693 lines
25 KiB
Python
693 lines
25 KiB
Python
import os
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import time
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import uuid
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import datetime
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from dataclasses import dataclass
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from tqdm import tqdm
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from loguru import logger
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from bitmart.api_contract import APIContract
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from bitmart.lib.cloud_exceptions import APIException
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from 交易.tools import send_dingtalk_message
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@dataclass
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class StrategyConfig:
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# =============================
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# 1m | ETH 永续 | 控止损≤5/日
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# =============================
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# ===== 合约 =====
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contract_symbol: str = "ETHUSDT"
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open_type: str = "cross"
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leverage: str = "30" # 50 -> 30：显著降低1m噪声导致的连环止损与回撤波动
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# ===== K线与指标 =====
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step_min: int = 1
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lookback_min: int = 240
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ema_len: int = 36 # 30 -> 36：均值更稳，信号更挑剔
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atr_len: int = 14
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# ===== 动态阈值基础（自适应行情）=====
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entry_dev_floor: float = 0.0012 # 0.10% -> 0.12%：过滤小噪声进场
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tp_floor: float = 0.0006 # 0.05% -> 0.06%：更接近“净盈利”
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sl_floor: float = 0.0018 # 0.15% -> 0.18%：ETH 1m插针多，底线略放宽
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# 更挑剔、更少止损（进场更苛刻；止损不过度随波动放大）
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entry_k: float = 1.45 # 1.20 -> 1.45：减少进场频率
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tp_k: float = 0.65 # 0.60 -> 0.65：略抬止盈
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sl_k: float = 1.05 # 1.20 -> 1.05：配合sl_floor，避免高波动下止损无限变大
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# ===== 时间/冷却 =====
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max_hold_sec: int = 75 # 90/120 -> 75：1m回归不恋战
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cooldown_sec_after_exit: int = 20 # 10 -> 20：减少“刚出又进”连环单
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# ===== 下单/仓位 =====
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risk_percent: float = 0.004 # 0.005 -> 0.004：再压一点波动，更贴合止损≤5/日
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min_size: int = 1
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max_size: int = 5000
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# ===== 日内风控 =====
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daily_loss_limit: float = 0.02 # -2% 停机
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daily_profit_cap: float = 0.01 # +1% 封顶停机
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# ===== 危险模式过滤（1m ETH 更敏感）=====
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atr_ratio_kill: float = 0.0038 # 0.0045 -> 0.0038：更早暂停开仓
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big_body_kill: float = 0.010 # 0.012 -> 0.010：更敏感
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# ===== 轮询节奏 =====
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klines_refresh_sec: int = 10
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tick_refresh_sec: int = 1
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status_notify_sec: int = 60
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# =========================================================
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# ✅ 止损后同向入场加门槛（但不禁止同向重入）
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# =========================================================
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reentry_penalty_mult: float = 1.55 # 同向入场门槛×1.55：大幅降低连环止损概率
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reentry_penalty_max_sec: int = 180 # 罚时最长持续
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reset_band_k: float = 0.45 # dev回到更靠近均值才解除罚则
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reset_band_floor: float = 0.0006 # 最小复位带宽（0.06%）
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# =========================================================
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# ✅ 自动阈值：ATR/Price 分位数基准（更稳，不被短时噪声带跑）
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# =========================================================
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vol_baseline_window: int = 120
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vol_baseline_quantile: float = 0.65
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vol_scale_min: float = 0.80
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vol_scale_max: float = 1.60
