points[i], points[j])] = (times[i][j], True)
    s += "&type=json&profile=car&out_array=times&out_array=distances&key=477b9de4-c4f2-4e05-8eb8-aaff7cd2eb2d"
    print(s)
    matrix = 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946,10486,11014,5183,13985],[5639,3619,10711,3418,22087,12676,5868,5762,4657,9349,19131,6681,7796,4467,5270,7511,4107,7749,5047,5047,5628,9066,1658,7873,0,9854,3209,4182,4251,3760,4509,16082,7583,3479,3898,3438,3966,8455,6936],[12154,11014,8007,10527,33127,23715,4453,10789,11171,9731,24158,9983,20299,10981,11785,14026,7021,11419,5352,5352,10687,14093,9773,20132,10000,0,9301,10971,6705,9384,8947,10340,3095,10268,9266,10272,9334,14970,11963],[6148,1713,8291,1512,24254,14842,6098,3856,6823,6711,17225,3750,9963,6633,7437,9678,3652,5843,6348,6348,3722,7160,1619,10040,2167,9338,0,2276,3795,1679,1241,13662,7067,1573,1561,1531,1628,10622,5030],[6375,1937,7714,1018,24832,15421,7016,2739,7402,6461,16109,3641,10541,7212,8015,10256,4569,4726,7792,7792,2606,6043,2227,10618,2745,10256,1577,0,4713,1189,1518,14580,7985,403,1326,763,1394,11200,3914],[8086,5196,8655,4995,24534,15122,3460,5710,7104,7292,19079,4904,10243,6914,7717,9958,842,6341,2600,2600,5609,9014,3594,10320,3821,6723,4223,5893,0,4306,3868,14026,4452,5190,4188,5194,4255,10902,6884],[6807,2369,8071,1449,24897,15485,5878,2064,7466,5792,15433,2972,10605,7276,8080,10320,3432,4051,6157,6157,1963,5368,2377,10683,2810,9118,730,1894,3576,0,800,13442,6848,1191,189,1195,256,11265,3238],[6938,2500,6798,1580,25028,15616,6265,2195,7597,5544,15564,2725,10736,7407,8211,10451,3818,4182,6544,6544,2093,5499,2508,10813,2940,9505,861,2024,3962,437,0,13829,7234,1322,319,1325,387,11396,3369],[19024,14589,8344,14101,44284,34872,11246,12020,17984,6910,24138,9711,31456,17794,18597,31635,12762,11871,12146,12146,12114,15324,14293,31289,14520,10572,12876,14546,12632,12959,12521,0,8301,13843,12841,13847,12908,21782,13194],[11058,9021,6341,8534,27506,18094,3338,8795,10075,8066,22165,7990,13214,9885,10689,12929,5028,9426,4238,4238,8694,12099,7780,13292,8007,2663,7308,8978,4711,7391,6954,8688,0,8275,7273,8279,7341,13874,9970],[6192,1754,9344,834,24649,15237,7151,3178,7218,7065,16547,4245,10357,7028,7832,10072,4705,5165,7609,7609,3044,6482,2044,10435,2562,10391,1712,1501,4849,1324,2073,14715,8121,0,1462,580,1529,11017,4352],[7066,2628,6956,1708,25156,15744,6349,1975,7725,5703,15344,2883,10864,7535,8339,10580,3903,3962,6628,6628,1874,5279,2637,10942,3069,9589,1766,1652,4047,1197,760,13913,7319,1103,0,1454,1147,11524,3149],[5878,1443,9262,174,24338,14926,7069,3244,6907,6983,16613,4163,10046,6717,7521,9761,4623,5231,7298,7298,3110,6548,1733,10124,2251,10309,1418,1664,4767,1242,1991,14633,8039,961,1380,0,1447,10706,4418],[6551,2113,8882,1193,24641,15229,6689,3217,7210,6603,16587,3783,10349,7020,7824,10064,4243,5204,6968,6968,3083,6521,2121,10426,2553,9929,1250,1637,4387,862,1611,14253,7659,934,1000,938,0,11009,4392],[6320,8388,16236,9347,16066,6654,10117,11691,5186,14873,25060,12610,5306,4056,1786,5182,9631,13678,9296,9296,11557,14995,7587,5383,7405,13834,9137,10111,9696,9689,10438,21607,12450,9408,9827,9366,9894,0,12865],[9666,5696,8478,4776,28591,19179,8881,2109,11160,7224,12252,4571,14299,10970,11774,14014,6435,1145,9161,9161,1975,2187,5986,14377,6504,12122,4464,3758,6579,4041,3603,14622