909 lines
32 KiB
Python
909 lines
32 KiB
Python
from fastapi import FastAPI, HTTPException, Depends, Request
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from fastapi.middleware.cors import CORSMiddleware
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import httpx
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from datetime import datetime, timedelta
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import asyncio, time, os
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from auth import router as auth_router, get_current_user, ensure_tables as ensure_auth_tables
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from db import (
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init_schema, ensure_partitions, get_async_pool, async_fetch, async_fetchrow, async_execute,
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close_async_pool,
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)
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import datetime as _dt
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app = FastAPI(title="Arbitrage Engine API")
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_methods=["*"],
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allow_headers=["*"],
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)
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app.include_router(auth_router)
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BINANCE_FAPI = "https://fapi.binance.com/fapi/v1"
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SYMBOLS = ["BTCUSDT", "ETHUSDT", "XRPUSDT", "SOLUSDT"]
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HEADERS = {"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"}
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# 简单内存缓存（history/stats 60秒，rates 3秒）
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_cache: dict = {}
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def get_cache(key: str, ttl: int):
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entry = _cache.get(key)
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if entry and time.time() - entry["ts"] < ttl:
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return entry["data"]
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return None
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def set_cache(key: str, data):
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_cache[key] = {"ts": time.time(), "data": data}
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async def save_snapshot(rates: dict):
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try:
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btc = rates.get("BTC", {})
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eth = rates.get("ETH", {})
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await async_execute(
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"INSERT INTO rate_snapshots (ts, btc_rate, eth_rate, btc_price, eth_price, btc_index_price, eth_index_price) "
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"VALUES ($1,$2,$3,$4,$5,$6,$7)",
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int(time.time()),
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float(btc.get("lastFundingRate", 0)),
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float(eth.get("lastFundingRate", 0)),
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float(btc.get("markPrice", 0)),
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float(eth.get("markPrice", 0)),
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float(btc.get("indexPrice", 0)),
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float(eth.get("indexPrice", 0)),
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)
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except Exception as e:
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pass # 落库失败不影响API响应
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async def background_snapshot_loop():
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"""后台每2秒自动拉取费率+价格并落库"""
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while True:
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try:
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async with httpx.AsyncClient(timeout=5, headers=HEADERS) as client:
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tasks = [client.get(f"{BINANCE_FAPI}/premiumIndex", params={"symbol": s}) for s in SYMBOLS]
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responses = await asyncio.gather(*tasks, return_exceptions=True)
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result = {}
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for sym, resp in zip(SYMBOLS, responses):
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if isinstance(resp, Exception) or resp.status_code != 200:
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continue
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data = resp.json()
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key = sym.replace("USDT", "")
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result[key] = {
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"lastFundingRate": float(data["lastFundingRate"]),
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"markPrice": float(data["markPrice"]),
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"indexPrice": float(data["indexPrice"]),
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}
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if result:
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await save_snapshot(result)
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except Exception:
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pass
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await asyncio.sleep(2)
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@app.on_event("startup")
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async def startup():
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# 初始化PG schema
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init_schema()
