Colombia, officially the Republic of Colombia,is a country mostly in South America with insular regions in North America. The Colombian mainland is bordered by the Caribbean Sea to the north, Venezuela to the east and northeast, Brazil to the southeast, Ecuador and Peru to the south and southwest, the Pacific Ocean to the west, and Panama to the northwest. Colombia is divided into 32 departments. The Capital is Bogotá.
The more catches you post, the higher your chances of winning this amazing prize.
Every catch shared between May and November 2025 is automatically entered into the prize draw.
Only one rule: Make sure to tag both the fish species and the body of water!
| 1 x Application (95.23%) | 444ms |
| 1 x Booting (4.77%) | 22.23ms |
select * from `sessions` where `id` = '2NiZO6N1bvRZJotIiSMETpOuUEgpMrL379TGAAVv' limit 1| Bindings |
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select * from `countries` where `alias` = 'colombia' and `published` = 1 limit 1| Bindings |
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select * from `translations` where `lang` = 'en' and `translations`.`translatable_id` in (54) and `translations`.`translatable_type` = 'App\\Models\\Country'| Bindings |
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select `continents`.*, `continent_country`.`country_id` as `pivot_country_id`, `continent_country`.`continent_id` as `pivot_continent_id` from `continents` inner join `continent_country` on `continents`.`id` = `continent_country`.`continent_id` where `continent_country`.`country_id` in (54)| Backtrace |
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select * from `translations` where `lang` = 'en' and `translations`.`translatable_id` in (5) and `translations`.`translatable_type` = 'App\\Models\\Continent'| Bindings |
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select `waters`.*, `country_water`.`country_id` as `pivot_country_id`, `country_water`.`water_id` as `pivot_water_id` from `waters` inner join `country_water` on `waters`.`id` = `country_water`.`water_id` where `country_water`.`country_id` = 54| Bindings |
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select * from `translations` where `lang` = 'en' and `translations`.`translatable_id` in (41, 375, 444, 446, 576, 598, 599, 607) and `translations`.`translatable_type` = 'App\\Models\\Water'| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 41| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (142, 145, 170, 194, 220, 221, 232, 238, 239, 240, 241, 242, 243, 244, 257, 260, 261, 262, 263, 265, 267, 269, 271, 275, 278, 284, 285, 286, 288, 290, 291, 293, 295, 297, 300, 304, 308, 310, 314, 315, 317, 319, 321, 323, 326, 329, 332, 334, 336, 337, 338, 339, 344, 347, 351, 352, 354, 356, 357, 359, 362, 363, 365, 367, 368, 372, 374, 375, 376, 377, 380, 384, 385, 388, 397, 400, 401, 403, 404, 405, 406, 410, 411, 416, 417, 418, 419, 422, 424, 427, 437, 439, 441, 443, 444, 446, 447, 448, 464, 468, 471, 473, 477, 480, 483, 486, 489, 490, 493, 496, 499, 508, 509, 513, 517, 524, 589, 634, 657, 663, 664, 687, 700, 710, 713, 714, 720, 797, 798, 800, 801, 805, 810, 812, 815, 817, 835, 896, 926, 929, 932, 934, 936, 937, 939, 940, 941, 944, 945, 946, 947, 951, 953, 954, 956, 957, 959, 960, 964, 966, 970, 983, 984, 986, 988, 995, 996, 998, 1001, 1002, 1003, 1006, 1007, 1008, 1012, 1018, 1022, 1024, 1025, 1031, 1033, 1040, 1043, 1046, 1047, 1050, 1052, 1053, 1054, 1055, 1058, 1059, 1060, 1088, 1093, 1098, 1101, 1102, 1113, 1137, 1138, 1145, 1149, 1153, 1156, 1159, 1162, 1173, 1212, 1214, 1230, 1232, 1236, 1239, 1242, 1251, 1255, 1256, 1257, 1262, 1265, 1266, 1267, 1268, 1272, 