import os, json, math, heapq, requests, urllib3 try: import msgpack except ImportError: print("[!] Zainstaluj msgpack: pip3 install msgpack") exit(1) urllib3.disable_warnings() BASE_PATH = "/var/lib/pterodactyl/volumes/cc7ccc03-03bd-4bde-8488-3057d3803420/squaremap/web" MTR_SAVES_PATH = "/var/lib/pterodactyl/volumes/cc7ccc03-03bd-4bde-8488-3057d3803420/world/mtr/minecraft/overworld" STATIONS_FILE = f"{BASE_PATH}/stations.json" OUTPUT_FILE = f"{BASE_PATH}/final_map_data.json" API_ROUTES_URL = "https://mtr.ciapongi.szablix.pl/mtr/api/map/stations-and-routes" API_RAILS_URL = "https://mtr.ciapongi.szablix.pl/mtr/api/map/rails" def normalize(s): return str(s).strip().lower().replace(" ", "") def dist_2d(p1, p2): return math.sqrt((p1[0]-p2[0])**2 + (p1[1]-p2[1])**2) def fetch_json(url): try: r = requests.get(url, verify=False, timeout=15) if r.status_code == 200: return r.json() except: pass return {} # ZMIANA: Pobieramy nie tylko współrzędne, ale też nazwy peronów z MsgPack def load_msgpack_data(folder_name): mapping = {} full_path = os.path.join(MTR_SAVES_PATH, folder_name) if not os.path.exists(full_path): return mapping for root, _, files in os.walk(full_path): for file in files: if file.startswith("."): continue try: with open(os.path.join(root, file), "rb") as f: data = msgpack.unpackb(f.read(), raw=False) p1, p2 = data.get("position1", {}), data.get("position2", {}) name = data.get("name", "Nieznany") if p1 and p2: k = tuple(sorted([(p1.get('x',0), p1.get('y',0), p1.get('z',0)), (p2.get('x',0), p2.get('y',0), p2.get('z',0))])) mapping[k] = name except: pass return mapping def dijkstra_on_rails(rail_dict, adj, start_rid, end_rid): if start_rid == end_rid: return [start_rid] queue = [(0, start_rid)] came_from = {start_rid: None} cost_so_far = {start_rid: 0} while queue: current_cost, curr = heapq.heappop(queue) if curr == end_rid: break for nxt in adj.get(curr, []): dist = rail_dict.get(nxt, {}).get('length', 10) new_cost = cost_so_far[curr] + dist if nxt not in cost_so_far or new_cost < cost_so_far[nxt]: cost_so_far[nxt] = new_cost heapq.heappush(queue, (new_cost, nxt)) came_from[nxt] = curr if end_rid not in came_from: return None path = [] c = end_rid while c is not None: path.append(c) c = came_from[c] path.reverse() return path def main(): print("=== GENERATOR V20 (ZOPTYMALIZOWANE PERONY I CZYSTE TRASY) ===") platform_data = load_msgpack_data("platforms") siding_data = load_msgpack_data("sidings") api_routes = fetch_json(API_ROUTES_URL).get('data', {}).get('routes', []) api_routes_map = {normalize(r.get('name', '')): r for r in api_routes} api_rails = fetch_json(API_RAILS_URL) rails_list = api_rails.get('data', {}).get('rails', []) if isinstance(api_rails, dict) else api_rails rail_dict, adj, grid = {}, {}, {} GRID_SIZE = 32 platforms_out, sidings_out, infra_out = [], [], [] nodes_set = set() for r in rails_list: rid = r['id'] rail_dict[rid] = r adj[rid] = set(r.get('connectedRails', [])) pts = [[c['x'], c['z']] for c in sorted(r.get('curvePoints', []), key=lambda x: x['progress'])] if not pts: continue nodes_set.add((round(pts[0][0], 2), round(pts[0][1], 2))) nodes_set.add((round(pts[-1][0], 2), round(pts[-1][1], 2))) for pt in pts: gx, gz = int(pt[0]//GRID_SIZE), int(pt[1]//GRID_SIZE) if (gx, gz) not in grid: grid[(gx, gz)] = set() grid[(gx, gz)].add(rid) p1, p2 = r.get('position1', {}), r.get('position2', {}) k = tuple(sorted([(p1.get('x',0), p1.get('y',0), p1.get('z',0)), (p2.get('x',0), p2.get('y',0), p2.get('z',0))])) # ZMIANA: Zapisujemy też nazwę do JSONa! if k in platform_data: platforms_out.append({"path": pts, "name": platform_data[k]}) elif k in siding_data: sidings_out.append({"path": pts, "name": siding_data[k]}) else: infra_out.append(pts) for r in rails_list: for connected in r.get('connectedRails', []): if connected in adj: adj[connected].add(r['id']) def find_closest_rail(pt): gx, gz = int(pt[0]//GRID_SIZE), int(pt[1]//GRID_SIZE) cands = set() for dx in [-1,0,1]: for dz in [-1,0,1]: cands.update(grid.get((gx+dx, gz+dz), [])) best_rail, min_d = None, float('inf') for rid in cands: for c in rail_dict[rid].get('curvePoints', []): d = dist_2d(pt, (c['x'], c['z'])) if d < min_d: min_d = d; best_rail = rid return best_rail, min_d try: with open(STATIONS_FILE, 'r') as f: data = json.load(f) except Exception: return final_routes = [] for route in data.get('routes', []): norm_name = normalize(route.get('name', '')) api_data = api_routes_map.get(norm_name) or next((v for k, v in api_routes_map.items() if norm_name in k), None) if api_data: route['id'] = api_data.get('id') route['stations'] = api_data.get('stations', []) stations = route['stations'] route_rids = [] if len(stations) > 1: for i in range(len(stations) - 1): s1, s2 = stations[i], stations[i+1] r1, d1 = find_closest_rail((s1['x'], s1['z'])) r2, d2 = find_closest_rail((s2['x'], s2['z'])) if r1 and r2: sub_path = dijkstra_on_rails(rail_dict, adj, r1, r2) if sub_path: if route_rids and route_rids[-1] == sub_path[0]: route_rids.extend(sub_path[1:]) else: route_rids.extend(sub_path) if route_rids: detailed_path = [] last_pt = None for rid in route_rids: r = rail_dict.get(rid) pts = [[c['x'], c['z']] for c in sorted(r.get('curvePoints', []), key=lambda x: x['progress'])] if not pts: continue if last_pt is not None: if dist_2d(last_pt, pts[-1]) < dist_2d(last_pt, pts[0]): pts.reverse() if detailed_path and dist_2d(detailed_path[-1], pts[0]) < 2.0: detailed_path.extend(pts[1:]) else: detailed_path.extend(pts) last_pt = pts[-1] route['path'] = detailed_path else: route['path'] = [[p['x'], p['z']] for p in api_data.get('path', [])] else: if 'stations' not in route: route['stations'] = [] final_routes.append(route) with open(OUTPUT_FILE, 'w') as f: json.dump({ "stations": data.get('stations', []), "routes": final_routes, "platforms": platforms_out, "sidings": sidings_out, "infrastructure": infra_out, "nodes": list(nodes_set) }, f) print("✅ GOTOWE! Wyeksportowano zaktualizowane perony i czyste trasy.") if __name__ == "__main__": main()