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ensure_auth_tables()
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# 初始化asyncpg池
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await get_async_pool()
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asyncio.create_task(background_snapshot_loop())
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@app.on_event("shutdown")
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async def shutdown():
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await close_async_pool()
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@app.get("/api/health")
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async def health():
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return {"status": "ok", "timestamp": datetime.utcnow().isoformat()}
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@app.get("/api/rates")
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async def get_rates():
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cached = get_cache("rates", 3)
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if cached: return cached
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async with httpx.AsyncClient(timeout=10, headers=HEADERS) as client:
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tasks = [client.get(f"{BINANCE_FAPI}/premiumIndex", params={"symbol": s}) for s in SYMBOLS]
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responses = await asyncio.gather(*tasks)
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result = {}
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for sym, resp in zip(SYMBOLS, responses):
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if resp.status_code != 200:
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raise HTTPException(status_code=502, detail=f"Binance error for {sym}")
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data = resp.json()
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key = sym.replace("USDT", "")
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result[key] = {
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"symbol": sym,
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"markPrice": float(data["markPrice"]),
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"indexPrice": float(data["indexPrice"]),
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"lastFundingRate": float(data["lastFundingRate"]),
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"nextFundingTime": data["nextFundingTime"],
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"timestamp": data["time"],
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}
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set_cache("rates", result)
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asyncio.create_task(save_snapshot(result))
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return result
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@app.get("/api/snapshots")
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async def get_snapshots(hours: int = 24, limit: int = 5000, user: dict = Depends(get_current_user)):
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since = int(time.time()) - hours * 3600
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rows = await async_fetch(
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"SELECT ts, btc_rate, eth_rate, btc_price, eth_price FROM rate_snapshots "
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"WHERE ts >= $1 ORDER BY ts ASC LIMIT $2",
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since, limit
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)
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return {"count": len(rows), "hours": hours, "data": rows}
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@app.get("/api/kline")
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async def get_kline(symbol: str = "BTC", interval: str = "5m", limit: int = 500, user: dict = Depends(get_current_user)):
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interval_secs = {
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"1m": 60, "5m": 300, "30m": 1800,
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"1h": 3600, "4h": 14400, "8h": 28800,
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"1d": 86400, "1w": 604800, "1M": 2592000,
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}
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bar_secs = interval_secs.get(interval, 300)
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rate_col = "btc_rate" if symbol.upper() == "BTC" else "eth_rate"
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price_col = "btc_price" if symbol.upper() == "BTC" else "eth_price"
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since = int(time.time()) - bar_secs * limit
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rows = await async_fetch(
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f"SELECT ts, {rate_col} as rate, {price_col} as price FROM rate_snapshots "
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f"WHERE ts >= $1 ORDER BY ts ASC",
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since
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)
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if not rows:
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return {"symbol": symbol, "interval": interval, "data": []}
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bars: dict = {}
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for r in rows:
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ts, rate, price = r["ts"], r["rate"], r["price"]
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bar_ts = (ts // bar_secs) * bar_secs
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if bar_ts not in bars:
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bars[bar_ts] = {
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"time": bar_ts,
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"open": rate, "high": rate, "low": rate, "close": rate,