1276, 1278, 1279, 1280, 1282, 1314, 1315, 1321, 1333, 1335, 1338, 1348, 1349, 1352, 1380, 1398, 1402, 1407, 1415, 1425, 1426, 1427, 1445, 1499, 1523, 1524, 1546, 1547, 1549, 1551, 1584, 1586, 1590, 1598, 1599, 1600, 1602, 1603, 1604, 1605, 1606, 1611, 1612, 1614, 1615, 1618, 1619, 1621, 1624, 1627, 1629, 1631, 1632, 1643, 1654, 1659, 1675, 1684, 1686, 1690, 1692, 1694, 1697, 1698, 1719, 1723, 1724, 1725, 1752, 1753, 1754, 1761, 1768, 1797, 1798, 1817, 1840, 1858, 1862, 1873, 1877, 1886, 1890, 1898, 1908, 1910, 1914, 1934, 1939, 1946, 1947, 1954, 1970, 1971, 2010, 2020, 2050, 2059, 2060, 2063, 2069, 2071, 2081, 2084, 2085, 2086, 2087, 2089, 2091, 2092, 2093, 2099, 2101, 2103, 2106, 2108, 2109, 2110, 2111, 2129, 2143, 2147, 2151, 2154, 2161, 2162, 2163, 2166, 2168, 2170, 2175, 2181, 2183, 2197, 2199, 2201, 2217, 2220, 2224, 2226, 2237, 2246, 2249, 2250, 2261, 2262, 2269, 2271, 2272, 2273, 2274, 2275, 2276, 2278, 2292, 2294, 2295, 2296, 2297, 2300, 2302, 2317, 2319, 2320, 2321, 2322, 2323, 2324, 2329, 2332, 2335, 2338, 2339, 2342, 2345, 2348, 2349, 2354, 2355, 2358, 2361, 2362, 2365, 2366, 2368, 2370, 2372, 2374, 2375, 2377, 2379, 2380, 2382, 2383, 2386, 2391, 2393, 2395, 2396, 2399, 2401, 2402, 2404, 2406, 2410, 2412, 2413, 2415, 2417, 2418, 2419, 2422, 2424, 2426, 2428, 2429, 2430, 2433, 2434, 2436, 2437, 2439, 2444, 2454, 2455, 2468, 2469, 2471, 2473, 2474, 2475, 2477, 2480, 2483, 2485, 2487, 2489, 2490, 2492, 2493, 2495, 2499, 2500, 2502, 2505, 2510, 2547, 2550, 2569, 2582, 2596, 2598, 2600, 2606, 2608, 2612, 2614, 2631, 2632, 2638, 2646, 2648, 2649, 2650, 2651, 2675, 2676, 2682, 2683, 2701, 2710, 2719, 2721, 2722, 2723, 2724, 2726, 2734, 2737, 2778, 2799, 2813, 2816, 2820, 2825, 2846, 2856, 2873, 2886, 2899, 2906, 2917, 2940, 8009, 8154, 8206, 9711, 9714, 10165, 10188, 10465, 10487, 11021, 11360, 11881, 12045, 12081, 12138, 12278, 12624, 13090, 13112, 13335, 13349, 13643, 13650, 14092, 14172, 14604, 14875, 15075, 15120, 15153, 15161, 15307, 15410, 15640, 15802, 16623, 17232, 17592, 18264, 19475, 19537, 19839, 20076, 20506, 20609, 21226, 21731, 21751, 21885, 22067, 23229, 23323, 23411, 23449, 23572, 23893, 23999, 24068, 25306, 25567, 26174, 26787, 27335, 27900, 27955, 28050, 28380, 28782, 29559, 30142, 30768, 30968, 31349, 31675, 32131, 32256, 32408, 32466, 32638, 32925, 33033, 33219, 33551, 33673, 34343, 34508, 35423, 36314, 37367, 37770, 38310, 38330, 39414, 40163, 40216, 40223, 40527, 40805)| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 375| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (142, 243, 257, 275, 278, 288, 362, 388, 422, 448, 449, 450, 451, 452, 453, 454, 464, 468, 471, 473, 475, 477, 480, 483, 486, 499, 500, 509, 517, 590, 603, 604, 605, 607, 609, 636, 647, 663, 665, 687, 691, 710, 720, 729, 801, 806, 808, 810, 815, 817, 837, 839, 926, 929, 930, 934, 937, 983, 988, 995, 998, 999, 1000, 1012, 1015, 1017, 1027, 1029, 1035, 1036, 1043, 1049, 1056, 1057, 1058, 1069, 1072, 1075, 1078, 1079, 1080, 1081, 1082, 1083, 1084, 1085, 1086, 1087, 1090, 1093, 1094, 1098, 1101, 1102, 1112, 1114, 1116, 1117, 1118, 1120, 1121, 1122, 1125, 1126, 1137, 1138, 1139, 1141, 1148, 1149, 1153, 1156, 1158, 1164, 1165, 1166, 1200, 1234, 1244, 1245, 1248, 1249, 1256, 1257, 1270, 1274, 1277, 1285, 1293, 1295, 1296, 1302, 1306, 1308, 1309, 1310, 1322, 1325, 1327, 1329, 1330, 1337, 1339, 1343, 1354, 1355, 1358, 1361, 1363, 1365, 1367, 1368, 1373, 1378, 1379, 1382, 1384, 1385, 1391, 1393, 1395, 1403, 1405, 1445, 1464, 1465, 1466, 1499, 1509, 1512, 1514, 1515, 1518, 1520, 1552, 1569, 1571, 1572, 1573, 1577, 1579, 1582, 1588, 1589, 1592, 1593, 1594, 1595, 1596, 1597, 1608, 1611, 