From b5d4f6dfdc2f87b122f9c047982bc4f8a8071f70 Mon Sep 17 00:00:00 2001 From: 27942 <1313123@342> Date: Sun, 1 Feb 2026 19:50:32 +0800 Subject: [PATCH] 14564 --- 1111 | 28 +- bitmart/交易，一直加仓，拉平开仓价位.py | 986 ------ bitmart/优化拿仓版本.py | 458 --- bitmart/回测.py | 83 - bitmart/回测图表.png | Bin 147692 -> 0 bytes bitmart/回测图表_交互式.html | 3888 ----------------------- bitmart/均线回归.py | 866 ----- bitmart/均线自动化开单.py | 1165 ------- bitmart/抓取数据_30分钟.py | 169 - mexc/30分钟.py | 91 +- 10 files changed, 82 insertions(+), 7652 deletions(-) delete mode 100644 bitmart/交易，一直加仓，拉平开仓价位.py delete mode 100644 bitmart/优化拿仓版本.py delete mode 100644 bitmart/回测.py delete mode 100644 bitmart/回测图表.png delete mode 100644 bitmart/回测图表_交互式.html delete mode 100644 bitmart/均线回归.py delete mode 100644 bitmart/均线自动化开单.py delete mode 100644 bitmart/抓取数据_30分钟.py diff --git a/1111 b/1111 index d1ec074..337f7ae 100644 --- a/1111 +++ b/1111 @@ -23,31 +23,7 @@ Abc12345678 yx20250715@gmail.com -3. 更多交易信号 -包住形态（原策略） -锤子线和上吊线 -早晨之星和黄昏之星 -乌云盖顶和刺透形态 -三只乌鸦和三白兵 -移动平均线金叉死叉 -RSI超买超卖 -布林带突破 - -4. 风险管理 -止损止盈：可配置的百分比止损止盈 -时间止损：持仓超过24小时自动平仓 -凯利公式改进版：仓位管理 -最大回撤控制 -手续费考虑：0.05%交易手续费 -申请API原因：我计划通过API实现自动化量化交易策略，以减少人工干预，提高交易效率并减少人为错误。通过API，我能够实时获取市场数据、执行交易指令、监控账户状态，并根据市场变化自动调整策略。 -申请API具体方式用途：我将使用API来获取实时的市场行情数据，执行各种量化策略（如网格交易、动量策略、均值回归等），并进行账户管理。API将自动监控并调整我的交易参数，比如仓位、止损、止盈等，同时还需要定期回测策略和优化模型。 -申请API主要交易什么币种：我主要通过API进行ETH和BTC的合约交易，还有一起其他的主流币 -申请API操作频率：预计API的调用频率将根据市场波动而变化，通常情况下，我的API请求频率大约在每秒5-10次，有时会根据策略的调整需要进行更频繁的请求。 -申请API大概体量：预计每日API请求量为5,000 - 15,000次，具体取决于市场波动和交易策略的复杂度。月度交易量预估为50,000 - 200,000 ETH/BTC。 -申请API对接后预估增长目标：通过API对接，我预计能够实现量化策略的高效执行和自动化交易，减少人工干预和错误。目标是在对接后的3个月内，将交易频率提高50%，并将月盈利提高20%至30%。 - - -45.84 -4998.6 \ No newline at end of file +555.73 +2278 \ No newline at end of file diff --git a/bitmart/交易，一直加仓，拉平开仓价位.py b/bitmart/交易，一直加仓，拉平开仓价位.py deleted file mode 100644 index 7507fab..0000000 --- a/bitmart/交易，一直加仓，拉平开仓价位.py +++ /dev/null @@ -1,986 +0,0 @@ -""" -BitMart 被动做市/高频刷单策略 -核心逻辑：在盘口两侧不断挂单，赚取价差+返佣 -使用浏览器自动化下单，获取高返佣 -""" - -import time -from loguru import logger -from threading import Lock -from dataclasses import dataclass -from bitmart.api_contract import APIContract -from typing import Optional, Dict, List, Tuple -from DrissionPage import ChromiumPage, ChromiumOptions - -from bit_tools import openBrowser - - -# ================================================================ -# 📊 配置类 -# ================================================================ - -@dataclass -class MarketMakingConfig: - bit_id: str = "f2320f57e24c45529a009e1541e25961" - """做市策略配置""" - # API配置（仅用于查询，不下单） - api_key: str = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8" - secret_key: str = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5" - memo: str = "合约交易" - contract_symbol: str = "ETHUSDT" - - # 浏览器配置 - tge_id: int = 196495 # TGE浏览器ID - tge_url: str = "http://127.0.0.1:50326" - tge_headers: Dict = None - trading_url: str = "https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT" - - # 做市参数 - spread_percent: float = 0.01 # 价差百分比（0.01% = 买一卖一之间） - order_size_usdt: float = 10.0 # 每单金额（USDT） - max_position_usdt: float = 100.0 # 最大持仓金额（USDT） - - # 订单管理 - order_refresh_interval: float = 2.0 # 订单刷新间隔（秒） - order_timeout: float = 60.0 # 订单超时时间（秒），超时后撤单重新挂 - - # 风险控制 - max_daily_loss: float = 50.0 # 每日最大亏损（USDT） - max_daily_trades: int = 1000 # 每日最大交易次数 - - # 杠杆和模式 - leverage: str = "30" # 杠杆倍数 - open_type: str = "cross" # 全仓模式 - - def __post_init__(self): - """初始化TGE headers""" - if self.tge_headers is None: - self.tge_headers = { - "Authorization": "Bearer asp_174003986c9b0799677c5b2c1adb76e402735d753bc91a91", - "Content-Type": "application/json" - } - - -# ================================================================ -# 📊 订单簿数据结构 -# ================================================================ - -@dataclass -class OrderBook: - """订单簿数据""" - bids: List[Tuple[float, float]] # [(价格, 数量), ...] 买盘，价格从高到低 - asks: List[Tuple[float, float]] # [(价格, 数量), ...] 卖盘，价格从低到高 - timestamp: float - - @property - def best_bid(self) -> Optional[float]: - """买一价""" - return self.bids[0][0] if self.bids else None - - @property - def best_ask(self) -> Optional[float]: - """卖一价""" - return self.asks[0][0] if self.asks else None - - @property - def spread(self) -> Optional[float]: - """价差""" - if self.best_bid and self.best_ask: - return self.best_ask - self.best_bid - return None - - @property - def mid_price(self) -> Optional[float]: - """中间价""" - if self.best_bid and self.best_ask: - return (self.best_bid + self.best_ask) / 2 - return None - - -@dataclass -class PendingOrder: - """pending订单信息""" - order_id: str - side: str # "buy" or "sell" - price: float - size: float - create_time: float - status: str # "pending", "filled", "cancelled" - - -# ================================================================ -# 📊 浏览器管理器 -# ================================================================ - -class BrowserManager: - """浏览器管理器：负责浏览器的启动、接管和标签页管理""" - - def __init__(self, config: MarketMakingConfig, bit_id="f2320f57e24c45529a009e1541e25961"): - self.bit_id = "f2320f57e24c45529a009e1541e25961" - self.config = config - self.tge_port: Optional[int] = None - self.page: Optional[ChromiumPage] = None - - def open_browser(self) -> bool: - """打开浏览器并获取端口""" - try: - bit_port = openBrowser(id=self.bit_id) - co = ChromiumOptions() - co.set_local_port(port=bit_port) - self.page = ChromiumPage(addr_or_opts=co) - return True - except Exception as e: - logger.error(f"打开浏览器失败: {e}") - return False - - def take_over_browser(self) -> bool: - """接管浏览器""" - if not self.tge_port: - logger.error("浏览器端口未设置") - return False - - try: - co = ChromiumOptions() - co.set_local_port(self.tge_port) - self.page = ChromiumPage(addr_or_opts=co) - self.page.set.window.max() - logger.success("成功接管浏览器") - return True - except Exception as e: - logger.error(f"接管浏览器失败: {e}") - return False - - def close_extra_tabs(self) -> bool: - """关闭多余的标签页，只保留第一个""" - if not self.page: - return False - - try: - tabs = self.page.get_tabs() - closed_count = 0 - for idx, tab in enumerate(tabs): - if idx == 0: - continue - tab.close() - closed_count += 1 - if closed_count > 0: - logger.info(f"已关闭{closed_count}个多余标签页") - return True - except Exception as e: - logger.warning(f"关闭多余标签页失败: {e}") - return False - - -# ================================================================ -# 📊 浏览器交易执行器 -# ================================================================ - -class BrowserTradingExecutor: - """浏览器交易执行器：通过浏览器自动化下单（获取高返佣）""" - - def __init__(self, page: ChromiumPage): - self.page = page - - def click_safe(self, xpath: str, sleep: float = 0.5) -> bool: - """安全点击""" - try: - ele = self.page.ele(xpath) - if not ele: - return False - ele.scroll.to_see(center=True) - time.sleep(sleep) - ele.click() - return True - except Exception as e: - logger.error(f"点击失败 {xpath}: {e}") - return False - - def 开单(self, marketPriceLongOrder: int = 0, limitPriceShortOrder: int = 0, - size: Optional[float] = None, price: Optional[float] = None) -> bool: - - size = 0.1 - """ - 开单操作（通过浏览器自动化，获取高返佣） - - Args: - marketPriceLongOrder: 市价最多或者做空，1是最多，-1是做空 - limitPriceShortOrder: 限价最多或者做空，1是最多，-1是做空 - size: 数量 - price: 价格（限价单需要） - - Returns: - 是否成功 - """ - try: - # 市价单 - if marketPriceLongOrder == -1: - # 市价做空 - if not self.click_safe('x://button[normalize-space(text()) ="市价"]'): - return False - self.page.ele('x://*[@id="size_0"]').input(vals=size, clear=True) - if not self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]'): - return False - logger.success(f"市价做空成功: {size}") - return True - - elif marketPriceLongOrder == 1: - # 市价做多 - if not self.click_safe('x://button[normalize-space(text()) ="市价"]'): - return False - self.page.ele('x://*[@id="size_0"]').input(vals=size, clear=True) - if not self.click_safe('x://span[normalize-space(text()) ="买入/做多"]'): - return False - logger.success(f"市价做多成功: {size}") - return True - - # 限价单 - if limitPriceShortOrder == -1: - # 限价做空 - if not self.click_safe('x://button[normalize-space(text()) ="限价"]'): - return False - self.page.ele('x://*[@id="price_0"]').input(vals=price, clear=True) - time.sleep(1) - self.page.ele('x://*[@id="size_0"]').input(vals=size, clear=True) - if not self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]'): - return False - logger.success(f"限价做空成功: {size} @ {price}") - return True - - elif limitPriceShortOrder == 1: - # 限价做多 - if not self.click_safe('x://button[normalize-space(text()) ="限价"]'): - return False - self.page.ele('x://*[@id="price_0"]').input(vals=price, clear=True) - time.sleep(1) - self.page.ele('x://*[@id="size_0"]').input(vals=size, clear=True) - if not self.click_safe('x://span[normalize-space(text()) ="买入/做多"]'): - return False - logger.success(f"限价做多成功: {size} @ {price}") - return True - - return False - except Exception as e: - logger.error(f"开单异常: {e}") - return False - - def 平仓(self) -> bool: - """市价平仓""" - try: - if self.click_safe('x://span[normalize-space(text()) ="市价"]'): - logger.success("平仓成功") - return True - return False - except Exception as e: - logger.error(f"平仓异常: {e}") - return False - - def place_limit_order(self, side: str, price: float, size: float) -> bool: - """ - 下限价单（通过浏览器） - - Args: - side: "buy" 或 "sell" - price: 价格 - size: 数量（张数） - - Returns: - 是否成功 - """ - try: - # size已经是张数，直接使用 - if side == "buy": - # 限价做多 - return self.开单(limitPriceShortOrder=1, size=size, price=price) - else: - # 限价做空 - return self.开单(limitPriceShortOrder=-1, size=size, price=price) - except Exception as e: - logger.error(f"限价下单异常: {e}") - return False - - -# ================================================================ -# 📊 BitMart API 封装（仅用于查询，不下单） -# ================================================================ - -class BitMartMarketMakerAPI: - """BitMart做市API封装（仅用于查询，不下单）""" - - def __init__(self, config: MarketMakingConfig): - self.config = config - self.contractAPI = APIContract( - config.api_key, - config.secret_key, - config.memo, - timeout=(5, 15) - ) - - def get_order_book(self, depth: int = 20) -> Optional[OrderBook]: - """ - 获取订单簿 - - Args: - depth: 深度数量（可能不使用） - - Returns: - OrderBook对象或None - """ - try: - # BitMart合约API获取深度数据 - # 根据错误信息，get_depth()不接受size参数 - # 尝试不同的调用方式 - try: - # 方法1：不传深度参数，使用默认值（最可能的方式） - response = self.contractAPI.get_depth( - contract_symbol=self.config.contract_symbol - )[0] - except TypeError as e1: - try: - # 方法2：尝试使用 limit 参数 - response = self.contractAPI.get_depth( - contract_symbol=self.config.contract_symbol, - limit=depth - )[0] - except TypeError as e2: - try: - # 方法3：尝试使用 depth 参数 - response = self.contractAPI.get_depth( - contract_symbol=self.config.contract_symbol, - depth=depth - )[0] - except TypeError as e3: - logger.error(f"get_depth()方法调用失败，尝试的参数方式都失败: {e1}, {e2}, {e3}") - return None - - if response.get('code') == 1000: - data = response.get('data', {}) - # BitMart返回格式可能是不同的，需要根据实际调整 - bids = [] - asks = [] - - if isinstance(data, dict): - bids_raw = data.get('bids', []) - asks_raw = data.get('asks', []) - - # 处理不同格式 - for b in bids_raw: - if isinstance(b, (list, tuple)) and len(b) >= 2: - bids.append((float(b[0]), float(b[1]))) - elif isinstance(b, dict): - bids.append((float(b.get('price', 0)), float(b.get('size', 0)))) - - for a in asks_raw: - if isinstance(a, (list, tuple)) and len(a) >= 2: - asks.append((float(a[0]), float(a[1]))) - elif isinstance(a, dict): - asks.append((float(a.get('price', 0)), float(a.get('size', 0)))) - - # 买盘按价格从高到低排序，卖盘按价格从低到高排序 - bids.sort(key=lambda x: x[0], reverse=True) - asks.sort(key=lambda x: x[0]) - - if bids and asks: - return OrderBook( - bids=bids, - asks=asks, - timestamp=time.time() - ) - return None - except Exception as e: - logger.error(f"获取订单簿异常: {e}") - # 如果获取订单簿失败，尝试使用最新价格作为备用方案 - logger.warning("尝试使用最新价格作为备用方案") - current_price = self.get_current_price() - if current_price: - # 使用当前价格和价差百分比计算买一卖一 - spread_amount = current_price * self.config.spread_percent / 100 - bids = [(current_price - spread_amount / 2, 1.0)] - asks = [(current_price + spread_amount / 2, 1.0)] - return OrderBook( - bids=bids, - asks=asks, - timestamp=time.time() - ) - return None - - def get_current_price(self) -> Optional[float]: - """获取当前最新价格""" - try: - end_time = int(time.time()) - response = self.contractAPI.get_kline( - contract_symbol=self.config.contract_symbol, - step=1, # 1分钟 - start_time=end_time - 60, - end_time=end_time - )[0] - - if response.get('code') == 1000: - data = response.get('data', []) - if data: - return float(data[-1]["close_price"]) - return None - except Exception as e: - logger.error(f"获取价格异常: {e}") - return None - - def get_available_balance(self) -> Optional[float]: - """获取合约账户可用USDT余额""" - try: - response = self.contractAPI.get_assets_detail()[0] - if response.get('code') == 1000: - data = response['data'] - if isinstance(data, dict): - return float(data.get('available_balance', 0)) - elif isinstance(data, list): - for asset in data: - if asset.get('currency') == 'USDT': - return float(asset.get('available_balance', 0)) - return None - except Exception as e: - logger.error(f"余额查询异常: {e}") - return None - - def get_position(self) -> Optional[Dict]: - """获取当前持仓""" - try: - response = self.contractAPI.get_position( - contract_symbol=self.config.contract_symbol - )[0] - - if response.get('code') == 1000: - positions = response.get('data', []) - if positions: - return positions[0] - return None - return None - except Exception as e: - logger.error(f"持仓查询异常: {e}") - return None - - def set_leverage(self) -> bool: - """设置杠杆和全仓模式""" - try: - response = self.contractAPI.post_submit_leverage( - contract_symbol=self.config.contract_symbol, - leverage=self.config.leverage, - open_type=self.config.open_type - )[0] - - if response.get('code') == 1000: - logger.success(f"全仓模式 + {self.config.leverage}x 杠杆设置成功") - return True - else: - logger.error(f"杠杆设置失败: {response}") - return False - except Exception as e: - logger.error(f"设置杠杆异常: {e}") - return False - - # ============== 新增：撤单、平仓 ============== - def get_open_orders(self) -> List[Dict]: - """获取当前所有挂单""" - try: - resp = self.contractAPI.get_open_order( - contract_symbol=self.config.contract_symbol - )[0] - if resp.get("code") == 1000: - data = resp.get("data", []) - return data if isinstance(data, list) else [] - return [] - except Exception as e: - logger.error(f"查询挂单异常: {e}") - return [] - - def cancel_order(self, order_id: str) -> bool: - """撤销单个挂单""" - try: - resp = self.contractAPI.post_cancel_order( - contract_symbol=self.config.contract_symbol, - order_id=order_id - )[0] - if resp.get("code") == 1000: - logger.success(f"撤单成功: {order_id}") - return True - logger.error(f"撤单失败: {resp}") - return False - except Exception as e: - logger.error(f"撤单异常: {e}") - return False - - def cancel_all_orders(self) -> None: - """撤销所有挂单（无精确超时信息时，直接全撤）""" - open_orders = self.get_open_orders() - for od in open_orders: - oid = str(od.get("order_id") or od.get("id") or "") - if oid: - self.cancel_order(oid) - - def close_position(self) -> bool: - """ - 使用API平仓（市价/近似市价） - 逻辑：查询当前持仓，根据方向下相反方向的平仓单 - """ - try: - position = self.get_position() - if not position: - logger.info("无持仓，无需平仓") - return True - - position_type = int(position.get("position_type", 0)) # 1=多, 2=空 - current_amount = float(position.get("current_amount", 0)) - if current_amount <= 0: - logger.info("持仓数量为0，无需平仓") - return True - - # 获取现价作为平仓价格参考 - current_price = self.get_current_price() - if not current_price: - logger.error("无法获取现价，平仓失败") - return False - - # BitMart合约订单类型：3=平多（限价），4=平空（限价） - if position_type == 1: - order_type = 3 # 平多 - elif position_type == 2: - order_type = 4 # 平空 - else: - logger.error(f"未知持仓方向: {position_type}") - return False - - # 下平仓单 - resp = self.contractAPI.post_submit_order( - contract_symbol=self.config.contract_symbol, - type=order_type, - price=str(current_price), - size=str(current_amount) - )[0] - - if resp.get("code") == 1000: - logger.success(f"API平仓成功，方向={position_type}, 数量={current_amount}, 价格={current_price}") - return True - - logger.error(f"API平仓失败: {resp}") - return False - except Exception as e: - logger.error(f"API平仓异常: {e}") - return False - - -# ================================================================ -# 📊 做市策略核心 -# ================================================================ - -class MarketMakingStrategy: - """被动做市策略（使用浏览器自动化下单，获取高返佣）""" - - def __init__(self, config: MarketMakingConfig, bit_id=None): - self.bit_id = bit_id - self.config = config - self.api = BitMartMarketMakerAPI(config) # 仅用于查询 - - # 浏览器管理 - self.browser_manager = BrowserManager(config) - self.trading_executor: Optional[BrowserTradingExecutor] = None - - # 订单管理（使用时间戳作为订单ID，因为浏览器下单无法直接获取订单ID） - self.pending_orders: Dict[str, PendingOrder] = {} - self.order_lock = Lock() - - # 统计 - self.daily_trades = 0 - self.daily_profit = 0.0 - self.total_trades = 0 - self.total_profit = 0.0 - - # 运行状态 - self.running = False - self.last_order_refresh = 0.0 - - # 初始化浏览器和杠杆 - if not self._initialize_browser(): - raise Exception("浏览器初始化失败") - self.api.set_leverage() - - def _initialize_browser(self) -> bool: - """初始化浏览器""" - try: - # 打开浏览器 - if not self.browser_manager.open_browser(): - logger.error("打开浏览器失败") - return False - - # # 接管浏览器 - # if not self.browser_manager.take_over_browser(): - # logger.error("接管浏览器失败") - # return False - - # 关闭多余标签页 - self.browser_manager.close_extra_tabs() - - # 打开交易页面 - self.browser_manager.page.get(self.config.trading_url) - time.sleep(2) # 等待页面加载 - - # 初始化交易执行器 - self.trading_executor = BrowserTradingExecutor(self.browser_manager.page) - - logger.success("浏览器初始化完成") - return True - except Exception as e: - logger.error(f"浏览器初始化异常: {e}") - return False - - def calculate_order_prices(self, order_book: OrderBook) -> Tuple[Optional[float], Optional[float]]: - """ - 计算挂单价格 - - Args: - order_book: 订单簿 - - Returns: - (buy_price, sell_price) - """ - if not order_book.mid_price or not order_book.best_bid or not order_book.best_ask: - return None, None - - mid = order_book.mid_price - spread_amount = mid * self.config.spread_percent / 100 - - # 买单价格：中间价 - 价差的一半，但不能低于买一 - buy_price = mid - spread_amount / 2 - buy_price = min(buy_price, order_book.best_bid * 0.9999) # 略低于买一，确保能成交 - - # 卖单价格：中间价 + 价差的一半，但不能高于卖一 - sell_price = mid + spread_amount / 2 - sell_price = max(sell_price, order_book.best_ask * 1.0001) # 略高于卖一，确保能成交 - - # 确保价差合理 - if sell_price <= buy_price: - # 如果价差太小，使用买一卖一价格 - buy_price = order_book.best_bid * 0.9999 - sell_price = order_book.best_ask * 1.0001 - - return buy_price, sell_price - - def should_refresh_orders(self) -> bool: - """判断是否需要刷新订单""" - now = time.time() - if now - self.last_order_refresh >= self.config.order_refresh_interval: - return True - return False - - def cancel_stale_orders(self): - """撤销超时订单（使用API撤单）""" - now = time.time() - to_cancel = [] - - with self.order_lock: - for order_id, order in self.pending_orders.items(): - if order.status == "pending": - if now - order.create_time > self.config.order_timeout: - to_cancel.append(order_id) - - if not to_cancel: - return - - logger.info(f"发现{len(to_cancel)}个超时订单，尝试API撤单") - try: - # 先通过API获取真实挂单列表并撤单 - self.api.cancel_all_orders() - # 本地状态同步 - with self.order_lock: - for order_id in to_cancel: - if order_id in self.pending_orders: - self.pending_orders[order_id].status = "cancelled" - except Exception as e: - logger.error(f"API撤单失败: {e}") - - def update_pending_orders(self): - """更新挂单状态（通过持仓变化判断订单是否成交）""" - try: - # 获取当前持仓 - current_position = self.api.get_position() - current_position_type = 0 - current_position_amount = 0.0 - - if current_position: - current_position_type = int(current_position.get('position_type', 0)) - current_position_amount = abs(float(current_position.get('current_amount', 0))) - - with self.order_lock: - # 检查挂单是否成交（通过持仓变化判断） - for order_id, order in list(self.pending_orders.items()): - if order.status == "pending": - # 检查订单是否超时 - if time.time() - order.create_time > self.config.order_timeout: - # 订单超时，标记为取消 - order.status = "cancelled" - logger.info(f"订单超时: {order_id} {order.side} @ {order.price}") - continue - except Exception as e: - logger.error(f"更新挂单状态异常: {e}") - - def _place_counter_order(self, filled_order: PendingOrder): - """ - 订单成交后，在另一侧挂单 - - Args: - filled_order: 已成交的订单 - """ - # 等待一小段时间，确保订单状态更新 - time.sleep(0.1) - - order_book = self.api.get_order_book() - if not order_book: - logger.warning("无法获取订单簿，无法挂反向单") - return - - # 计算反向订单价格 - buy_price, sell_price = self.calculate_order_prices(order_book) - - if filled_order.side == "buy": - # 买单成交，挂卖单 - if sell_price and self.trading_executor: - contract_size = self.config.order_size_usdt / sell_price / 0.01 - if contract_size < 1: - contract_size = 1 - - if self.trading_executor.place_limit_order("sell", sell_price, contract_size): - order_id = f"sell_{int(time.time() * 1000)}" - with self.order_lock: - self.pending_orders[order_id] = PendingOrder( - order_id=order_id, - side="sell", - price=sell_price, - size=self.config.order_size_usdt, - create_time=time.time(), - status="pending" - ) - logger.info(f"买单成交后挂卖单: {sell_price}, 订单ID: {order_id}") - else: - logger.warning("买单成交后挂卖单失败") - else: - # 卖单成交，挂买单平空或开多 - if buy_price and self.trading_executor: - contract_size = self.config.order_size_usdt / buy_price / 0.01 - if contract_size < 1: - contract_size = 1 - - if self.trading_executor.place_limit_order("buy", buy_price, contract_size): - order_id = f"buy_{int(time.time() * 1000)}" - with self.order_lock: - self.pending_orders[order_id] = PendingOrder( - order_id=order_id, - side="buy", - price=buy_price, - size=self.config.order_size_usdt, - create_time=time.time(), - status="pending" - ) - logger.info(f"卖单成交后挂买单: {buy_price}, 订单ID: {order_id}") - else: - logger.warning("卖单成交后挂买单失败") - - def place_market_making_orders(self): - """放置做市订单""" - # 获取订单簿 - order_book = self.api.get_order_book() - if not order_book or not order_book.mid_price: - logger.warning("无法获取订单簿") - return - - # 检查持仓 - position = self.api.get_position() - position_value = 0.0 - if position: - current_price = order_book.mid_price - position_amount = abs(float(position.get('current_amount', 0))) - # 计算持仓价值（USDT） - position_value = position_amount * current_price - - # 如果持仓超过限制，只挂反向单 - if position_value >= self.config.max_position_usdt: - logger.warning(f"持仓超过限制: {position_value} USDT，只挂反向单") - # 只挂反向单平仓 - if position: - position_type = int(position.get('position_type', 0)) - if position_type == 1: # 多仓 - # 挂卖单平多 - _, sell_price = self.calculate_order_prices(order_book) - if sell_price and self.trading_executor: - contract_size = self.config.order_size_usdt / sell_price / 0.01 - if contract_size < 1: - contract_size = 1 - self.trading_executor.place_limit_order("sell", sell_price, contract_size) - elif position_type == 2: # 空仓 - # 挂买单平空 - buy_price, _ = self.calculate_order_prices(order_book) - if buy_price and self.trading_executor: - contract_size = self.config.order_size_usdt / buy_price / 0.01 - if contract_size < 1: - contract_size = 1 - self.trading_executor.place_limit_order("buy", buy_price, contract_size) - return - - # 计算挂单价格 - buy_price, sell_price = self.calculate_order_prices(order_book) - - if not buy_price or not sell_price: - return - - # 检查当前挂单数量 - with self.order_lock: - pending_buy_count = sum(1 for o in self.pending_orders.values() - if o.side == "buy" and o.status == "pending") - pending_sell_count = sum(1 for o in self.pending_orders.values() - if o.side == "sell" and o.status == "pending") - - # 如果两侧都有挂单，不重复挂 - if pending_buy_count > 0 and pending_sell_count > 0: - return - - # 挂买单（通过浏览器） - if pending_buy_count == 0: - # 计算张数（根据合约规格调整） - # 假设页面输入框单位是张数，需要将USDT金额转换为张数 - # size_usdt / price = ETH数量，再除以合约面值得到张数 - contract_size = self.config.order_size_usdt / buy_price / 0.01 - if contract_size < 1: - contract_size = 1 - - if self.trading_executor and self.trading_executor.place_limit_order("buy", buy_price, contract_size): - # 使用时间戳作为订单ID - order_id = f"buy_{int(time.time() * 1000)}" - with self.order_lock: - self.pending_orders[order_id] = PendingOrder( - order_id=order_id, - side="buy", - price=buy_price, - size=self.config.order_size_usdt, - create_time=time.time(), - status="pending" - ) - logger.info(f"挂买单成功: {buy_price}, 订单ID: {order_id}") - else: - logger.warning("挂买单失败") - - # 挂卖单（通过浏览器） - if pending_sell_count == 0: - # 计算张数 - contract_size = self.config.order_size_usdt / sell_price / 0.01 - if contract_size < 1: - contract_size = 1 - - if self.trading_executor and self.trading_executor.place_limit_order("sell", sell_price, contract_size): - # 使用时间戳作为订单ID - order_id = f"sell_{int(time.time() * 1000)}" - with self.order_lock: - self.pending_orders[order_id] = PendingOrder( - order_id=order_id, - side="sell", - price=sell_price, - size=self.config.order_size_usdt, - create_time=time.time(), - status="pending" - ) - logger.info(f"挂卖单成功: {sell_price}, 订单ID: {order_id}") - else: - logger.warning("挂卖单失败") - - self.last_order_refresh = time.time() - - def check_risk_limits(self) -> bool: - """检查风险限制""" - # 检查每日交易次数 - if self.daily_trades >= self.config.max_daily_trades: - logger.warning(f"达到每日最大交易次数: {self.daily_trades}") - return False - - # 检查每日亏损 - if self.daily_profit <= -self.config.max_daily_loss: - logger.error(f"达到每日最大亏损: {self.daily_profit}") - # send_dingtalk_message(f"做市策略达到每日最大亏损: {self.daily_profit} USDT", error=True) - return False - - return True - - def run(self): - """主运行循环""" - self.running = True - logger.info("做市策略启动") - - while self.running: - try: - # 检查风险限制 - if not self.check_risk_limits(): - logger.error("风险限制触发，停止策略") - break - - # 撤销超时订单 - self.cancel_stale_orders() - - # 更新挂单状态 - self.update_pending_orders() - - # 刷新订单 - if self.should_refresh_orders(): - self.place_market_making_orders() - - # 短暂休眠 - time.sleep(0.5) - - except KeyboardInterrupt: - logger.info("收到中断信号，停止策略") - break - except Exception as e: - logger.error(f"策略运行异常: {e}") - time.sleep(1) - - # 清理：刷新页面，手动撤销挂单 - logger.info("清理挂单...