Create api.py

api.py

@@ -0,0 +1,74 @@
+from fastapi import FastAPI
+from fastapi.middleware.cors import CORSMiddleware
+import ccxt
+import os
+import pandas as pd
+from dotenv import load_dotenv
+
+load_dotenv()
+
+app = FastAPI()
+
+# CORS (optional)
+app.add_middleware(
+    CORSMiddleware,
+    allow_origins=["*"],
+    allow_credentials=True,
+    allow_methods=["*"],
+    allow_headers=["*"],
+)
+
+exchange = ccxt.gateio({
+    'apiKey': os.getenv("GATE_API_KEY"),
+    'secret': os.getenv("GATE_API_SECRET"),
+    'enableRateLimit': True,
+    'options': {'defaultType': 'swap'}
+})
+
+@app.get("/api/data")
+def get_data():
+    try:
+        markets = exchange.load_markets()
+        usdt_pairs = [s for s in markets if "/USDT" in s and markets[s].get("type") == "swap"]
+        results = []
+
+        for symbol in usdt_pairs:
+            try:
+                ticker = exchange.fetch_ticker(symbol)
+                price = ticker['last']
+                volume = ticker['quoteVolume']
+                orderbook = exchange.fetch_order_book(symbol)
+                if orderbook['asks'] and orderbook['bids']:
+                    spread = orderbook['asks'][0][0] - orderbook['bids'][0][0]
+                    spread_pct = (spread / price) * 100
+                    bid_depth = sum(b[1] for b in orderbook['bids'][:5])
+                    ask_depth = sum(a[1] for a in orderbook['asks'][:5])
+                    depth = bid_depth + ask_depth
+                    ohlcv = exchange.fetch_ohlcv(symbol, '1h', limit=24)
+                    closes = [x[4] for x in ohlcv]
+                    volatility = (pd.Series(closes).std() / pd.Series(closes).mean()) * 100
+
+                    score = (
+                        max(0, 100 - (spread_pct * 20)) +
+                        min(100, volume / 200000 * 100) +
+                        min(100, depth / 100) +
+                        max(0, 100 - (volatility * 10))
+                    ) / 4
+
+                    results.append({
+                        "symbol": symbol,
+                        "price": price,
+                        "spread_pct": spread_pct,
+                        "volume_24h": volume,
+                        "depth": depth,
+                        "volatility": volatility,
+                        "mm_score": round(score, 2)
+                    })
+            except:
+                continue
+
+        top_symbols = sorted(results, key=lambda x: x['mm_score'], reverse=True)[:10]
+        return {"top_symbols": top_symbols}
+
+    except Exception as e:
+        return {"error": str(e)}