1613, 1614, 1625, 1653, 1656, 1661, 1662, 1666, 1676, 1678, 1679, 1687, 1691, 1693, 1695, 1700, 1702, 1703, 1706, 1707, 1708, 1709, 1710, 1713, 1714, 1721, 1722, 1723, 1724, 1726, 1727, 1729, 1731, 1738, 1740, 1747, 1748, 1755, 1757, 1759, 1760, 1763, 1777, 1783, 1788, 1791, 1792, 1793, 1794, 1796, 1841, 1849, 1854, 1858, 1862, 1866, 1870, 1873, 1883, 1890, 1894, 1898, 1902, 1904, 1908, 1910, 1916, 1930, 1938, 1939, 1943, 1947, 1954, 1956, 1970, 1971, 1978, 2016, 2018, 2019, 2022, 2024, 2041, 2046, 2047, 2048, 2051, 2052, 2053, 2056, 2065, 2081, 2094, 2096, 2098, 2103, 2105, 2108, 2119, 2138, 2141, 2148, 2149, 2155, 2164, 2169, 2171, 2172, 2173, 2174, 2184, 2185, 2189, 2191, 2192, 2195, 2222, 2225, 2227, 2232, 2233, 2234, 2235, 2239, 2242, 2251, 2253, 2254, 2256, 2263, 2264, 2265, 2266, 2267, 2268, 2277, 2279, 2283, 2284, 2286, 2287, 2289, 2290, 2291, 2293, 2326, 2327, 2328, 2372, 2407, 2408, 2409, 2417, 2440, 2442, 2443, 2445, 2448, 2449, 2456, 2458, 2461, 2463, 2464, 2466, 2467, 2498, 2504, 2517, 2519, 2520, 2539, 2541, 2543, 2546, 2548, 2549, 2557, 2558, 2559, 2560, 2561, 2564, 2565, 2566, 2567, 2568, 2570, 2571, 2572, 2573, 2574, 2577, 2578, 2580, 2584, 2591, 2592, 2596, 2599, 2600, 2602, 2610, 2614, 2616, 2634, 2636, 2637, 2638, 2639, 2641, 2643, 2644, 2645, 2647, 2648, 2652, 2654, 2656, 2658, 2659, 2661, 2662, 2663, 2664, 2665, 2669, 2670, 2671, 2672, 2675, 2676, 2678, 2679, 2682, 2684, 2685, 2688, 2695, 2698, 2702, 2705, 2706, 2707, 2708, 2709, 2711, 2712, 2713, 2714, 2715, 2728, 2731, 2733, 2736, 2738, 2739, 2740, 2742, 2743, 2744, 2752, 2754, 2777, 2798, 2800, 2807, 2808, 2811, 2812, 2827, 2828, 2831, 2834, 2836, 2838, 2840, 2842, 2843, 2844, 2849, 2851, 2854, 2857, 2858, 2859, 2860, 2861, 2862, 2863, 2865, 2866, 2867, 2868, 2870, 2873, 2877, 2880, 2882, 2883, 2885, 2889, 2891, 2894, 2896, 2897, 2900, 2902, 2903, 2904, 2909, 2913, 2914, 2915, 2918, 2920, 2921, 2924, 2925, 2927, 2929, 2931, 2937, 2939, 2940, 2941, 7873, 7981, 8147, 8391, 8499, 8959, 9058, 9071, 9724, 9752, 9793, 9827, 9940, 10023, 10378, 10750, 10963, 10964, 11335, 11401, 11432, 11760, 11816, 12049, 12278, 12741, 12950, 13039, 13227, 13332, 13461, 13650, 13670, 13741, 13985, 13989, 14133, 14159, 14175, 14284, 14387, 14502, 14681, 14794, 14801, 14831, 15075, 15153, 15478, 15640, 15802, 15947, 16076, 16333, 16427, 17090, 17092, 17093, 17483, 17592, 17718, 17902, 18060, 18321, 18322, 19017, 19110, 19145, 19592, 19864, 20028, 20219, 20506, 21287, 21329, 21803, 21859, 21933, 21949, 21969, 22002, 22019, 22214, 22370, 22780, 23119, 23411, 23425, 23753, 23906, 23999, 24068, 24650, 24991, 25024, 25299, 25673, 25714, 25963, 26062, 26095, 26124, 26821, 27866, 27900, 28050, 28151, 28782, 28822, 28915, 29059, 29087, 29217, 29418, 29569, 29690, 29850, 29853, 30021, 30256, 30583, 30737, 30763, 30774, 30915, 31148, 32105, 32234, 32345, 32567, 32780, 32816, 32961, 33033, 33073, 33421, 33530, 33549, 33551, 33764, 33821, 33906, 34019, 34322, 34597, 34640, 35016, 35806, 35851, 36585, 36747, 36805, 37126, 37207, 37233, 37861, 37912, 38183, 38243, 38429, 38435, 38559, 38679, 38815, 38996, 39674, 39675, 40071, 40163, 40205, 40731, 41102, 41113, 41273, 41278, 41279)| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 444| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (574, 576, 579, 581, 585, 597, 612, 630, 639, 640, 642, 659, 683, 1128, 1129, 1133, 1289, 1299, 1305, 1429, 1448, 1453, 1454, 1507, 1543, 1766, 1965, 1966, 1967, 1976, 2013, 2745, 2747, 2757, 2761, 2764, 2768, 2780, 2785, 2791, 2794, 2806, 2823, 2825, 11554, 11555, 13089, 14382, 17514, 17629, 20209, 25336, 26703, 26786, 26988, 28439, 29238, 35885, 