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"price_open": price, "price_high": price, "price_low": price, "price_close": price,
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}
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else:
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b = bars[bar_ts]
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b["high"] = max(b["high"], rate)
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b["low"] = min(b["low"], rate)
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b["close"] = rate
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b["price_high"] = max(b["price_high"], price)
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b["price_low"] = min(b["price_low"], price)
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b["price_close"] = price
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data = sorted(bars.values(), key=lambda x: x["time"])[-limit:]
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for b in data:
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for k in ("open", "high", "low", "close"):
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b[k] = round(b[k] * 10000, 4)
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return {"symbol": symbol, "interval": interval, "count": len(data), "data": data}
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@app.get("/api/stats/ytd")
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async def get_stats_ytd(user: dict = Depends(get_current_user)):
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cached = get_cache("stats_ytd", 3600)
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if cached: return cached
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import datetime
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year_start = int(datetime.datetime(datetime.datetime.utcnow().year, 1, 1).timestamp() * 1000)
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end_time = int(time.time() * 1000)
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async with httpx.AsyncClient(timeout=20, headers=HEADERS) as client:
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tasks = [
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client.get(f"{BINANCE_FAPI}/fundingRate",
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params={"symbol": s, "startTime": year_start, "endTime": end_time, "limit": 1000})
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for s in SYMBOLS
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]
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responses = await asyncio.gather(*tasks)
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result = {}
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for sym, resp in zip(SYMBOLS, responses):
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if resp.status_code != 200:
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result[sym.replace("USDT","")] = {"annualized": 0, "count": 0}
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continue
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key = sym.replace("USDT", "")
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rates = [float(item["fundingRate"]) for item in resp.json()]
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if not rates:
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result[key] = {"annualized": 0, "count": 0}
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continue
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mean = sum(rates) / len(rates)
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annualized = round(mean * 3 * 365 * 100, 2)
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result[key] = {"annualized": annualized, "count": len(rates)}
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set_cache("stats_ytd", result)
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return result
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@app.get("/api/signals/history")
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async def get_signals_history(limit: int = 100, user: dict = Depends(get_current_user)):
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try:
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rows = await async_fetch(
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"SELECT id, symbol, rate, annualized, sent_at, message FROM signal_logs ORDER BY sent_at DESC LIMIT $1",
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limit
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)
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return {"items": rows}
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except Exception as e:
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return {"items": [], "error": str(e)}
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@app.get("/api/history")
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async def get_history(user: dict = Depends(get_current_user)):
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cached = get_cache("history", 60)
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if cached: return cached
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end_time = int(datetime.utcnow().timestamp() * 1000)
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start_time = int((datetime.utcnow() - timedelta(days=7)).timestamp() * 1000)
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async with httpx.AsyncClient(timeout=15, headers=HEADERS) as client:
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tasks = [
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client.get(f"{BINANCE_FAPI}/fundingRate",
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params={"symbol": s, "startTime": start_time, "endTime": end_time, "limit": 1000})
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for s in SYMBOLS
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]
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responses = await asyncio.gather(*tasks)
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result = {}