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# =========================================================
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# ✅ 升级：止损后同方向 SL 放宽幅度与“止损时 vol_scale”联动
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# =========================================================
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post_sl_sl_max_sec: int = 90 # 只照顾“扫损后很快反弹”的窗口
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post_sl_mult_min: float = 1.02
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post_sl_mult_max: float = 1.16
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post_sl_vol_alpha: float = 0.20 # mult = 1 + alpha*(vol_scale_at_sl - 1)
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class BitmartFuturesMeanReversionBot:
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def __init__(self, cfg: StrategyConfig):
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self.cfg = cfg
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# ✅ 只从环境变量读（请务必更换曾经硬编码泄露过的 key）
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self.api_key = os.getenv("BITMART_API_KEY", "").strip()
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self.secret_key = os.getenv("BITMART_SECRET_KEY", "").strip()
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self.memo = os.getenv("BITMART_MEMO", "合约交易").strip()
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if not self.api_key or not self.secret_key:
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raise RuntimeError("请先设置环境变量 BITMART_API_KEY / BITMART_SECRET_KEY / BITMART_MEMO(可选)")
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self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15))
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# 持仓状态: -1 空, 0 无, 1 多
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self.pos = 0
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self.entry_price = None
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self.entry_ts = None
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self.last_exit_ts = 0
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# 日内权益基准
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self.day_start_equity = None
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self.trading_enabled = True
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self.day_tag = datetime.date.today()
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# 缓存
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self._klines_cache = None
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self._klines_cache_ts = 0
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self._last_status_notify_ts = 0
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# ✅ 止损后“同向入场加门槛”状态
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self.last_sl_dir = 0 # 1=多止损，-1=空止损，0=无
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self.last_sl_ts = 0.0
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# ✅ 止损后“同方向 SL 联动放宽”状态
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self.post_sl_dir = 0
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self.post_sl_ts = 0.0
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self.post_sl_vol_scale = 1.0 # 记录止损时的 vol_scale
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self.pbar = tqdm(total=60, desc="运行中(秒)", ncols=90)
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# ----------------- 通用工具 -----------------
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def ding(self, msg, error=False):
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prefix = "❌bitmart：" if error else "🔔bitmart："
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if error:
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for _ in range(3):
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send_dingtalk_message(f"{prefix}{msg}")
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else:
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send_dingtalk_message(f"{prefix}{msg}")
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def set_leverage(self) -> bool:
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try:
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resp = self.contractAPI.post_submit_leverage(
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contract_symbol=self.cfg.contract_symbol,
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leverage=self.cfg.leverage,
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open_type=self.cfg.open_type
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)[0]
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if resp.get("code") == 1000:
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logger.success(f"设置杠杆成功：{self.cfg.open_type} + {self.cfg.leverage}x")
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return True
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logger.error(f"设置杠杆失败: {resp}")
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self.ding(f"设置杠杆失败: {resp}", error=True)
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return False
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except Exception as e:
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logger.error(f"设置杠杆异常: {e}")
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self.ding(f"设置杠杆异常: {e}", error=True)
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return False
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# ----------------- 行情/指标 -----------------
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def get_klines_cached(self):