,9851,4162,3923,4522,3990,14959,0]],"times":[[0,408,1505,549,1524,1339,985,777,249,1279,1587,1038,952,634,517,905,796,1012,917,917,778,978,481,954,476,1499,583,656,815,614,684,1984,1114,623,636,574,629,702,851],[467,0,1187,190,1980,1795,1002,459,716,961,1269,720,1132,814,840,1085,588,694,934,934,460,660,272,1134,276,1334,265,338,606,296,367,1666,954,305,318,215,311,1158,533],[1625,1182,0,1076,2616,2431,1137,910,1699,339,1507,732,1992,1674,1700,1945,992,997,1237,1237,924,1111,1182,1994,1179,1135,1005,1082,1006,958,907,938,755,1083,952,1074,946,2018,984],[604,153,1004,0,1888,1704,886,276,748,778,1086,537,1041,723,749,994,476,511,843,843,277,477,217,1043,184,1151,147,155,495,113,184,1483,771,122,135,134,128,1067,350],[1579,1825,2781,1940,0,727,2161,2118,1528,2595,2928,2379,1160,1529,1171,1178,2058,2353,2093,2093,2119,2319,1758,1126,1778,2176,1924,1997,2074,1955,2026,2602,2291,1964,1977,1965,1970,972,2192],[1398,1644,2346,1759,698,0,1980,1938,1347,2414,2747,2198,912,1349,990,929,1877,2172,1912,1912,1938,2139,1577,877,1597,1927,1744,1817,1894,1774,1845,2354,2110,1784,1796,1784,1789,791,2011],[1085,1062,1085,965,2197,2012,0,1009,1057,1130,1818,999,1349,1032,1058,1302,578,1209,433,433,1012,1210,858,1352,878,679,865,1005,531,847,796,1417,375,972,842,963,835,1375,1083],[923,520,908,414,2255,2070,1056,0,1115,651,809,475,1407,1090,1116,1361,646,235,1081,1081,144,201,584,1410,551,1321,492,302,665,390,339,1494,940,386,385,412,378,1434,74],[257,503,1600,644,1552,1367,1080,872,0,1374,1681,1133,990,729,544,964,891,1107,1012,1012,872,1073,576,992,571,1594,678,751,910,709,779,2079,1209,718,730,668,724,730,946],[1286,843,333,737,2565,2380,1127,571,1424,0,1380,393,1717,1399,1425,1670,717,658,1152,1152,585,772,884,1719,859,1117,666,743,736,619,568,919,737,744,613,735,606,1743,645],[1575,1172,1516,1065,2907,2722,1705,793,1767,1351,0,1175,2059,1741,1768,2012,1296,878,1731,1731,793,576,1236,2061,1203,1970,1156,954,1314,1040,989,1998,1590,1038,1034,1064,1028,2085,717],[1105,662,673,556,2384,2199,946,422,1244,417,1231,0,1536,1218,1245,1489,536,509,971,971,436,623,703,1538,678,1211,485,540,555,438,387,1259,831,563,433,554,426,1562,496],[1044,1157,1980,1139,1178,993,1360,1317,989,1794,2127,1578,0,523,663,156,1257,1552,1292,1292,1318,1518,957,34,977,1874,1123,1196,1273,1154,1224,2233,1490,1163,1176,1164,1169,673,1391],[683,796,1619,777,1583,1398,999,956,689,1433,1765,1217,523,0,444,476,896,1191,931,931,957,1157,596,525,616,1513,762,835,912,793,863,2098,1129,802,815,802,808,722,1030],[562,808,1647,806,1204,1019,1027,984,512,1461,1794,1245,629,395,0,603,924,1219,959,959,985,1185,624,631,644,1542,790,863,940,821,892,2126,1157,830,843,831,836,382,1058],[997,1110,1933,1092,1200,1015,1313,1270,963,1747,2080,1531,154,476,637,0,1210,1505,1245,1245,1271,1471,910,120,930,1828,1076,1149,1226,1107,1178,2412,1443,1116,1129,1117,1122,669,1344],[969,616,1000,597,2081,1896,518,638,941,814,1448,629,1233,915,942,1186,0,838,469,469,641,839,469,1235,466,899,495,634,52,476,425,1479,519,601,471,593,464,1259,712],[1051,648,944,542,2383,2198,1167,269,1243,688,926,512,1535,1218,1244,1489,757,0,1192,1192,270,318,712,1538,679,1432,632,430,776,516,465,1530,1051,514,511,540,504,1562,191],[945,918,1142,899,2057,1872,315,979,917,1154,1788,969,1209,891,918,1162,472,1179,0,0,981,1180,717,