41244)| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 446| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (559, 560, 576, 579, 581, 612, 630, 640, 659, 1133, 1290, 1305, 1429, 1448, 1453, 1454, 1543, 1566, 1967, 2747, 2757, 2766, 2781, 2783, 2785, 2794, 2805, 2823, 2825, 2908, 11554, 11555, 14382, 17629, 20209, 25336, 26988, 35885, 37669)| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 576| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (936, 959, 1003, 1524, 1590, 1654, 1659, 1684, 1690, 1692, 1694, 1719, 1753, 1754, 1797, 1840, 1934, 2020, 2086, 2101, 2103, 2105, 2106, 2108, 2109, 2110, 2147, 2151, 2161, 2162, 2163, 2168, 2181, 2183, 2226, 2249, 2271, 2272, 2273, 2274, 2275, 2276, 2278, 2292, 2296, 2302, 2317, 2319, 2324, 2412, 2415, 2437, 2439, 2444, 2455, 2569, 2582, 2612, 2631, 2632, 2646, 2649, 2651, 2710, 2719, 2721, 2722, 2723, 2726, 2799, 2813, 2846, 2940, 8009, 8154, 10188, 10487, 11881, 12624, 13112, 13335, 14172, 15120, 15410, 19839, 21731, 23229, 23572, 29559, 37770, 38310, 38330, 40216, 40527)| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 598| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (559, 560, 1289, 1305, 1345, 1566, 2783, 37669)| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 599| Bindings |
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select `fish`.*, `water_fish`.`water_id` as `pivot_water_id`, `water_fish`.`fish_id` as `pivot_fish_id` from `fish` inner join `water_fish` on `fish`.`id` = `water_fish`.`fish_id` where `water_fish`.`water_id` = 607| Bindings |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (1131, 1133, 8271)| Bindings |
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select * from `companies` where `companies`.`country_id` in (54)| Backtrace |
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select `climates`.*, `climate_country`.`country_id` as `pivot_country_id`, `climate_country`.`climate_id` as `pivot_climate_id` from `climates` inner join `climate_country` on `climates`.`id` = `climate_country`.`climate_id` where `climate_country`.`country_id` = 54| Bindings |
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select * from `translations` where `translations`.`translatable_type` = 'App\\Models\\Climate' and `translations`.`translatable_id` = 1 and `translations`.`translatable_id` is not null and `lang` = 'en' limit 1| Bindings |
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select count(*) as aggregate from `tags` where `tags`.`context_id` = 54 and `tags`.`context_id` is not null and `type` = 'country'| Bindings |
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with recursive `laravel_cte` as ((select `fish`.*, -1 as `depth`, cast(`id` as char(65535)) as `path` from `fish` where `fish`.`id` in (60, 62, 63, 159, 163, 166, 193, 219, 231, 235, 236, 237, 256, 259, 264, 266, 268, 270, 274, 277, 283, 287, 289, 292, 294, 296, 299, 303, 307, 309, 313, 316, 318, 320, 322, 325, 328, 331, 333, 335, 343, 346, 350, 353, 355, 358, 361, 364, 366, 371, 373, 379, 383, 387, 396, 399, 415, 421, 423, 426, 429, 436, 438, 440, 442, 445, 463, 467, 470, 472, 474, 476, 479, 482, 485, 488, 492, 495, 498, 507, 512, 516, 523, 557, 573, 575, 578, 580, 584, 588, 596, 599, 602, 606, 608, 611, 629, 633, 635, 638, 641, 645, 656, 658, 662, 682, 690, 699, 709, 719, 728, 799, 802, 804, 807, 809, 811, 813, 834, 836, 838, 895, 928, 931, 933, 935, 938, 943, 950, 952, 955, 958, 963, 965, 968, 982, 987, 994, 997, 1004, 1011, 1014, 1016, 1021, 1023, 1026, 1028, 1030, 1032, 1034, 1039, 1042, 1045, 1048, 1051, 1068, 1071, 1074, 1077, 1089, 1092, 1097, 1100, 1115, 1127, 1130, 1132, 1136, 1140, 1144, 1147, 1152, 1155, 