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now = time.time()
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if self._klines_cache is not None and (now - self._klines_cache_ts) < self.cfg.klines_refresh_sec:
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return self._klines_cache
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kl = self.get_klines()
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if kl:
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self._klines_cache = kl
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self._klines_cache_ts = now
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return self._klines_cache
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def get_klines(self):
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try:
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end_time = int(time.time())
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start_time = end_time - 60 * self.cfg.lookback_min
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resp = self.contractAPI.get_kline(
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contract_symbol=self.cfg.contract_symbol,
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step=self.cfg.step_min,
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start_time=start_time,
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end_time=end_time
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)[0]
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if resp.get("code") != 1000:
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logger.error(f"获取K线失败: {resp}")
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return None
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data = resp.get("data", [])
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formatted = []
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for k in data:
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formatted.append({
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"id": int(k["timestamp"]),
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"open": float(k["open_price"]),
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"high": float(k["high_price"]),
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"low": float(k["low_price"]),
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"close": float(k["close_price"]),
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})
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formatted.sort(key=lambda x: x["id"])
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return formatted
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except Exception as e:
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logger.error(f"获取K线异常: {e}")
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self.ding(f"获取K线异常: {e}", error=True)
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return None
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def get_last_price(self, fallback_close: float) -> float:
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"""
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优先取更实时的最新价；若SDK不支持/字段不同，回退到K线close。
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"""
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try:
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if hasattr(self.contractAPI, "get_contract_details"):
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r = self.contractAPI.get_contract_details(contract_symbol=self.cfg.contract_symbol)[0]
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d = r.get("data") if isinstance(r, dict) else None
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if isinstance(d, dict):
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for key in ("last_price", "mark_price", "index_price"):
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if key in d and d[key] is not None:
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return float(d[key])
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if hasattr(self.contractAPI, "get_ticker"):
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r = self.contractAPI.get_ticker(contract_symbol=self.cfg.contract_symbol)[0]
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d = r.get("data") if isinstance(r, dict) else None
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if isinstance(d, dict):
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for key in ("last_price", "price", "last", "close"):
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if key in d and d[key] is not None:
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return float(d[key])
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except Exception:
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pass
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return float(fallback_close)
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@staticmethod
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def ema(values, n: int) -> float:
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k = 2 / (n + 1)
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e = values[0]
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for v in values[1:]:
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e = v * k + e * (1 - k)
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return e
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@staticmethod
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def atr(klines, n: int) -> float:
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if len(klines) < n + 1:
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return 0.0
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trs = []
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for i in range(-n, 0):
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cur = klines[i]
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prev = klines[i - 1]
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tr = max(
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cur["high"] - cur["low"],
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abs(cur["high"] - prev["close"]),
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abs(cur["low"] - prev["close"]),
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)
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trs.append(tr)
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return sum(trs) / len(trs)
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def is_danger_market(self, klines, price: float) -> bool:
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last = klines[-1]
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body = abs(last["close"] - last["open"]) / last["open"] if last["open"] else 0.0
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if body >= self.cfg.big_body_kill:
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return True
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a = self.atr(klines, self.cfg.atr_len)
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atr_ratio = (a / price) if price > 0 else 0.0
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if atr_ratio >= self.cfg.atr_ratio_kill:
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return True
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return False
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def atr_ratio_baseline(self, klines) -> float:
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"""
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自动阈值基准：最近 window 根的 atr_ratio 分布的 quantile 作为“典型波动”
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"""
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window = self.cfg.vol_baseline_window
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if len(klines) < (window + self.cfg.atr_len + 5):
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return 0.0
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ratios = []
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for i in range(-window, 0):
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sub = klines[:i] if i != 0 else klines
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a = self.atr(sub, self.cfg.atr_len)
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p = sub[-1]["close"]
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if p > 0 and a > 0:
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ratios.append(a / p)
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if not ratios:
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return 0.0
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ratios.sort()
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q = max(0.0, min(1.0, self.cfg.vol_baseline_quantile))
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idx = int(q * (len(ratios) - 1))
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return ratios[idx]
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def dynamic_thresholds(self, atr_ratio: float, base_ratio: float):
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"""
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动态阈值：atr_ratio * vol_scale，并带 floor
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"""
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if base_ratio <= 0:
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vol_scale = 1.0
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else:
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raw = atr_ratio / base_ratio
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vol_scale = max(self.cfg.vol_scale_min, min(self.cfg.vol_scale_max, raw))
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entry_dev = max(self.cfg.entry_dev_floor, self.cfg.entry_k * vol_scale * atr_ratio)
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tp = max(self.cfg.tp_floor, self.cfg.tp_k * vol_scale * atr_ratio)
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sl = max(self.cfg.sl_floor, self.cfg.sl_k * vol_scale * atr_ratio)
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return entry_dev, tp, sl, vol_scale
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# ----------------- 账户/仓位 -----------------
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def get_assets_available(self) -> float:
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try:
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resp = self.contractAPI.get_assets_detail()[0]
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if resp.get("code") != 1000:
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return 0.0
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data = resp.get("data")
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if isinstance(data, dict):
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return float(data.get("available_balance", 0))
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if isinstance(data, list):
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for asset in data:
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if asset.get("currency") == "USDT":
