luguog/gate_dash

1from fastapi import FastAPI2from fastapi.middleware.cors import CORSMiddleware3import ccxt4import os5import pandas as pd6from dotenv import load_dotenv7 8load_dotenv()9 10app = FastAPI()11 12# CORS (optional)13app.add_middleware(14    CORSMiddleware,15    allow_origins=["*"],16    allow_credentials=True,17    allow_methods=["*"],18    allow_headers=["*"],19)20 21exchange = ccxt.gateio({22    'apiKey': os.getenv("GATE_API_KEY"),23    'secret': os.getenv("GATE_API_SECRET"),24    'enableRateLimit': True,25    'options': {'defaultType': 'swap'}26})27 28@app.get("/api/data")29def get_data():30    try:31        markets = exchange.load_markets()32        usdt_pairs = [s for s in markets if "/USDT" in s and markets[s].get("type") == "swap"]33        results = []34 35        for symbol in usdt_pairs:36            try:37                ticker = exchange.fetch_ticker(symbol)38                price = ticker['last']39                volume = ticker['quoteVolume']40                orderbook = exchange.fetch_order_book(symbol)41                if orderbook['asks'] and orderbook['bids']:42                    spread = orderbook['asks'][0][0] - orderbook['bids'][0][0]43                    spread_pct = (spread / price) * 10044                    bid_depth = sum(b[1] for b in orderbook['bids'][:5])45                    ask_depth = sum(a[1] for a in orderbook['asks'][:5])46                    depth = bid_depth + ask_depth47                    ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=24)48                    closes = [x[4] for x in ohlcv]49                    volatility = (pd.Series(closes).std() / pd.Series(closes).mean()) * 10050 51                    score = (52                        max(0, 100 - (spread_pct * 20)) +53                        min(100, volume / 200000 * 100) +54                        min(100, depth / 100) +55                        max(0, 100 - (volatility * 10))56                    ) / 457 58                    results.append({59                        "symbol": symbol,60                        "price": price,61                        "spread_pct": spread_pct,62                        "volume_24h": volume,63                        "depth": depth,64                        "volatility": volatility,65                        "mm_score": round(score, 2)66                    })67            except:68                continue69 70        top_symbols = sorted(results, key=lambda x: x['mm_score'], reverse=True)[:10]71        return {"top_symbols": top_symbols}72 73    except Exception as e:74        return {"error": str(e)}