1157, 1163, 1172, 1199, 1211, 1229, 1231, 1233, 1235, 1238, 1241, 1243, 1247, 1250, 1258, 1261, 1264, 1271, 1273, 1275, 1281, 1284, 1294, 1298, 1301, 1304, 1313, 1320, 1324, 1328, 1332, 1334, 1336, 1342, 1344, 1347, 1351, 1353, 1357, 1360, 1362, 1364, 1366, 1372, 1375, 1377, 1381, 1383, 1387, 1389, 1394, 1397, 1401, 1406, 1424, 1428, 1447, 1452, 1506, 1508, 1511, 1513, 1517, 1519, 1522, 1542, 1548, 1550, 1575, 1581, 1583, 1585, 1591, 1607, 1610, 1623, 1626, 1628, 1630, 1652, 1655, 1658, 1660, 1665, 1674, 1677, 1683, 1685, 1689, 1696, 1699, 1701, 1705, 1718, 1728, 1730, 1737, 1739, 1742, 1746, 1750, 1756, 1758, 1764, 1767, 1776, 1782, 1785, 1787, 1789, 1795, 1816, 1838, 1839, 1848, 1852, 1857, 1861, 1865, 1869, 1872, 1876, 1882, 1885, 1889, 1893, 1897, 1901, 1903, 1907, 1909, 1913, 1915, 1929, 1933, 1936, 1937, 1945, 1955, 1964, 1969, 1975, 1977, 2012, 2015, 2017, 2023, 2040, 2045, 2049, 2055, 2058, 2062, 2064, 2070, 2072, 2083, 2088, 2090, 2095, 2097, 2100, 2102, 2104, 2118, 2128, 2137, 2140, 2146, 2150, 2165, 2188, 2190, 2194, 2196, 2198, 2219, 2221, 2223, 2231, 2236, 2238, 2241, 2248, 2252, 2255, 2260, 2270, 2281, 2282, 2285, 2288, 2299, 2301, 2318, 2325, 2334, 2337, 2341, 2344, 2347, 2353, 2357, 2360, 2364, 2367, 2369, 2373, 2376, 2381, 2385, 2392, 2394, 2398, 2400, 2403, 2405, 2411, 2414, 2416, 2421, 2423, 2425, 2427, 2432, 2435, 2438, 2446, 2460, 2462, 2465, 2470, 2472, 2476, 2479, 2482, 2484, 2486, 2488, 2491, 2494, 2497, 2501, 2503, 2509, 2516, 2540, 2542, 2545, 2581, 2583, 2587, 2590, 2595, 2597, 2605, 2607, 2609, 2611, 2613, 2615, 2635, 2653, 2657, 2660, 2674, 2681, 2694, 2697, 2700, 2704, 2718, 2720, 2725, 2730, 2732, 2735, 2746, 2750, 2753, 2756, 2765, 2776, 2779, 2782, 2784, 2793, 2804, 2810, 2815, 2819, 2822, 2824, 2826, 2830, 2833, 2835, 2837, 2839, 2841, 2845, 2848, 2850, 2853, 2864, 2872, 2876, 2881, 2884, 2888, 2890, 2893, 2895, 2901, 2905, 2916, 2919, 2923, 2926, 2930, 2936, 2938, 3370, 3380, 3383, 3415, 3418, 3422, 3454, 3483, 3498, 3594, 3597, 3644, 3689, 3697, 3698, 3701, 3729, 3738, 3747, 3806, 3981, 4017, 4026, 4068, 4113, 4131, 4137, 4152, 4171, 4200, 4209, 4241, 4312, 4614, 4672, 4723, 4736, 4766, 4778, 4828, 4841, 4849, 4916, 4928, 4956, 5053, 5074, 5075, 5138, 5152, 5218, 5278, 5362, 5429, 5441, 5461, 5504, 5534, 5589, 5652, 5772, 5805, 5839, 5909, 5913, 5936, 5968, 6032, 6151, 6158, 6185, 6218, 6230, 6398, 6471, 6493, 6596, 6619, 6620, 6682, 6691, 6695, 6748, 6759, 6764, 6814, 6850, 6857, 6918, 6948, 7071, 7084, 7113, 7120, 7140, 7201, 7234, 7263, 7301, 7357, 7448, 7450, 7460, 7539, 7610, 7659, 7726, 7729)) union all (select `fish`.*, `depth` - 1 as `depth`, concat(`path`, '.', `fish`.`id`) from `fish` inner join `laravel_cte` on `laravel_cte`.`parent_id` = `fish`.`id`)) select * from `laravel_cte`| Bindings |
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| Backtrace |
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select * from `fish_names` where `locale` = 'en' and `main` = 1 and `fish_names`.`fish_id` in (1, 34, 58, 59, 60, 62, 63, 66, 67, 68, 69, 70, 71, 72, 148, 151, 155, 159, 161, 163, 165, 166, 191, 192, 193, 202, 218, 219, 230, 231, 233, 234, 235, 236, 237, 255, 256, 258, 259, 264, 266, 268, 270, 272, 273, 274, 276, 277, 281, 283, 287, 289, 292, 294, 296, 298, 299, 301, 302, 303, 305, 306, 307, 309, 311, 312, 313, 316, 318, 320, 322, 324, 325, 327, 328, 330, 331, 333, 335, 342, 343, 345, 346, 348, 349, 350, 353, 355, 358, 360, 361, 364, 366, 369, 370, 371, 373, 378, 379, 381, 382, 383, 386, 387, 396, 398, 399, 413, 414, 415, 421, 423, 426, 429, 431, 436, 438, 440, 442, 445, 461, 462, 463, 465, 466, 467, 469, 470, 472, 474, 476, 