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return float(asset.get("available_balance", 0))
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return 0.0
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except Exception as e:
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logger.error(f"余额查询异常: {e}")
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return 0.0
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def get_position_status(self) -> bool:
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try:
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resp = self.contractAPI.get_position(contract_symbol=self.cfg.contract_symbol)[0]
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if resp.get("code") != 1000:
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return False
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positions = resp.get("data", [])
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if not positions:
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self.pos = 0
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return True
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p = positions[0]
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self.pos = 1 if p["position_type"] == 1 else -1
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return True
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except Exception as e:
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logger.error(f"持仓查询异常: {e}")
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self.ding(f"持仓查询异常: {e}", error=True)
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return False
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def get_equity_proxy(self) -> float:
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return self.get_assets_available()
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def refresh_daily_baseline(self):
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today = datetime.date.today()
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if today != self.day_tag:
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self.day_tag = today
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self.day_start_equity = None
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self.trading_enabled = True
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self.ding(f"新的一天({today})：重置日内风控基准")
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def risk_kill_switch(self):
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self.refresh_daily_baseline()
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equity = self.get_equity_proxy()
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if equity <= 0:
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return
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if self.day_start_equity is None:
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self.day_start_equity = equity
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logger.info(f"日内权益基准设定：{equity:.2f} USDT")
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return
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pnl = (equity - self.day_start_equity) / self.day_start_equity
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if pnl <= -self.cfg.daily_loss_limit:
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self.trading_enabled = False
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self.ding(f"触发日止损：{pnl * 100:.2f}% -> 停机", error=True)
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if pnl >= self.cfg.daily_profit_cap:
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self.trading_enabled = False
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self.ding(f"达到日盈利封顶：{pnl * 100:.2f}% -> 停机")
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# ----------------- 下单 -----------------
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def calculate_size(self, price: float) -> int:
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"""
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保守仓位估算：按 1张≈0.001ETH（沿用你原假设）
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"""
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bal = self.get_assets_available()
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if bal < 10:
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return 0
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margin = bal * self.cfg.risk_percent
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lev = int(self.cfg.leverage)
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size = int((margin * lev) / (price * 0.001))
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size = max(self.cfg.min_size, size)
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size = min(self.cfg.max_size, size)
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return size
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def place_market_order(self, side: int, size: int) -> bool:
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"""
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side:
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1 开多
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2 平空
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3 平多
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4 开空
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"""
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if size <= 0:
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return False