1211,738,829,835,957,425,817,766,1535,493,924,811,924,805,1235,1053],[945,918,1142,899,2057,1872,315,979,917,1154,1788,969,1209,891,918,1162,472,1179,0,0,981,1180,717,1211,738,829,835,957,425,817,766,1535,493,924,811,924,805,1235,1053],[831,428,815,322,2163,1979,964,38,1023,558,847,382,1316,998,1024,1269,554,272,989,989,0,239,492,1318,459,1229,401,210,573,299,247,1400,849,295,293,320,286,1342,112],[1027,624,1060,518,2359,2174,1157,245,1219,803,623,628,1511,1193,1220,1464,748,330,1183,1183,246,0,688,1513,655,1422,608,406,766,492,441,1646,1042,490,487,516,480,1537,169],[652,201,1088,182,1875,1690,820,361,735,862,1170,621,1027,709,736,980,380,595,771,771,361,562,0,1029,171,1201,167,240,398,197,268,1567,821,207,219,207,212,1053,435],[1033,1160,1982,1141,1144,959,1362,1319,983,1796,2129,1580,34,525,657,121,1259,1554,1294,1294,1320,1520,959,0,979,1877,1125,1198,1275,1156,1227,2199,1492,1165,1178,1166,1171,639,1393],[592,418,1258,400,1704,1519,726,578,564,1072,1388,839,856,539,565,809,535,813,658,658,579,779,218,858,0,1192,384,457,553,415,486,1737,812,424,437,425,430,882,652],[1529,1345,1060,1243,2171,1986,732,1287,1501,1105,2097,1277,1689,1476,1502,1746,937,1487,880,880,1290,1488,1274,1654,1271,0,1144,1283,890,1125,1074,1392,519,1250,1120,1241,1113,1819,1361],[652,201,959,183,1914,1729,840,361,774,739,1170,512,1066,749,775,1019,431,596,854,854,362,562,224,1068,210,1105,0,240,449,199,148,1438,725,207,193,207,187,1092,435],[661,218,1027,112,1953,1768,913,245,813,770,1054,529,1105,788,814,1059,503,479,907,907,245,446,282,1108,249,1178,190,0,522,140,199,1510,798,84,162,110,155,1132,319],[943,626,1010,607,2055,1870,492,649,914,824,1458,639,1207,889,915,1160,142,848,442,442,651,850,479,1209,476,873,505,644,0,486,435,1489,493,611,481,603,474,1233,722],[713,269,909,163,1990,1805,791,229,849,683,1039,442,1142,824,850,1095,382,464,817,817,232,430,310,1144,286,1056,161,203,400,0,89,1388,676,170,40,161,33,1168,303],[719,275,945,169,1995,1811,824,235,855,688,1044,447,1148,830,856,1101,414,470,849,849,238,436,316,1150,291,1089,167,209,433,51,0,1421,709,176,46,167,39,1174,309],[1819,1368,808,1266,2404,2219,1173,1254,1867,684,1750,1076,1922,1842,1868,1939,1156,1342,1287,1287,1269,1455,1346,1887,1343,1149,1166,1306,1170,1148,1097,0,768,1273,1142,1264,1136,2186,1328],[1170,943,710,841,2282,2097,447,886,1141,755,1695,876,1434,1116,1142,1387,535,1085,561,561,888,1087,872,1436,869,422,742,881,489,723,672,1042,0,848,718,840,711,1460,959],[693,250,1079,143,1985,1800,961,347,845,853,1156,612,1137,819,846,1090,551,581,939,939,347,548,314,1139,281,1226,238,223,570,188,258,1558,846,0,210,142,203,1163,420],[777,333,936,227,2054,1869,877,225,913,679,1035,438,1206,888,914,1159,468,460,902,902,228,426,374,1208,349,1142,242,211,486,160,109,1474,762,201,0,225,147,1232,299],[649,198,1049,45,1933,1748,931,321,793,823,1130,582,1085,768,794,1038,521,556,887,887,321,522,262,1088,229,1196,192,200,540,158,228,1528,815,167,179,0,172,1111,395],[680,237,985,130,1957,1772,867,291,816,759,1101,518,1109,791,818,1062,458,526,893,893,292,492,277,1111,253,1132,145,170,476,94,165,1464,752,137,116,128,0,1135,365],[607,853,1809,968,1068,883,1190,1147,557,1624,1956,1407,650,558,199,624,1087,1381,1121,1121,1147,1348,786,653,806,1704,953,1026,1103,984,1054,2288,1319,993,1005,993,998,0,1221],[970,567,1003,461,2302,2117,1100,188,1162,746,746,571,1454,1136,1163,1407,691,222,1126,1126,189,137,631,1456,598,1365,551,349,709,435,384,1589,985,433,430,459,423,1480,0]]}