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for sym, resp in zip(SYMBOLS, responses):
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if resp.status_code != 200:
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raise HTTPException(status_code=502, detail=f"Binance history error for {sym}")
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key = sym.replace("USDT", "")
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result[key] = [
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{"fundingTime": item["fundingTime"], "fundingRate": float(item["fundingRate"]),
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"timestamp": datetime.utcfromtimestamp(item["fundingTime"] / 1000).isoformat()}
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for item in resp.json()
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]
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set_cache("history", result)
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return result
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@app.get("/api/stats")
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async def get_stats(user: dict = Depends(get_current_user)):
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cached = get_cache("stats", 60)
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if cached: return cached
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end_time = int(datetime.utcnow().timestamp() * 1000)
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start_time = int((datetime.utcnow() - timedelta(days=7)).timestamp() * 1000)
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async with httpx.AsyncClient(timeout=15, headers=HEADERS) as client:
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tasks = [
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client.get(f"{BINANCE_FAPI}/fundingRate",
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params={"symbol": s, "startTime": start_time, "endTime": end_time, "limit": 1000})
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for s in SYMBOLS
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]
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responses = await asyncio.gather(*tasks)
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stats = {}
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for sym, resp in zip(SYMBOLS, responses):
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if resp.status_code != 200:
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raise HTTPException(status_code=502, detail=f"Binance stats error for {sym}")
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key = sym.replace("USDT", "")
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rates = [float(item["fundingRate"]) for item in resp.json()]
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if not rates:
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stats[key] = {"mean7d": 0, "annualized": 0, "count": 0}
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continue
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mean = sum(rates) / len(rates)
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annualized = mean * 3 * 365 * 100
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stats[key] = {
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"mean7d": round(mean * 100, 6),
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"annualized": round(annualized, 2),
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"count": len(rates),
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}
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btc_ann = stats.get("BTC", {}).get("annualized", 0)
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eth_ann = stats.get("ETH", {}).get("annualized", 0)
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btc_mean = stats.get("BTC", {}).get("mean7d", 0)
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eth_mean = stats.get("ETH", {}).get("mean7d", 0)
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stats["combo"] = {
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"mean7d": round((btc_mean + eth_mean) / 2, 6),
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"annualized": round((btc_ann + eth_ann) / 2, 2),
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}
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set_cache("stats", stats)
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return stats
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# ─── aggTrades 查询接口（PG版）───────────────────────────────────
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@app.get("/api/trades/meta")
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async def get_trades_meta(user: dict = Depends(get_current_user)):
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rows = await async_fetch("SELECT symbol, last_agg_id, last_time_ms, updated_at FROM agg_trades_meta")
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result = {}
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for r in rows:
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sym = r["symbol"].replace("USDT", "")
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result[sym] = {
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"last_agg_id": r["last_agg_id"],
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"last_time_ms": r["last_time_ms"],
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"updated_at": r["updated_at"],
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}
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return result
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@app.get("/api/trades/summary")
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async def get_trades_summary(
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symbol: str = "BTC",
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start_ms: int = 0,
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end_ms: int = 0,
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interval: str = "1m",
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user: dict = Depends(get_current_user),