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client_order_id = f"mr_{int(time.time())}_{uuid.uuid4().hex[:8]}"
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try:
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resp = self.contractAPI.post_submit_order(
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contract_symbol=self.cfg.contract_symbol,
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client_order_id=client_order_id,
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side=side,
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mode=1,
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type="market",
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leverage=self.cfg.leverage,
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open_type=self.cfg.open_type,
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size=size
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)[0]
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logger.info(f"order_resp: {resp}")
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if resp.get("code") == 1000:
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return True
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self.ding(f"下单失败: {resp}", error=True)
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return False
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except APIException as e:
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logger.error(f"API下单异常: {e}")
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self.ding(f"API下单异常: {e}", error=True)
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return False
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except Exception as e:
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logger.error(f"下单未知异常: {e}")
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self.ding(f"下单未知异常: {e}", error=True)
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return False
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def close_position_all(self):
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if self.pos == 1:
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ok = self.place_market_order(3, 999999)
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if ok:
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self.pos = 0
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elif self.pos == -1:
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ok = self.place_market_order(2, 999999)
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if ok:
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self.pos = 0
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# ----------------- 止损后机制（核心优化） -----------------
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def _reentry_penalty_active(self, dev: float, entry_dev: float) -> bool:
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"""
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止损后同向入场加门槛：
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- 只要 dev 还没有回到中性区，就对“上次止损方向”的同向入场门槛提高
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- dev 回到 abs(dev) <= reset_band 后自动解除
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- 超过 max_sec 自动解除（避免一直卡住）
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"""
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if self.last_sl_dir == 0:
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return False
|
||
|
||
if (time.time() - self.last_sl_ts) > self.cfg.reentry_penalty_max_sec:
|
||
self.last_sl_dir = 0
|
||
return False
|
||
|
||
reset_band = max(self.cfg.reset_band_floor, self.cfg.reset_band_k * entry_dev)
|
||
if abs(dev) <= reset_band:
|
||
self.last_sl_dir = 0
|
||
return False
|
||
|
||
return True
|
||
|
||
def _post_sl_dynamic_mult(self) -> float:
|
||
"""
|
||
止损后同方向 SL 放宽倍数与“止损时 vol_scale”联动：
|
||
mult = 1 + alpha*(vol_scale_at_sl - 1)
|
||
并做上下限裁剪 + 有效期控制
|
||
"""
|
||
if self.post_sl_dir == 0:
|
||
return 1.0
|
||
|
||
if (time.time() - self.post_sl_ts) > self.cfg.post_sl_sl_max_sec:
|
||
self.post_sl_dir = 0
|
||
self.post_sl_vol_scale = 1.0
|
||
return 1.0
|
||
|
||
raw = 1.0 + self.cfg.post_sl_vol_alpha * (self.post_sl_vol_scale - 1.0)
|
||
raw = max(1.0, raw) # 不缩小止损，只放宽
|
||
return max(self.cfg.post_sl_mult_min, min(self.cfg.post_sl_mult_max, raw))
|
||
|
||
# ----------------- 交易逻辑 -----------------
|
||
def in_cooldown(self) -> bool:
|
||
return (time.time() - self.last_exit_ts) < self.cfg.cooldown_sec_after_exit
|
||
|
||
def maybe_enter(self, price: float, ema_value: float, entry_dev: float):
|
||
if self.pos != 0:
|
||
return
|
||
if self.in_cooldown():
|
||
return
|
||
|
||
dev = (price - ema_value) / ema_value if ema_value else 0.0
|
||
size = self.calculate_size(price)
|
||
if size <= 0:
|
||
return
|
||
|
||
penalty_active = self._reentry_penalty_active(dev, entry_dev)
|
||
|
||
# 基础阈值
|
||
long_th = -entry_dev
|
||
short_th = entry_dev
|
||
|
||
# 若罚则生效：对“上次止损方向”的同向阈值提高
|
||
if penalty_active:
|
||
if self.last_sl_dir == 1:
|
||
long_th = -entry_dev * self.cfg.reentry_penalty_mult
|
||
elif self.last_sl_dir == -1:
|
||
short_th = entry_dev * self.cfg.reentry_penalty_mult
|
||
|
||
logger.info(
|
||
f"enter_check: price={price:.2f}, ema={ema_value:.2f}, dev={dev * 100:.3f}% "
|
||
f"(entry_dev={entry_dev * 100:.3f}%, long_th={long_th * 100:.3f}%, short_th={short_th * 100:.3f}%) "
|
||
f"size={size}, penalty={penalty_active}, last_sl_dir={self.last_sl_dir}"
|
||
)
|
||
|
||
if dev <= long_th:
|
||
if self.place_market_order(1, size): # 开多
|
||
self.pos = 1
|
||
self.entry_price = price
|
||