    matrix = matrix['times']
    ids = ['654aa10dbff6a11489a510ef', '654aa10ebff6a11489a510f0', '654aa10ebff6a11489a510f1', '654aa10ebff6a11489a510f2', '654aa10ebff6a11489a510f3', '654aa112bff6a11489a510f4', '654aa113bff6a11489a510f5', '654aa114bff6a11489a510f6', '654aa114bff6a11489a510f7', '654aa114bff6a11489a510f8', '654aa115bff6a11489a510f9', '654aa115bff6a11489a510fa', '654aa115bff6a11489a510fb', '654aa115bff6a11489a510fc', '654aa115bff6a11489a510fd', '654aa115bff6a11489a510fe', '654aa116bff6a11489a510ff', '654aa117bff6a11489a51100', '654aa118bff6a11489a51101', '654aa119bff6a11489a51102', '654aa119bff6a11489a51103', '654aa119bff6a11489a51104', '654aa119bff6a11489a51105', '654aa119bff6a11489a51106', '654aa11abff6a11489a51107', '654aa11abff6a11489a51108', '654aa11abff6a11489a51109', '654aa11bbff6a11489a5110a', '654aa11bbff6a11489a5110b', '654aa11bbff6a11489a5110c', '654aa11bbff6a11489a5110d', '654aa11cbff6a11489a5110e', '654aa11cbff6a11489a5110f', '654aa11cbff6a11489a51110', '654aa11cbff6a11489a51111', '654aa11cbff6a11489a51112', '654aa11dbff6a11489a51113', '654aa11dbff6a11489a51114', '654aa11dbff6a11489a51115']
    print(len(matrix), len(matrix[0]), len(ids))
    # Замените "your_connection_string" на строку подключения к вашему MongoDB
    # Например: "mongodb://username:password@localhost:27017/mydatabase"
    mongo_url = "mongodb://root:password@193.104.57.178:27017"

    # Создайте подключение к базе данных
    client = MongoClient(mongo_url)

    # Выберите базу данных (используйте ваше собственное имя базы данных)
    db = client["task-allocator"]

    # Выберите коллекцию, в которую вы хотите добавить запись (используйте ваше собственное имя коллекции)
    collection = db["from_to_in_minutes"]
    fr_to_minutes = {}
    fr_inner_dict_to_minutes = {}

    for i in range(len(ids)):
        for j in range(i+1, len(ids)):
            from_id, to_id, minutes = ids[i], ids[j], matrix[i][j]
            fr_to_minutes[(from_id, to_id)] = minutes
            if from_id not in fr_inner_dict_to_minutes:
                fr_inner_dict_to_minutes[from_id] = {}
            fr_inner_dict_to_minutes[from_id][to_id] = minutes
            id_ = collection.insert_one({'from': from_id, 'to': to_id, 'minutes': minutes/60}).inserted_id

def generate_table_with_minutes():
    d = {'ул. Ставропольская, д. 140': (('654aa10dbff6a11489a510ef'), ('39.003879', '45.019844')), 'ул. им. Максима Горького, д. 128': (('654aa10ebff6a11489a510f0'), ('38.979517', '45.030113')), 'ул. им. Дзержинского, д. 100': (('654aa10ebff6a11489a510f1'), ('38.983856', '45.102209')), 'ул. Красноармейская, д. 126': (('654aa10ebff6a11489a510f2'), ('38.977244', '45.037961')), 'х. Ленина, п/о. 37': (('654aa10ebff6a11489a510f3'), ('39.242822', '45.036904')), 'тер. Пашковский жилой массив, ул. Крылатая, д. 2': (('654aa112bff6a11489a510f4'), ('39.122574', '45.01144')), 'ул. Восточно-Кругликовская, д. 64/2': (('654aa113bff6a11489a510f5'), ('39.025637', '45.068257')), 'ул. Красных Партизан, д. 439': (('654aa114bff6a11489a510f6'), ('38.956475', '45.051538')), 'ул. Таманская, д. 153 к. 3, кв. 