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):
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if end_ms == 0:
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end_ms = int(time.time() * 1000)
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if start_ms == 0:
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start_ms = end_ms - 3600 * 1000
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interval_ms = {"1m": 60000, "5m": 300000, "15m": 900000, "1h": 3600000}.get(interval, 60000)
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sym_full = symbol.upper() + "USDT"
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# PG原生聚合，比Python循环快100倍
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rows = await async_fetch(
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"""
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SELECT
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(time_ms / $4) * $4 AS bar_ms,
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ROUND(SUM(CASE WHEN is_buyer_maker = 0 THEN qty ELSE 0 END)::numeric, 4) AS buy_vol,
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ROUND(SUM(CASE WHEN is_buyer_maker = 1 THEN qty ELSE 0 END)::numeric, 4) AS sell_vol,
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COUNT(*) AS trade_count,
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ROUND((SUM(price * qty) / NULLIF(SUM(qty), 0))::numeric, 2) AS vwap,
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ROUND(MAX(qty)::numeric, 4) AS max_qty
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FROM agg_trades
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WHERE symbol = $1 AND time_ms >= $2 AND time_ms < $3
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GROUP BY bar_ms
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ORDER BY bar_ms ASC
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""",
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sym_full, start_ms, end_ms, interval_ms
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)
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result = []
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for r in rows:
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buy = float(r["buy_vol"])
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sell = float(r["sell_vol"])
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result.append({
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"time_ms": r["bar_ms"],
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"buy_vol": buy,
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"sell_vol": sell,
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"delta": round(buy - sell, 4),
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"total_vol": round(buy + sell, 4),
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"trade_count": r["trade_count"],
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"vwap": float(r["vwap"]) if r["vwap"] else 0,
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"max_qty": float(r["max_qty"]),
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})
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return {"symbol": symbol, "interval": interval, "count": len(result), "data": result}
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@app.get("/api/trades/latest")
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async def get_trades_latest(
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symbol: str = "BTC",
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limit: int = 30,
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user: dict = Depends(get_current_user),
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):
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cache_key = f"trades_latest_{symbol}_{limit}"
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cached = get_cache(cache_key, 2)
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if cached: return cached
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sym_full = symbol.upper() + "USDT"
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rows = await async_fetch(
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"SELECT agg_id, price, qty, time_ms, is_buyer_maker FROM agg_trades "
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"WHERE symbol = $1 ORDER BY time_ms DESC, agg_id DESC LIMIT $2",
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sym_full, limit
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)
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result = {"symbol": symbol, "count": len(rows), "data": rows}
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set_cache(cache_key, result)
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return result
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@app.get("/api/collector/health")
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async def collector_health(user: dict = Depends(get_current_user)):
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now_ms = int(time.time() * 1000)
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rows = await async_fetch("SELECT symbol, last_agg_id, last_time_ms FROM agg_trades_meta")
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status = {}
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for r in rows:
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sym = r["symbol"].replace("USDT", "")
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lag_s = (now_ms - (r["last_time_ms"] or 0)) / 1000
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status[sym] = {
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"last_agg_id": r["last_agg_id"],
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"lag_seconds": round(lag_s, 1),
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"healthy": lag_s < 30,
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}
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return {"collector": status, "timestamp": now_ms}
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# ─── V5 Signal Engine API ────────────────────────────────────────