478, 479, 481, 482, 484, 485, 487, 488, 491, 492, 494, 495, 497, 498, 502, 503, 505, 506, 507, 510, 511, 512, 514, 515, 516, 521, 522, 523, 537, 555, 556, 557, 571, 572, 573, 575, 577, 578, 580, 582, 583, 584, 586, 587, 588, 596, 598, 599, 602, 606, 608, 610, 611, 627, 628, 629, 631, 632, 633, 635, 637, 638, 641, 644, 645, 655, 656, 658, 660, 661, 662, 676, 677, 681, 682, 688, 689, 690, 692, 697, 698, 699, 705, 707, 708, 709, 711, 712, 717, 718, 719, 728, 799, 802, 803, 804, 807, 809, 811, 813, 832, 833, 834, 836, 838, 886, 892, 893, 894, 895, 904, 906, 908, 909, 910, 927, 928, 931, 933, 935, 938, 942, 943, 949, 950, 952, 955, 958, 961, 962, 963, 965, 967, 968, 980, 981, 982, 987, 994, 997, 1004, 1009, 1010, 1011, 1013, 1014, 1016, 1019, 1020, 1021, 1023, 1026, 1028, 1030, 1032, 1034, 1037, 1038, 1039, 1041, 1042, 1044, 1045, 1048, 1051, 1067, 1068, 1071, 1073, 1074, 1076, 1077, 1089, 1091, 1092, 1095, 1096, 1097, 1099, 1100, 1108, 1115, 1127, 1130, 1132, 1135, 1136, 1140, 1143, 1144, 1146, 1147, 1150, 1151, 1152, 1154, 1155, 1157, 1163, 1172, 1198, 1199, 1211, 1229, 1231, 1233, 1235, 1237, 1238, 1240, 1241, 1243, 1246, 1247, 1250, 1258, 1260, 1261, 1263, 1264, 1271, 1273, 1275, 1281, 1283, 1284, 1294, 1297, 1298, 1300, 1301, 1303, 1304, 1311, 1312, 1313, 1320, 1323, 1324, 1328, 1331, 1332, 1334, 1336, 1342, 1344, 1346, 1347, 1350, 1351, 1353, 1356, 1357, 1359, 1360, 1362, 1364, 1366, 1372, 1374, 1375, 1377, 1381, 1383, 1386, 1387, 1389, 1394, 1397, 1401, 1406, 1424, 1428, 1446, 1447, 1451, 1452, 1506, 1508, 1510, 1511, 1513, 1516, 1517, 1519, 1521, 1522, 1541, 1542, 1548, 1550, 1575, 1580, 1581, 1583, 1585, 1591, 1607, 1609, 1610, 1622, 1623, 1626, 1628, 1630, 1651, 1652, 1655, 1658, 1660, 1664, 1665, 1674, 1677, 1683, 1685, 1688, 1689, 1696, 1699, 1701, 1704, 1705, 1717, 1718, 1728, 1730, 1736, 1737, 1739, 1741, 1742, 1744, 1745, 1746, 1749, 1750, 1756, 1758, 1764, 1767, 1770, 1776, 1779, 1782, 1784, 1785, 1787, 1789, 1795, 1799, 1815, 1816, 1838, 1839, 1843, 1845, 1846, 1847, 1848, 1850, 1851, 1852, 1855, 1856, 1857, 1859, 1860, 1861, 1863, 1864, 1865, 1867, 1868, 1869, 1871, 1872, 1874, 1875, 1876, 1879, 1880, 1881, 1882, 1884, 1885, 1887, 1888, 1889, 1891, 1892, 1893, 1895, 1896, 1897, 1899, 1900, 1901, 1903, 1905, 1906, 1907, 1909, 1911, 1912, 1913, 1915, 1927, 1928, 1929, 1931, 1932, 1933, 1935, 1936, 1937, 1944, 1945, 1955, 1961, 1964, 1968, 1969, 1974, 1975, 1977, 2011, 2012, 2014, 2015, 2017, 2023, 2040, 2044, 2045, 2049, 2055, 2057, 2058, 2061, 2062, 2064, 2070, 2072, 2082, 2083, 2088, 2090, 2095, 2097, 2100, 2102, 2104, 2117, 2118, 2127, 2128, 2137, 2139, 2140, 2146, 2150, 2165, 2188, 2190, 2193, 2194, 2196, 2198, 2219, 2221, 2223, 2228, 2231, 2236, 2238, 2240, 2241, 2247, 2248, 2252, 2255, 2257, 2260, 2270, 2280, 2281, 2282, 2285, 2288, 2298, 2299, 2301, 2318, 2325, 2333, 2334, 2336, 2337, 2340, 2341, 2343, 2344, 2346, 2347, 2353, 2356, 2357, 2359, 2360, 2364, 2367, 2369, 2373, 2376, 2381, 2385, 2392, 2394, 2397, 2398, 2400, 2403, 2405, 2411, 2414, 2416, 2420, 2421, 2423, 2425, 2427, 2431, 2432, 2435, 2438, 2446, 2459, 2460, 2462, 2465, 2470, 2472, 2476, 2478, 2479, 2481, 2482, 2484, 2486, 2488, 2491, 2494, 2496, 2497, 2501, 2503, 2509, 2516, 2540, 2542, 2544, 2545, 2581, 2583, 2587, 2590, 2595, 2597, 2604, 2605, 2607, 2609, 2611, 2613, 2615, 2635, 2653, 2657, 2660, 2673, 2674, 2681, 2693, 2694, 2696, 2697, 2699, 2700, 2703, 2704, 2718, 2720, 2725, 2729, 2730, 2732, 2735, 2746, 2749, 2750, 2753, 2755, 2756, 2765, 2776, 2779, 2782, 2784, 2793, 2801, 2804, 2810, 2814, 2815, 2818, 2819, 2821, 2822, 2824, 2826, 2829, 2830, 2833, 2835, 2837, 2839, 2841, 2845, 2847, 2848, 