2': (('654aa114bff6a11489a510f7'), ('39.012809', '45.023609')), 'ул. им. Дзержинского, д. 165': (('654aa114bff6a11489a510f8'), ('38.976481', '45.090285')), 'ст-ца. Елизаветинская, ул. Широкая, д. 260': (('654aa115bff6a11489a510f9'), ('38.803393', '45.049488')), 'ул. им. Тургенева, д. 174, 1 этаж': (('654aa115bff6a11489a510fa'), ('38.970211', '45.069792')), 'ул. Уральская, д. 162': (('654aa115bff6a11489a510fb'), ('39.094052', '45.038534')), 'ул. Уральская, д. 79/1': (('654aa115bff6a11489a510fc'), ('39.051463', '45.035273')), 'ул. им. Селезнева, д. 197/5': (('654aa115bff6a11489a510fd'), ('39.054428', '45.016556')), 'ул. Уральская, д. 117': (('654aa115bff6a11489a510fe'), ('39.091735', '45.039203')), 'ул. им. 40-летия Победы, д. 20/1': (('654aa116bff6a11489a510ff'), ('39.001418', '45.054767')), 'ул. им. Атарбекова, д. 24': (('654aa117bff6a11489a51100'), ('38.949172', '45.059128')), 'ул. им. Героя Аверкиева А.А., д. 8': (('654aa118bff6a11489a51101'), ('39.029266', '45.060211')), 'ул. им. Героя Аверкиева А.А., д. 8/1 к. мая, кв. 268': (('654aa119bff6a11489a51102'), ('39.029266', '45.060211')), 'ул. им. Тургенева, д. 106': (('654aa119bff6a11489a51103'), ('38.959835', '45.052175')), 'ул. Красных Партизан, д. 117': (('654aa119bff6a11489a51104'), ('38.919267', '45.063381')), 'ул. Северная, д. 389': (('654aa119bff6a11489a51105'), ('38.993378', '45.037706')), 'ул. Уральская, д. 166/3': (('654aa119bff6a11489a51106'), ('39.095624', '45.038942')), 'ул. Северная, д. 524': (('654aa11abff6a11489a51107'), ('39.000753', '45.035935')), 'ул. им. Кирилла Россинского, д. 61/1': (('654aa11abff6a11489a51108'), ('39.036991', '45.088866')), 'ул. Коммунаров, д. 258': (('654aa11abff6a11489a51109'), ('38.981691', '45.043693')), 'ул. Северная, д. 326': (('654aa11bbff6a11489a5110a'), ('38.970795', '45.040445')), 'ул. им. 40-летия Победы, д. 34': (('654aa11bbff6a11489a5110b'), ('39.003736', '45.054684')), 'ул. Красная, д. 176': (('654aa11bbff6a11489a5110c'), ('38.978915', '45.046463')), 'ул. Красная, д. 149': (('654aa11bbff6a11489a5110d'), ('38.978161', '45.048348')), 'п. Березовый, ул. Целиноградская, д. 6/1': (('654aa11cbff6a11489a5110e'), ('38.998561', '45.145759')), 'ул. Российская, д. 418': (('654aa11cbff6a11489a5110f'), ('39.014929', '45.085277')), 'ул. им. Володи Головатого, д. 313': (('654aa11cbff6a11489a51110'), ('38.974307', '45.039464')), 'ул. Красная, д. 145': (('654aa11cbff6a11489a51111'), ('38.977685', '45.046718')), 'ул. Красная, д. 154': (('654aa11cbff6a11489a51112'), ('38.975636', '45.037165')), 'Краснодар, Красная, д. 139': (('654aa11dbff6a11489a51113'), ('38.977047', '45.04496')), 'Краснодар, В.Н. Мачуги, 41': (('654aa11dbff6a11489a51114'), ('39.071711', '45.012835')), 'Краснодар, Красных Партизан, 321': (('654aa11dbff6a11489a51115'), ('38.941986', '45.053773'))}
    points = []#(float(i[1][0]), float(i[1][1])) for i in d.values()]
    fr_to = {}
    k = list(d.keys())
    print(len(k))
    ids = []
    for i in range(len(k)):
        #for j in range(i+1, len(k)):
            v = d[k[i]]
            points.append((float(v[1][0]), float(v[1][1])))
            ids.append(v[0])
            fr_to[(float(v[1][0]), float(v[1][1]))] = 1
    print(f"ids = {ids}")
    get_matrix(points) #lon,lat
    #fr[]collection.insert_one(ins).inserted_id


generate_table_with_minutes()