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@app.get("/api/signals/indicators")
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async def get_signal_indicators(
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symbol: str = "BTC",
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minutes: int = 60,
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user: dict = Depends(get_current_user),
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):
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sym_full = symbol.upper() + "USDT"
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now_ms = int(time.time() * 1000)
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start_ms = now_ms - minutes * 60 * 1000
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rows = await async_fetch(
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"SELECT ts, cvd_fast, cvd_mid, cvd_day, atr_5m, vwap_30m, price, score, signal "
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"FROM signal_indicators_1m WHERE symbol = $1 AND ts >= $2 ORDER BY ts ASC",
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sym_full, start_ms
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)
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return {"symbol": symbol, "count": len(rows), "data": rows}
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@app.get("/api/signals/latest")
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async def get_signal_latest(user: dict = Depends(get_current_user)):
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result = {}
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for sym in SYMBOLS:
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row = await async_fetchrow(
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"SELECT ts, cvd_fast, cvd_mid, cvd_day, cvd_fast_slope, atr_5m, atr_percentile, "
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"vwap_30m, price, p95_qty, p99_qty, score, signal "
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"FROM signal_indicators WHERE symbol = $1 ORDER BY ts DESC LIMIT 1",
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sym
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)
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if row:
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result[sym.replace("USDT", "")] = row
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return result
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@app.get("/api/signals/market-indicators")
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async def get_market_indicators(user: dict = Depends(get_current_user)):
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"""返回最新的market_indicators数据（V5.1新增4个数据源）"""
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result = {}
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for sym in SYMBOLS:
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indicators = {}
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for ind_type in ["long_short_ratio", "top_trader_position", "open_interest_hist", "coinbase_premium"]:
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row = await async_fetchrow(
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"SELECT value, timestamp_ms FROM market_indicators WHERE symbol = $1 AND indicator_type = $2 ORDER BY timestamp_ms DESC LIMIT 1",
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sym,
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ind_type,
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)
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if row:
|
||
val = row["value"]
|
||
if isinstance(val, str):
|
||
import json as _json
|
||
try:
|
||
val = _json.loads(val)
|
||
except Exception:
|
||
pass
|
||
indicators[ind_type] = {"value": val, "ts": row["timestamp_ms"]}
|
||
result[sym.replace("USDT", "")] = indicators
|
||
return result
|
||
|
||
|
||
@app.get("/api/signals/signal-history")
|
||
async def get_signal_history(
|
||
symbol: str = "BTC",
|
||
limit: int = 50,
|
||
user: dict = Depends(get_current_user),
|
||
):
|
||
"""返回最近的信号历史（只返回有信号的记录）"""
|
||
sym_full = symbol.upper() + "USDT"
|
||
rows = await async_fetch(
|
||
"SELECT ts, score, signal FROM signal_indicators "
|
||
"WHERE symbol = $1 AND signal IS NOT NULL "
|
||
"ORDER BY ts DESC LIMIT $2",
|
||
sym_full, limit
|
||
)
|
||
return {"symbol": symbol, "count": len(rows), "data": rows}
|
||
|
||
|
||
@app.get("/api/signals/trades")
|
||
async def get_signal_trades(
|
||
status: str = "all",
|
||
limit: int = 50,
|
||
user: dict = Depends(get_current_user),
|
||
):
|
||
if status == "all":
|
||
rows = await async_fetch(
|
||
"SELECT * FROM signal_trades ORDER BY ts_open DESC LIMIT $1", limit
|
||
)
|
||
else:
|
||
rows = await async_fetch(
|
||
"SELECT * FROM signal_trades WHERE status = $1 ORDER BY ts_open DESC LIMIT $2",
|
||
status, limit
|
||
)
|
||
return {"count": len(rows), "data": rows}
|
||
|
||
|
||
# ─── 模拟盘 API ──────────────────────────────────────────────────
|
||
|
||
# 模拟盘配置状态（与signal_engine共享的运行时状态）
|
||
paper_config = {
|
||
"enabled": False,
|
||
"initial_balance": 10000,
|
||
"risk_per_trade": 0.02,
|
||
"max_positions": 4,
|
||
"tier_multiplier": {"light": 0.5, "standard": 1.0, "heavy": 1.5},
|
||
}
|
||
|
||
|
||
@app.get("/api/paper/config")
|
||
async def paper_get_config(user: dict = Depends(get_current_user)):
|
||
"""获取模拟盘配置"""
|
||
return paper_config
|
||
|
||
|
||
@app.post("/api/paper/config")
|
||
async def paper_set_config(request: Request, user: dict = Depends(get_current_user)):
|
||
"""修改模拟盘配置（仅admin）"""
|
||
if user.get("role") != "admin":
|
||
raise HTTPException(status_code=403, detail="仅管理员可修改")
|
||
body = await request.json()
|
||
for k in ["enabled", "initial_balance", "risk_per_trade", "max_positions"]:
|
||
if k in body:
|
||
paper_config[k] = body[k]
|
||
# 写入配置文件让signal_engine也能读到
|
||
import json
|
||
config_path = os.path.join(os.path.dirname(__file__), "paper_config.json")
|
||
with open(config_path, "w") as f:
|
||