self.entry_ts = time.time()
|
||
self.ding(f"✅开多：dev={dev * 100:.3f}% size={size} entry={price:.2f}")
|
||
|
||
elif dev >= short_th:
|
||
if self.place_market_order(4, size): # 开空
|
||
self.pos = -1
|
||
self.entry_price = price
|
||
self.entry_ts = time.time()
|
||
self.ding(f"✅开空：dev={dev * 100:.3f}% size={size} entry={price:.2f}")
|
||
|
||
def maybe_exit(self, price: float, tp: float, sl: float, vol_scale: float):
|
||
if self.pos == 0 or self.entry_price is None or self.entry_ts is None:
|
||
return
|
||
|
||
hold = time.time() - self.entry_ts
|
||
|
||
if self.pos == 1:
|
||
pnl = (price - self.entry_price) / self.entry_price
|
||
else:
|
||
pnl = (self.entry_price - price) / self.entry_price
|
||
|
||
# ✅ 同方向止损后：在有效期内放宽 SL（与止损时 vol_scale 联动）
|
||
sl_mult = 1.0
|
||
if self.post_sl_dir == self.pos and self.post_sl_dir != 0:
|
||
sl_mult = self._post_sl_dynamic_mult()
|
||
effective_sl = sl * sl_mult
|
||
|
||
if pnl >= tp:
|
||
self.close_position_all()
|
||
self.ding(f"🎯止盈：pnl={pnl * 100:.3f}% price={price:.2f} tp={tp * 100:.3f}%")
|
||
self.entry_price, self.entry_ts = None, None
|
||
self.last_exit_ts = time.time()
|
||
|
||
elif pnl <= -effective_sl:
|
||
# 记录止损方向
|
||
sl_dir = self.pos # 1=多止损，-1=空止损
|
||
|
||
self.close_position_all()
|
||
self.ding(
|
||
f"🛑止损：pnl={pnl * 100:.3f}% price={price:.2f} "
|
||
f"sl={sl * 100:.3f}% effective_sl={effective_sl * 100:.3f}%(×{sl_mult:.2f})",
|
||
error=True
|
||
)
|
||
|
||
# ✅ 开启：同向入场加门槛
|
||
self.last_sl_dir = sl_dir
|
||
self.last_sl_ts = time.time()
|
||
|
||
# ✅ 开启：同向 SL 联动放宽（记录止损时 vol_scale）
|
||
self.post_sl_dir = sl_dir
|
||
self.post_sl_ts = time.time()
|
||
self.post_sl_vol_scale = float(vol_scale)
|
||
|
||
self.entry_price, self.entry_ts = None, None
|
||
self.last_exit_ts = time.time()
|
||
|
||
elif hold >= self.cfg.max_hold_sec:
|
||
self.close_position_all()
|
||
self.ding(f"⏱超时：hold={int(hold)}s pnl={pnl * 100:.3f}% price={price:.2f}")
|
||
self.entry_price, self.entry_ts = None, None
|
||
self.last_exit_ts = time.time()
|
||
|
||
def notify_status_throttled(self, price: float, ema_value: float, dev: float, bal: float,
|
||
atr_ratio: float, base_ratio: float, vol_scale: float,
|
||
entry_dev: float, tp: float, sl: float):
|
||
now = time.time()
|
||
if (now - self._last_status_notify_ts) < self.cfg.status_notify_sec:
|
||
return
|
||
self._last_status_notify_ts = now
|
||
|
||
direction_str = "多" if self.pos == 1 else ("空" if self.pos == -1 else "无")
|
||
penalty_active = self._reentry_penalty_active(dev, entry_dev)
|
||
|
||
sl_mult = 1.0
|
||
if self.pos != 0 and self.post_sl_dir == self.pos:
|
||
sl_mult = self._post_sl_dynamic_mult()
|
||
|
||
msg = (
|
||
f"【BitMart {self.cfg.contract_symbol}｜1m均值回归(自动阈值+止损智能)】\n"
|
||
f"方向：{direction_str}\n"
|
||
f"现价：{price:.2f}\n"
|
||
f"EMA{self.cfg.ema_len}：{ema_value:.2f}\n"
|
||
f"dev：{dev * 100:.3f}%（entry_dev={entry_dev * 100:.3f}%）\n"
|
||
f"ATR比：{atr_ratio * 100:.3f}% 基准：{base_ratio * 100:.3f}% vol_scale={vol_scale:.2f}\n"
|
||
f"tp/sl：{tp * 100:.3f}% / {sl * 100:.3f}%（postSL×{sl_mult:.2f}, sl@scale={self.post_sl_vol_scale:.2f}）\n"
|
||
f"止损同向加门槛：{'ON' if penalty_active else 'OFF'}（last_sl_dir={self.last_sl_dir}）\n"
|
||
f"可用余额：{bal:.2f} USDT 杠杆：{self.cfg.leverage}x\n"
|
||
f"超时：{self.cfg.max_hold_sec}s 冷却：{self.cfg.cooldown_sec_after_exit}s"
|
||
)
|
||
self.ding(msg)
|
||
|
||
def action(self):
|
||
if not self.set_leverage():
|
||
self.ding("杠杆设置失败，停止运行", error=True)
|
||
return
|
||
|
||
while True:
|
||
now_dt = datetime.datetime.now()
|
||
self.pbar.n = now_dt.second
|
||
self.pbar.refresh()
|
||
|
||
klines = self.get_klines_cached()
|
||
if not klines or len(klines) < (self.cfg.ema_len + 5):
|
||
time.sleep(1)
|
||
continue
|
||
|
||
last_k = klines[-1]
|
||
closes = [k["close"] for k in klines[-(self.cfg.ema_len + 1):]]
|
||
ema_value = self.ema(closes, self.cfg.ema_len)
|
||
|
||
price = self.get_last_price(fallback_close=float(last_k["close"]))
|
||
dev = (price - ema_value) / ema_value if ema_value else 0.0
|
||
|
||
# 自动阈值
|
||
a = self.atr(klines, self.cfg.atr_len)
|
||
atr_ratio = (a / price) if price > 0 else 0.0
|
||
base_ratio = self.atr_ratio_baseline(klines)
|
||
entry_dev, tp, sl, vol_scale = self.dynamic_thresholds(atr_ratio, base_ratio)
|
||
|
||
# 日内风控
|
||
self.risk_kill_switch()
|
||
|
||
# 刷新仓位
|
||
if not self.get_position_status():
|
||
time.sleep(1)
|
||
continue
|
||
|
||
# 停机：平仓+不再开仓
|
||
if not self.trading_enabled:
|
||
if self.pos != 0:
|
||
self.close_position_all()
|
||
time.sleep(5)
|
||
continue
|
||
|
||
# 危险市场：不新开仓（允许已有仓按 tp/sl/超时 退出）
|
||
if self.is_danger_market(klines, price):
|
||
logger.warning("危险模式：高波动/大实体K，暂停开仓")
|
||
self.maybe_exit(price, tp, sl, vol_scale)
|
||
time.sleep(self.cfg.tick_refresh_sec)
|
||
continue
|
||
|
||
# 先出场再入场
|
||
self.maybe_exit(price, tp, sl, vol_scale)
|
||
self.maybe_enter(price, ema_value, entry_dev)
|
||
|
||
# 状态通知（限频）
|
||
bal = self.get_assets_available()
|
||
self.notify_status_throttled(
|
||
price, ema_value, dev, bal,
|
||
atr_ratio, base_ratio, vol_scale,
|
||
entry_dev, tp, sl
|
||
)
|
||
|
||
time.sleep(self.cfg.tick_refresh_sec)
|
||
|
||
|
||
if __name__ == "__main__":
|
||
"""
|
||
Windows PowerShell:
|
||
setx BITMART_API_KEY "你的key"
|
||
setx BITMART_SECRET_KEY "你的secret"
|
||
setx BITMART_MEMO "合约交易"
|
||
重新打开终端再运行。
|
||
|
||
Linux/macOS:
|
||
export BITMART_API_KEY="你的key"
|
||
export BITMART_SECRET_KEY="你的secret"
|
||
export BITMART_MEMO="合约交易"
|
||
"""
|
||
cfg = StrategyConfig()
|
||
bot = BitmartFuturesMeanReversionBot(cfg)
|
||
bot.action()
|
||
|
||
# 9208.96
|