2850, 2852, 2853, 2864, 2871, 2872, 2876, 2881, 2884, 2887, 2888, 2890, 2893, 2895, 2901, 2905, 2916, 2919, 2923, 2926, 2930, 2936, 2938, 2947, 2950, 2952, 2954, 2960, 2975, 2989, 3032, 3035, 3042, 3061, 3084, 3125, 3149, 3152, 3154, 3174, 3182, 3184, 3212, 3217, 3233, 3272, 3290, 3316, 3370, 3380, 3383, 3415, 3418, 3422, 3454, 3483, 3498, 3594, 3597, 3644, 3689, 3697, 3698, 3701, 3729, 3738, 3747, 3806, 3981, 4017, 4026, 4068, 4113, 4131, 4137, 4152, 4171, 4200, 4209, 4241, 4312, 4614, 4672, 4723, 4736, 4766, 4778, 4828, 4841, 4849, 4916, 4928, 4956, 5053, 5074, 5075, 5138, 5152, 5218, 5278, 5362, 5429, 5441, 5461, 5504, 5534, 5589, 5652, 5772, 5805, 5839, 5909, 5913, 5936, 5968, 6032, 6151, 6158, 6185, 6218, 6230, 6398, 6471, 6493, 6596, 6619, 6620, 6682, 6691, 6695, 6748, 6759, 6764, 6814, 6850, 6857, 6918, 6948, 7071, 7084, 7113, 7120, 7140, 7201, 7234, 7263, 7301, 7357, 7448, 7450, 7460, 7539, 7610, 7659, 7726, 7729)| Bindings |
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| Backtrace |
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select * from `tags` where `tags`.`context_id` = 54 and `tags`.`context_id` is not null and `type` = 'country' order by `created_at` desc limit 100| Bindings |
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| Backtrace |
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select * from `brands` where `brands`.`country_id` = 54 and `brands`.`country_id` is not null| Bindings |
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| Backtrace |
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select * from `sessions` where `id` = '2NiZO6N1bvRZJotIiSMETpOuUEgpMrL379TGAAVv' limit 1| Bindings |
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| Backtrace |
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insert into `sessions` (`payload`, `last_activity`, `user_id`, `ip_address`, `user_agent`, `id`) values ('YTozOntzOjY6Il90b2tlbiI7czo0MDoibXV5ZVc1aE96cnBnVVdMRERPOXhqTXZIbUhhWTF0VjF1YU5HVzJLYiI7czo5OiJfcHJldmlvdXMiO2E6MTp7czozOiJ1cmwiO3M6NDQ6Imh0dHBzOi8vZGV2LnRhZ215ZmlzaC5jb20vY291bnRyaWVzL2NvbG9tYmlhIjt9czo2OiJfZmxhc2giO2E6Mjp7czozOiJvbGQiO2E6MDp7fXM6MzoibmV3IjthOjA6e319fQ==', 1747458774, null, '172.18.0.5', 'Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)', '2NiZO6N1bvRZJotIiSMETpOuUEgpMrL379TGAAVv')| Bindings |
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| Backtrace |
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200
[]
[]
0 of 0array:35 [▼ "x-real-ip" => array:1 [▶ 0 => "172.70.126.216" ] "x-forwarded-server" => array:1 [▶ 0 => "traefik" ] "x-forwarded-proto" => array:1 [▶ 0 => "https" ] "x-forwarded-port" => array:1 [▶ 0 => "443" ] "x-forwarded-host" => array:1 [▶ 0 => "dev.tagmyfish.com" ] "x-forwarded-for" => array:1 [▶ 0 => "172.70.126.216" ] "upgrade-insecure-requests" => array:1 [▶ 0 => "1" ] "sec-fetch-user" => array:1 [▶ 0 => "?1" ] "sec-fetch-site" => array:1 [▶ 0 => "none" ] "sec-fetch-mode" => array:1 [▶ 0 => "navigate" ] "sec-fetch-dest" => array:1 [▶ 0 => "document" ] "sec-ch-ua-platform" => array:1 [▶ 0 => ""Windows"" ] "sec-ch-ua-mobile" => array:1 [▶ 0 => "?0" ] "sec-ch-ua" => array:1 [▶ 0 => ""Chromium";v="130", "HeadlessChrome";v="130", "Not?A_Brand";v="99"" ] "priority" => array:1 [▶ 0 => "u=0, i" ] "pragma" => array:1 [▶ 0 => "no-cache" ] "cf-visitor" => array:1 [▶ 0 => "{"scheme":"https"}" ] "cf-timezone" => array:1 [▶ 0 => "America/New_York" ] "cf-region-code" => array:1 [▶ 0 => "OH" ] "cf-region" => array:1 [▶ 0 => "Ohio" ] "cf-ray" => array:1 [▶ 0 => "94109f5c4faa0044-ORD" ] "cf-postal-code" => array:1 [▶ 0 => "43221" ] "cf-metro-code" => array:1 [▶ 0 => "535" ] "cf-iplongitude" => array:1 [▶ 0 => "-83.08590" ] "cf-iplatitude" => array:1 [▶ 0 => "40.02330" ] "cf-ipcountry" => array:1 [▶ 0 => "US" ] "cf-ipcontinent" => array:1 [▶ 0 => "NA" ] "cf-ipcity" => array:1 [▶ 0 => "Columbus" ] "cf-connecting-ip" => array:1 [▶ 0 => "3.143.170.30" ] "cdn-loop" => array:1 [▶ 0 => "cloudflare; loops=1" ] "cache-control" => array:1 [▶ 0 => "no-cache" ] "accept-encoding" => array:1 [▶ 0 => "gzip, br" ] "accept" => array:1 [▶ 0 => "text/html,application/xhtml+xml,application/xml;q=0.9,image/avif,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.7" ] "user-agent" => array:1 [▶ 0 => "Mozilla/5.0 AppleWebKit/537.36 (KHTML, like Gecko; compatible; ClaudeBot/1.0; +claudebot@anthropic.com)" ] "host" => array:1 [▶ 0 => "dev.tagmyfish.com" ] ]
[]
0 of 0array:5 [▼ "content-type" => array:1 [▶ 0 => "text/html; charset=UTF-8" ] "cache-control" => array:1 [▶ 0 => "no-cache, private" ] "date" => array:1 [▶ 0 => "Sat, 17 May 2025 05:12:54 GMT" ] "set-cookie" => array:2 [▶ 0 => "XSRF-TOKEN=eyJpdiI6Ilh3cjNzNzIvcGduZWVrVXRmV0dJL3c9PSIsInZhbHVlIjoiaXJrVkJqd1VxUU9qRE9mUUJQUGQ5cktQZ2tDT25HcEZYQk9xbzZtR0hESnQzWThCbFBCblpaMWN1UkJSeVdRcFFFZEZLSVJqZjRka0dSdTN1WXlLTEFlZTFiWFNHTGt0VHN0Y3ZWNXRSOHlBbTdVd2MvTVAxdVM1bWZpOHIrNEsiLCJtYWMiOiI5ZTljYmVlODY4NzllODM3N2MzZDgxZWZmNTM0OTgxNzg5YzA0MDgyYTY3NWE4M2E3NzcyZTY2YmM4ZDQ3MzM5IiwidGFnIjoiIn0%3D; expires=Sat, 17 May 2025 07:12:54 GMT; Max-Age=7200; path=/; secure; samesite=lax ◀XSRF-TOKEN=eyJpdiI6Ilh3cjNzNzIvcGduZWVrVXRmV0dJL3c9PSIsInZhbHVlIjoiaXJrVkJqd1VxUU9qRE9mUUJQUGQ5cktQZ2tDT25HcEZYQk9xbzZtR0hESnQzWThCbFBCblpaMWN1UkJSeVdRcFFFZEZLS ▶" 1 => "tagmyfish_session=eyJpdiI6Ijh0QnlkTm0zS1ByUndDeUdibkJIdUE9PSIsInZhbHVlIjoiem1iL2lpNXA3YmRaQURQU1pMUHZYb0lKN2VMd2c5dUV1dFRpdk9Na01ya1hxSjFMd0FWWjBLWXFQcUtoYmtEQi9ROXhldFZZcVZramR1RGhPM0tPM0d6MmhuR0J5UjhEOHdCQ2liby92MTVUeHpEaS9mN00waWpXdjYvejNlVnEiLCJtYWMiOiI5Yzc5NWFmM2ZmNjk3MjdhM2M3NWE4ODc3MjBmM2I5ZDkyMjk3MTI5Zjc0OTlhYjIxNWFhN2RiMzRmMGUxOTI1IiwidGFnIjoiIn0%3D; expires=Sat, 17 May 2025 07:12:54 GMT; Max-Age=7200; path=/; secure; httponly; samesite=lax ◀tagmyfish_session=eyJpdiI6Ijh0QnlkTm0zS1ByUndDeUdibkJIdUE9PSIsInZhbHVlIjoiem1iL2lpNXA3YmRaQURQU1pMUHZYb0lKN2VMd2c5dUV1dFRpdk9Na01ya1hxSjFMd0FWWjBLWXFQcUtoYmtEQi ▶" ] "Set-Cookie" => array:2 [▶ 0 => "XSRF-TOKEN=eyJpdiI6Ilh3cjNzNzIvcGduZWVrVXRmV0dJL3c9PSIsInZhbHVlIjoiaXJrVkJqd1VxUU9qRE9mUUJQUGQ5cktQZ2tDT25HcEZYQk9xbzZtR0hESnQzWThCbFBCblpaMWN1UkJSeVdRcFFFZEZLSVJqZjRka0dSdTN1WXlLTEFlZTFiWFNHTGt0VHN0Y3ZWNXRSOHlBbTdVd2MvTVAxdVM1bWZpOHIrNEsiLCJtYWMiOiI5ZTljYmVlODY4NzllODM3N2MzZDgxZWZmNTM0OTgxNzg5YzA0MDgyYTY3NWE4M2E3NzcyZTY2YmM4ZDQ3MzM5IiwidGFnIjoiIn0%3D; expires=Sat, 17-May-2025 07:12:54 GMT; path=/; secure ◀XSRF-TOKEN=eyJpdiI6Ilh3cjNzNzIvcGduZWVrVXRmV0dJL3c9PSIsInZhbHVlIjoiaXJrVkJqd1VxUU9qRE9mUUJQUGQ5cktQZ2tDT25HcEZYQk9xbzZtR0hESnQzWThCbFBCblpaMWN1UkJSeVdRcFFFZEZLS ▶" 1 => "tagmyfish_session=eyJpdiI6Ijh0QnlkTm0zS1ByUndDeUdibkJIdUE9PSIsInZhbHVlIjoiem1iL2lpNXA3YmRaQURQU1pMUHZYb0lKN2VMd2c5dUV1dFRpdk9Na01ya1hxSjFMd0FWWjBLWXFQcUtoYmtEQi9ROXhldFZZcVZramR1RGhPM0tPM0d6MmhuR0J5UjhEOHdCQ2liby92MTVUeHpEaS9mN00waWpXdjYvejNlVnEiLCJtYWMiOiI5Yzc5NWFmM2ZmNjk3MjdhM2M3NWE4ODc3MjBmM2I5ZDkyMjk3MTI5Zjc0OTlhYjIxNWFhN2RiMzRmMGUxOTI1IiwidGFnIjoiIn0%3D; expires=Sat, 17-May-2025 07:12:54 GMT; path=/; secure; httponly ◀tagmyfish_session=eyJpdiI6Ijh0QnlkTm0zS1ByUndDeUdibkJIdUE9PSIsInZhbHVlIjoiem1iL2lpNXA3YmRaQURQU1pMUHZYb0lKN2VMd2c5dUV1dFRpdk9Na01ya1hxSjFMd0FWWjBLWXFQcUtoYmtEQi ▶" ] ]
0 of 0array:3 [▼ "_token" => "muyeW5hOzrpgUWLDDO9xjMvHmHaY1tV1uaNGW2Kb" "_previous" => array:1 [▶ "url" => "https://dev.tagmyfish.com/countries/colombia" ] "_flash" => array:2 [▶ "old" => [] "new" => [] ] ]