json.dump(paper_config, f, indent=2)
|
||
return {"ok": True, "config": paper_config}
|
||
|
||
|
||
@app.get("/api/paper/summary")
|
||
async def paper_summary(user: dict = Depends(get_current_user)):
|
||
"""模拟盘总览"""
|
||
closed = await async_fetch(
|
||
"SELECT pnl_r, direction FROM paper_trades WHERE status NOT IN ('active','tp1_hit')"
|
||
)
|
||
active = await async_fetch(
|
||
"SELECT id FROM paper_trades WHERE status IN ('active','tp1_hit')"
|
||
)
|
||
first = await async_fetchrow("SELECT MIN(created_at) as start FROM paper_trades")
|
||
|
||
total = len(closed)
|
||
wins = len([r for r in closed if r["pnl_r"] > 0])
|
||
total_pnl = sum(r["pnl_r"] for r in closed)
|
||
win_rate = (wins / total * 100) if total > 0 else 0
|
||
gross_profit = sum(r["pnl_r"] for r in closed if r["pnl_r"] > 0)
|
||
gross_loss = abs(sum(r["pnl_r"] for r in closed if r["pnl_r"] <= 0))
|
||
profit_factor = (gross_profit / gross_loss) if gross_loss > 0 else 0
|
||
|
||
return {
|
||
"total_trades": total,
|
||
"win_rate": round(win_rate, 1),
|
||
"total_pnl": round(total_pnl, 2),
|
||
"active_positions": len(active),
|
||
"profit_factor": round(profit_factor, 2),
|
||
"start_time": str(first["start"]) if first and first["start"] else None,
|
||
}
|
||
|
||
|
||
@app.get("/api/paper/positions")
|
||
async def paper_positions(user: dict = Depends(get_current_user)):
|
||
"""当前活跃持仓（含实时价格和浮动盈亏）"""
|
||
rows = await async_fetch(
|
||
"SELECT id, symbol, direction, score, tier, entry_price, entry_ts, "
|
||
"tp1_price, tp2_price, sl_price, tp1_hit, status, atr_at_entry "
|
||
"FROM paper_trades WHERE status IN ('active','tp1_hit') ORDER BY entry_ts DESC"
|
||
)
|
||
# 从币安API获取实时价格
|
||
prices = {}
|
||
symbols_needed = list(set(r["symbol"] for r in rows))
|
||
if symbols_needed:
|
||
try:
|
||
async with httpx.AsyncClient(timeout=5) as client:
|
||
resp = await client.get("https://fapi.binance.com/fapi/v1/ticker/price")
|
||
if resp.status_code == 200:
|
||
for item in resp.json():
|
||
if item["symbol"] in symbols_needed:
|
||
prices[item["symbol"]] = float(item["price"])
|
||
except Exception:
|
||
pass
|
||
# fallback: 如果币安API失败，用signal_indicators
|
||
for r in rows:
|
||
sym = r["symbol"]
|
||
if sym not in prices:
|
||
try:
|
||
latest = await async_fetchrow(
|
||
"SELECT price FROM signal_indicators WHERE symbol=$1 ORDER BY ts DESC LIMIT 1", sym
|
||
)
|
||
prices[sym] = latest["price"] if latest else 0
|
||
except Exception:
|
||
prices[sym] = 0
|
||
|
||
result = []
|
||
for r in rows:
|
||
d = dict(r)
|
||
current_price = prices.get(r["symbol"], 0)
|
||
d["current_price"] = current_price
|
||
# 浮动盈亏(R)
|
||
entry = r["entry_price"]
|
||
atr = r["atr_at_entry"] or 1
|
||
risk_distance = 2.0 * 0.7 * atr
|
||
if risk_distance > 0 and entry > 0:
|
||
if r["direction"] == "LONG":
|
||
d["unrealized_pnl_r"] = round((current_price - entry) / risk_distance, 2)
|
||
else:
|
||
d["unrealized_pnl_r"] = round((entry - current_price) / risk_distance, 2)
|
||
# 浮动盈亏(USDT) — 假设1R = risk_per_trade
|
||
d["unrealized_pnl_usdt"] = round(d["unrealized_pnl_r"] * 200, 2) # 2% of 10000
|
||
else:
|
||
d["unrealized_pnl_r"] = 0
|
||
d["unrealized_pnl_usdt"] = 0
|
||
result.append(d)
|
||
return {"data": result}
|
||
|
||
|
||
@app.get("/api/paper/trades")
|
||
async def paper_trades(
|
||
symbol: str = "all",
|
||
result: str = "all",
|
||
limit: int = 100,
|
||
user: dict = Depends(get_current_user),
|
||
):
|
||
"""历史交易列表"""
|
||
conditions = ["status NOT IN ('active','tp1_hit')"]
|
||
params = []
|
||
idx = 1
|
||
|
||
if symbol != "all":
|
||
conditions.append(f"symbol = ${idx}")
|
||
params.append(symbol.upper() + "USDT")
|
||
idx += 1
|
||
|
||
if result == "win":
|
||
conditions.append("pnl_r > 0")
|
||
elif result == "loss":
|
||
conditions.append("pnl_r <= 0")
|
||
|
||
where = " AND ".join(conditions)
|
||
params.append(limit)
|
||
rows = await async_fetch(
|
||
f"SELECT id, symbol, direction, score, tier, entry_price, exit_price, "
|
||
f"entry_ts, exit_ts, pnl_r, status, tp1_hit "
|
||
f"FROM paper_trades WHERE {where} ORDER BY exit_ts DESC LIMIT ${idx}",
|
||
*params
|
||
)
|
||
return {"count": len(rows), "data": rows}
|
||
|
||
|
||
@app.get("/api/paper/equity-curve")
|
||
async def paper_equity_curve(user: dict = Depends(get_current_user)):
|
||
"""权益曲线"""
|
||
rows = await async_fetch(
|
||
"SELECT exit_ts, pnl_r FROM paper_trades WHERE status NOT IN ('active','tp1_hit') ORDER BY exit_ts ASC"
|
||
)
|
||
cumulative = 0.0
|
||
curve = []
|
||
for r in rows:
|
||
cumulative += r["pnl_r"]
|
||
curve.append({"ts": r["exit_ts"], "pnl": round(cumulative, 2)})
|
||
return {"data": curve}
|
||
|
||
|
||
@app.get("/api/paper/stats")
|
||
async def paper_stats(user: dict = Depends(get_current_user)):
|
||
"""详细统计"""
|
||
rows = await async_fetch(
|
||
"SELECT symbol, direction, pnl_r, tier, entry_ts, exit_ts "
|
||
"FROM paper_trades WHERE status NOT IN ('active','tp1_hit')"
|
||
)
|
||
if not rows:
|
||
return {"error": "暂无数据"}
|
||
|
||
total = len(rows)
|
||
wins = [r for r in rows if r["pnl_r"] > 0]
|
||
losses = [r for r in rows if r["pnl_r"] <= 0]
|
||
|
||
# 基础统计
|
||
win_rate = len(wins) / total * 100
|
||
avg_win = sum(r["pnl_r"] for r in wins) / len(wins) if wins else 0
|
||
avg_loss = abs(sum(r["pnl_r"] for r in losses)) / len(losses) if losses else 0
|
||
win_loss_ratio = avg_win / avg_loss if avg_loss > 0 else 0
|
||
|
||
# MDD
|
||
peak = 0.0
|
||
mdd = 0.0
|
||
running = 0.0
|
||
for r in sorted(rows, key=lambda x: x["exit_ts"] or 0):
|
||
running += r["pnl_r"]
|
||
peak = max(peak, running)
|
||
mdd = max(mdd, peak - running)
|
||
|
||
# 夏普
|
||
returns = [r["pnl_r"] for r in rows]
|
||
if len(returns) > 1:
|
||
import statistics
|
||
avg_ret = statistics.mean(returns)
|
||
std_ret = statistics.stdev(returns)
|
||
sharpe = (avg_ret / std_ret) * (252 ** 0.5) if std_ret > 0 else 0
|
||
else:
|
||
sharpe = 0
|
||
|
||
# 按币种
|
||
by_symbol = {}
|
||
for r in rows:
|
||
s = r["symbol"].replace("USDT", "")
|
||
if s not in by_symbol:
|
||
by_symbol[s] = {"total": 0, "wins": 0}
|
||
by_symbol[s]["total"] += 1
|
||
if r["pnl_r"] > 0:
|
||
by_symbol[s]["wins"] += 1
|
||
symbol_stats = {s: {"total": v["total"], "win_rate": round(v["wins"]/v["total"]*100, 1)} for s, v in by_symbol.items()}
|
||
|
||
# 按方向
|
||
longs = [r for r in rows if r["direction"] == "LONG"]
|
||
shorts = [r for r in rows if r["direction"] == "SHORT"]
|
||
long_wr = len([r for r in longs if r["pnl_r"] > 0]) / len(longs) * 100 if longs else 0
|
||
short_wr = len([r for r in shorts if r["pnl_r"] > 0]) / len(shorts) * 100 if shorts else 0
|
||
|
||
# 按档位
|
||
by_tier = {}
|
||
for r in rows:
|
||
t = r["tier"]
|
||
if t not in by_tier:
|
||
by_tier[t] = {"total": 0, "wins": 0}
|
||
by_tier[t]["total"] += 1
|
||
if r["pnl_r"] > 0:
|
||
by_tier[t]["wins"] += 1
|
||
tier_stats = {t: {"total": v["total"], "win_rate": round(v["wins"]/v["total"]*100, 1)} for t, v in by_tier.items()}
|
||
|
||
return {
|
||
"total": total,
|
||
"win_rate": round(win_rate, 1),
|
||
"avg_win": round(avg_win, 2),
|
||
"avg_loss": round(avg_loss, 2),
|
||
"win_loss_ratio": round(win_loss_ratio, 2),
|
||
"mdd": round(mdd, 2),
|
||
"sharpe": round(sharpe, 2),
|
||
"long_win_rate": round(long_wr, 1),
|
||
"long_count": len(longs),
|
||
"short_win_rate": round(short_wr, 1),
|
||
"short_count": len(shorts),
|
||
"by_symbol": symbol_stats,
|
||
"by_tier": tier_stats,
|
||
}
|
||
|
||
|
||
# ─── 服务器状态监控 ───────────────────────────────────────────────
|
||
|
||
import shutil, subprocess, psutil
|
||
|
||
# 服务器状态缓存（避免重复调用慢操作）
|
||
_server_cache: dict = {"data": None, "ts": 0}
|
||
_PM2_BIN = None
|
||
|
||
def _find_pm2_bin():
|
||
"""找到pm2二进制路径，避免每次走npx"""
|
||
global _PM2_BIN
|
||
if _PM2_BIN:
|
||
return _PM2_BIN
|
||
import shutil as _sh
|
||
for p in ["/home/fzq1228/.local/bin/pm2", "/usr/local/bin/pm2", "/usr/bin/pm2"]:
|
||
if os.path.exists(p):
|
||
_PM2_BIN = p
|
||
return p
|
||
found = _sh.which("pm2")
|
||
if found:
|
||
_PM2_BIN = found
|
||
return found
|
||
return "npx pm2"
|
||
|
||
# 启动时初始化CPU采样（首次调用不阻塞）
|
||
psutil.cpu_percent(interval=None)
|
||
|
||
@app.get("/api/server/status")
|
||
async def get_server_status(user: dict = Depends(get_current_user)):
|
||
"""服务器全状态：CPU/内存/硬盘/负载/PM2进程/PG数据库/回补进度"""
|
||
|
||
# 5秒缓存，避免频繁调用慢操作
|
||
now = time.time()
|
||
if _server_cache["data"] and (now - _server_cache["ts"]) < 5:
|
||
return _server_cache["data"]
|
||
|
||
# CPU（非阻塞，取上次采样间隔的值）
|
||
cpu_percent = psutil.cpu_percent(interval=None)
|
||
cpu_count = psutil.cpu_count()
|
||
|
||
# 内存
|
||
mem = psutil.virtual_memory()
|
||
swap = psutil.swap_memory()
|
||
|
||
# 硬盘
|
||
disk = shutil.disk_usage("/")
|
||
|
||
# 负载
|
||
load1, load5, load15 = os.getloadavg()
|
||
|
||
# Uptime
|
||
boot_time = psutil.boot_time()
|
||
uptime_s = time.time() - boot_time
|
||
|
||
# 网络IO
|
||
net = psutil.net_io_counters()
|
||
|
||
# PM2进程状态（直接调pm2二进制，不走npx）
|
||
pm2_procs = []
|
||
try:
|
||
pm2_bin = _find_pm2_bin()
|
||
cmd = [pm2_bin, "jlist"] if not pm2_bin.startswith("npx") else ["npx", "pm2", "jlist"]
|
||
result = subprocess.run(
|
||
cmd,
|
||
capture_output=True, text=True, timeout=5
|
||
)
|
||
import json as _json
|
||
procs = _json.loads(result.stdout)
|
||
for p in procs:
|
||
pm2_procs.append({
|
||
"name": p.get("name", ""),
|
||
"status": p.get("pm2_env", {}).get("status", "unknown"),
|
||
"cpu": p.get("monit", {}).get("cpu", 0),
|
||
"memory_mb": round(p.get("monit", {}).get("memory", 0) / 1024 / 1024, 1),
|
||
"restarts": p.get("pm2_env", {}).get("restart_time", 0),
|
||
"uptime_ms": p.get("pm2_env", {}).get("pm_uptime", 0),
|
||
"pid": p.get("pid", 0),
|
||
})
|
||
except Exception:
|
||
pm2_procs = []
|
||
|
||
# PG数据库大小 + agg_trades条数（用估算值，快1000倍）
|
||
pg_info = {}
|
||
try:
|
||
row = await async_fetchrow(
|
||
"SELECT pg_database_size(current_database()) as db_size"
|
||
)
|
||
pg_info["db_size_mb"] = round(row["db_size"] / 1024 / 1024, 1) if row else 0
|
||
|
||
# 用PG统计信息估算行数（毫秒级，而非COUNT(*)的秒级全表扫描）
|
||
row2 = await async_fetchrow(
|
||
"SELECT SUM(n_live_tup)::bigint as cnt FROM pg_stat_user_tables WHERE relname LIKE 'agg_trades%'"
|
||
)
|
||
pg_info["agg_trades_count"] = row2["cnt"] if row2 and row2["cnt"] else 0
|
||
|
||
row3 = await async_fetchrow(
|
||
"SELECT n_live_tup::bigint as cnt FROM pg_stat_user_tables WHERE relname = 'rate_snapshots'"
|
||
)
|
||
pg_info["rate_snapshots_count"] = row3["cnt"] if row3 else 0
|
||
|
||
# 各symbol最新数据时间
|
||
meta_rows = await async_fetch("SELECT symbol, last_time_ms, earliest_time_ms FROM agg_trades_meta")
|
||
pg_info["symbols"] = {}
|
||
for m in meta_rows:
|
||
sym = m["symbol"].replace("USDT", "")
|
||
pg_info["symbols"][sym] = {
|
||
"latest_ms": m["last_time_ms"],
|
||
"earliest_ms": m["earliest_time_ms"],
|
||
"span_hours": round((m["last_time_ms"] - m["earliest_time_ms"]) / 3600000, 1),
|
||
}
|
||
except Exception:
|
||
pass
|
||
|
||
# 回补进程
|
||
backfill_running = False
|
||
try:
|
||
for proc in psutil.process_iter(["pid", "cmdline"]):
|
||
cmdline = " ".join(proc.info.get("cmdline") or [])
|
||
if "backfill_agg_trades" in cmdline:
|
||
backfill_running = True
|
||
break
|
||
except Exception:
|
||
pass
|
||
|
||
result = {
|
||
"timestamp": int(time.time() * 1000),
|
||
"cpu": {
|
||
"percent": cpu_percent,
|
||
"cores": cpu_count,
|
||
},
|
||
"memory": {
|
||
"total_gb": round(mem.total / 1024**3, 1),
|
||
"used_gb": round(mem.used / 1024**3, 1),
|
||
"percent": mem.percent,
|
||
"swap_percent": swap.percent,
|
||
},
|
||
"disk": {
|
||
"total_gb": round(disk.total / 1024**3, 1),
|
||
"used_gb": round(disk.used / 1024**3, 1),
|
||
"free_gb": round(disk.free / 1024**3, 1),
|
||
"percent": round(disk.used / disk.total * 100, 1),
|
||
},
|
||
"load": {
|
||
"load1": round(load1, 2),
|
||
"load5": round(load5, 2),
|
||
"load15": round(load15, 2),
|
||
},
|
||
"uptime_hours": round(uptime_s / 3600, 1),
|
||
"network": {
|
||
"bytes_sent_gb": round(net.bytes_sent / 1024**3, 2),
|
||
"bytes_recv_gb": round(net.bytes_recv / 1024**3, 2),
|
||
},
|
||
"pm2": pm2_procs,
|
||
"postgres": pg_info,
|
||
"backfill_running": backfill_running,
|
||
}
|
||
_server_cache["data"] = result
|
||
_server_cache["ts"] = now
|
||
return result
|