使用API撤单") - try: - self.api.cancel_all_orders() - with self.order_lock: - for order_id in list(self.pending_orders.keys()): - if self.pending_orders[order_id].status == "pending": - self.pending_orders[order_id].status = "cancelled" - except Exception as e: - logger.error(f"清理挂单失败: {e}") - - logger.info("做市策略已停止") - - def stop(self): - """停止策略""" - self.running = False - - -# ================================================================ -# 🚀 主程序 -# ================================================================ - -if __name__ == '__main__': - config = MarketMakingConfig( - contract_symbol="ETHUSDT", - bit_id="f2320f57e24c45529a009e1541e25961", # TGE浏览器ID - trading_url="https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT", - spread_percent=0.01, # 0.01%价差 - order_size_usdt=0.1, # 每单10 USDT - max_position_usdt=3.0, # 最大持仓100 USDT - order_refresh_interval=2.0, # 2秒刷新一次 - order_timeout=60.0, # 60秒超时 - max_daily_loss=50.0, # 每日最大亏损50 USDT - max_daily_trades=1000, # 每日最大1000笔 - leverage="35", - open_type="cross" - ) - - strategy = MarketMakingStrategy(config) - - try: - strategy.run() - except Exception as e: - logger.error(f"程序异常: {e}") - # send_dingtalk_message(f"做市策略异常: {e}", error=True) - -# 9359,53 -# 14.35 diff --git a/bitmart/优化拿仓版本.py b/bitmart/优化拿仓版本.py deleted file mode 100644 index 489fcbb..0000000 --- a/bitmart/优化拿仓版本.py +++ /dev/null @@ -1,458 +0,0 @@ -""" -BitMart 被动做市/高频刷单策略 (修复版 V2) -修复内容： -1. 修正 get_order_book 中解析深度数据的方式，由字典键名访问改为列表索引访问 (['price'] -> [0]) -""" - -import time -import requests -from typing import Optional, Dict, List, Tuple -from dataclasses import dataclass -from loguru import logger -from threading import Lock - -from DrissionPage import ChromiumPage, ChromiumOptions -from bitmart.api_contract import APIContract - - -# ================================================================ -# 📊 配置类 -# ================================================================ - -@dataclass -class MarketMakingConfig: - """做市策略配置""" - # API配置（仅用于查询，不下单） - api_key: str = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8" - secret_key: str = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5" - memo: str = "合约交易" - contract_symbol: str = "ETHUSDT" - - # 浏览器配置 - tge_id: int = 196495 # TGE浏览器ID - tge_url: str = "http://127.0.0.1:50326" - tge_headers: Dict = None - trading_url: str = "https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT" - - # 做市基础参数 - spread_percent: float = 0.04 # 基础价差 (0.04% 约为 $1左右 on ETH) - order_size_usdt: float = 10.0 # 每单金额（USDT） - max_position_usdt: float = 100.0 # 最大持仓金额（USDT） - - # 🚀 高级策略参数 - # 库存倾斜：每持有100U，价格偏移多少。正数表示持有多单时价格下调（利于卖出，不利于买入） - inventory_skew_factor: float = 0.0005 - # 价格容忍度：只有当(目标价 - 当前挂单价) / 目标价 > 0.05% 时才改单，避免频繁操作 - price_tolerance: float = 0.0005 - - # 风险控制 - max_daily_loss: float = 50.0 - leverage: str = "30" - open_type: str = "cross" - - def __post_init__(self): - """初始化TGE headers""" - if self.tge_headers is None: - self.tge_headers = { - "Authorization": "Bearer asp_174003986c9b0799677c5b2c1adb76e402735d753bc91a91", - "Content-Type": "application/json" - } - - -# ================================================================ -# 📊 订单簿数据结构 -# ================================================================ - -@dataclass -class OrderBook: - """订单簿数据""" - bids: List[Tuple[float, float]] # [(价格, 数量), ...] - asks: List[Tuple[float, float]] # [(价格, 数量), ...] - timestamp: float - - @property - def mid_price(self) -> Optional[float]: - """中间价""" - if self.bids and self.asks: - return (self.bids[0][0] + self.asks[0][0]) / 2 - return None - - -# ================================================================ -# 📊 浏览器管理器 -# ================================================================ - -class BrowserManager: - """浏览器管理器：负责浏览器的启动、接管和标签页管理""" - - def __init__(self, config: MarketMakingConfig): - self.config = config - self.tge_port: Optional[int] = None - self.page: Optional[ChromiumPage] = None - - def open_browser(self) -> bool: - """打开浏览器并获取端口""" - try: - response = requests.post( - f"{self.config.tge_url}/api/browser/start", - json={"envId": self.config.tge_id}, - headers=self.config.tge_headers, - timeout=10 - ) - data = response.json() - if "data" in data and "port" in data["data"]: - self.tge_port = data["data"]["port"] - logger.success(f"成功打开浏览器，端口：{self.tge_port}") - return True - else: - logger.error(f"打开浏览器响应异常: {data}") - return False - except Exception as e: - logger.error(f"打开浏览器失败: {e}") - return False - - def take_over_browser(self) -> bool: - """接管浏览器""" - if not self.tge_port: - logger.error("浏览器端口未设置") - return False - - try: - co = ChromiumOptions() - co.set_local_port(self.tge_port) - self.page = ChromiumPage(addr_or_opts=co) - logger.success("成功接管浏览器") - return True - except Exception as e: - logger.error(f"接管浏览器失败: {e}") - return False - - def close_extra_tabs(self) -> bool: - """关闭多余的标签页，只保留第一个""" - if not self.page: - return False - try: - tabs = self.page.get_tabs() - for idx, tab in enumerate(tabs): - if idx == 0: continue - tab.close() - return True - except Exception as e: - logger.warning(f"关闭多余标签页失败: {e}") - return False - - -# ================================================================ -# 📊 浏览器交易执行器 -# ================================================================ - -class BrowserTradingExecutor: - """浏览器交易执行器：通过浏览器自动化下单（获取高返佣）""" - - def __init__(self, page: ChromiumPage): - self.page = page - - def click_safe(self, xpath: str, sleep: float = 0.5) -> bool: - """安全点击""" - try: - ele = self.page.ele(xpath) - if not ele: - return False - ele.scroll.to_see(center=True) - time.sleep(sleep) - ele.click() - return True - except Exception as e: - logger.error(f"点击失败 {xpath}: {e}") - return False - - def 开单(self, marketPriceLongOrder: int = 0, limitPriceShortOrder: int = 0, - size: Optional[float] = None, price: Optional[float] = None) -> bool: - """开单操作""" - size = 0.1 - - try: - # 市价单 (代码略) - if marketPriceLongOrder == -1: pass - elif marketPriceLongOrder == 1: pass - - # 限价单 - if limitPriceShortOrder == -1: - # 限价做空 - if not self.click_safe('x://button[normalize-space(text()) ="限价"]'): return False - self.page.ele('x://*[ @id="price_0"]').input(vals=price, clear=True) - time.sleep(0.2) - self.page.ele('x://*[ @id="size_0"]').input(vals=size, clear=True) - if not self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]'): return False - logger.success(f"浏览器下单: 限价做空 {size} @ {price}") - return True - - elif limitPriceShortOrder == 1: - # 限价做多 - if not self.click_safe('x://button[normalize-space(text()) ="限价"]'): return False - self.page.ele('x://*[ @id="price_0"]').input(vals=price, clear=True) - time.sleep(0.2) - self.page.ele('x://*[ @id="size_0"]').input(vals=size, clear=True) - if not self.click_safe('x://span[normalize-space(text()) ="买入/做多"]'): return False - logger.success(f"浏览器下单: 限价做多 {size} @ {price}") - return True - - return False - except Exception as e: - logger.error(f"开单异常: {e}") - return False - - def place_limit_order(self, side: str, price: float, size: float) -> bool: - """统一接口""" - if side == "buy": - return self.开单(limitPriceShortOrder=1, size=size, price=price) - else: - return self.开单(limitPriceShortOrder=-1, size=size, price=price) - - -# ================================================================ -# 📊 BitMart API 封装 (修复 get_order_book) -# ================================================================ - -class BitMartMarketMakerAPI: - """BitMart做市API封装（仅用于查询，不下单）""" - - def __init__(self, config: MarketMakingConfig): - self.config = config - self.contractAPI = APIContract( - config.api_key, - config.secret_key, - config.memo, - timeout=(5, 15) - ) - - def get_order_book(self) -> Optional[OrderBook]: - try: - # 移除不支持的 limit 参数 - response = self.contractAPI.get_depth(contract_symbol=self.config.contract_symbol)[0] - - if response.get('code') == 1000: - data = response.get('data', {}) - bids = [] - asks = [] - # 解析数据 - if isinstance(data, dict): - bids_raw = data.get('bids', []) - asks_raw = data.get('asks', []) - - # 修复：b 是列表 [price, size]，不是字典 - for b in bids_raw[:10]: - # b[0] 是价格, b[1] 是数量 - bids.append((float(b[0]), float(b[1]))) - - for a in asks_raw[:10]: - # a[0] 是价格, a[1] 是数量 - asks.append((float(a[0]), float(a[1]))) - - if bids and asks: - return OrderBook(bids=bids, asks=asks, timestamp=time.time()) - else: - logger.warning(f"获取深度失败: {response}") - return None - except Exception as e: - logger.error(f"获取订单簿异常: {e}") - return None - - def get_position_net(self) -> float: - """获取净持仓 (多为正，空为负)""" - try: - response = self.contractAPI.get_position(contract_symbol=self.config.contract_symbol)[0] - if response.get('code') == 1000: - data = response.get('data', []) - if data: - pos = data[0] - current_amount = float(pos.get('current_amount', 0)) - position_type = int(pos.get('position_type', 0)) # 1多 2空 - if position_type == 1: return current_amount - if position_type == 2: return -current_amount - return 0.0 - except Exception as e: - logger.error(f"持仓查询异常: {e}") - return 0.0 - - def get_open_orders(self) -> List[Dict]: - """获取当前挂单""" - try: - resp = self.contractAPI.get_open_order(contract_symbol=self.config.contract_symbol)[0] - if resp.get("code") == 1000: - return resp.get("data", []) - return [] - except Exception as e: - logger.error(f"查询挂单异常: {e}") - return [] - - def cancel_order(self, order_id: str) -> bool: - """API撤单""" - try: - resp = self.contractAPI.post_cancel_order(contract_symbol=self.config.contract_symbol, order_id=order_id)[0] - return resp.get("code") == 1000 - except Exception as e: - logger.error(f"API撤单异常: {e}") - return False - - def set_leverage(self): - try: - self.contractAPI.post_submit_leverage(contract_symbol=self.config.contract_symbol, leverage=self.config.leverage, open_type=self.config.open_type) - except: - pass - - -# ================================================================ -# 🧠 策略核心 -# ================================================================ - -class MarketMakingStrategy: - """优化版被动做市策略""" - - def __init__(self, config: MarketMakingConfig): - self.config = config - self.api = BitMartMarketMakerAPI(config) - self.browser_manager = BrowserManager(config) - self.trading_executor: Optional[BrowserTradingExecutor] = None - self.running = False - - # 初始化流程 - if not self._initialize_browser(): - raise Exception("浏览器初始化失败") - self.api.set_leverage() - - def _initialize_browser(self) -> bool: - try: - if not self.browser_manager.open_browser(): return False - if not self.browser_manager.take_over_browser(): return False - self.browser_manager.close_extra_tabs() - - # 访问交易页 - logger.info(f"正在访问交易页: {self.config.trading_url}") - self.browser_manager.page.get(self.config.trading_url) - time.sleep(3) - - self.trading_executor = BrowserTradingExecutor(self.browser_manager.page) - logger.success("浏览器环境就绪") - return True - except Exception as e: - logger.error(f"浏览器初始化异常: {e}") - return False - - def calculate_target_prices(self, mid_price: float, net_position: float) -> Tuple[float, float]: - """核心算法：计算考虑了库存倾斜的目标买卖价""" - # 1. 基础价差的一半 - half_spread = mid_price * (self.config.spread_percent / 100) / 2 - - # 2. 库存倾斜调整 - skew_adjust = net_position * self.config.inventory_skew_factor * mid_price - - quote_mid = mid_price - skew_adjust - - target_bid = quote_mid - half_spread - target_ask = quote_mid + half_spread - - # 3. 价格修正 (防止穿仓) - if target_ask <= target_bid: - target_ask = target_bid + mid_price * 0.0001 - - return round(target_bid, 2), round(target_ask, 2) - - def reconcile_orders(self, target_bid: float, target_ask: float): - """调节逻辑：对比API实际挂单 vs 目标价格""" - open_orders = self.api.get_open_orders() - - current_bids = [] - current_asks = [] - - for o in open_orders: - side = o.get('side') - # 兼容API返回 - side_str = str(side).lower() - if side_str == '1' or 'buy' in side_str: - current_bids.append(o) - elif side_str == '2' or 'sell' in side_str: - current_asks.append(o) - - # --- 调节买单 --- - valid_bid_exists = False - for order in current_bids: - price = float(order.get('price', 0)) - diff_pct = abs(price - target_bid) / target_bid - - if diff_pct < self.config.price_tolerance: - valid_bid_exists = True - else: - logger.info(f"♻️ 买单价格偏离 (现{price} vs 标{target_bid})，撤单") - self.api.cancel_order(order.get('order_id') or order.get('id')) - - if not valid_bid_exists: - # 计算张数 - size_contract = self.config.order_size_usdt / target_bid / 0.01 - size_contract = max(1, int(size_contract)) - logger.info(f"➕ 补买单: {target_bid} (数量:{size_contract})") - self.trading_executor.place_limit_order("buy", target_bid, size_contract) - - # --- 调节卖单 --- - valid_ask_exists = False - for order in current_asks: - price = float(order.get('price', 0)) - diff_pct = abs(price - target_ask) / target_ask - - if diff_pct < self.config.price_tolerance: - valid_ask_exists = True - else: - logger.info(f"♻️ 卖单价格偏离 (现{price} vs 标{target_ask})，撤单") - self.api.cancel_order(order.get('order_id') or order.get('id')) - - if not valid_ask_exists: - size_contract = self.config.order_size_usdt / target_ask / 0.01 - size_contract = max(1, int(size_contract)) - logger.info(f"➕ 补卖单: {target_ask} (数量:{size_contract})") - self.trading_executor.place_limit_order("sell", target_ask, size_contract) - - def run(self): - self.running = True - logger.info("🚀 策略已启动") - - while self.running: - try: - # 1. 获取市场数据 - ob = self.api.get_order_book() - if not ob: - time.sleep(1) - continue - mid_price = ob.mid_price - - # 2. 获取持仓 - net_position = self.api.get_position_net() - - # 3. 计算目标价 - t_bid, t_ask = self.calculate_target_prices(mid_price, net_position) - logger.info(f"Mid:{mid_price:.2f} | Pos:{net_position} | Target Bid:{t_bid} Ask:{t_ask}") - - # 4. 调节挂单 - self.reconcile_orders(t_bid, t_ask) - - # 5. 循环间隔 - time.sleep(3) - - except KeyboardInterrupt: - logger.warning("停止策略") - break - except Exception as e: - logger.error(f"Loop Exception: {e}") - time.sleep(2) - -if __name__ == '__main__': - config = MarketMakingConfig( - contract_symbol="ETHUSDT", - spread_percent=0.04, - order_size_usdt=0.1, - max_position_usdt=50.0, - inventory_skew_factor=0.0005, - price_tolerance=0.0005 - ) - - strategy = MarketMakingStrategy(config) - strategy.run() diff --git a/bitmart/回测.py b/bitmart/回测.py deleted file mode 100644 index f709dce..0000000 --- a/bitmart/回测.py +++ /dev/null @@ -1,83 +0,0 @@ -import time -import csv - -import loguru -from bitmart.api_contract import APIContract - -# ------------------ 配置 ------------------ -START_YEAR = 2025 -CONTRACT_SYMBOL = "ETHUSDT" -STEP = 3 # K 线周期，单位分钟 -CSV_FILE = f"kline_{STEP}.csv" - -memo = "合约交易" -api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8" -secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5" - -contractAPI = APIContract(api_key, secret_key, memo, timeout=(5, 15)) - -# ------------------ 时间戳 ------------------ -start_of_year = int(time.mktime((START_YEAR, 1, 1, 0, 0, 0, 0, 0, 0))) -current_time = int(time.time()) - -# ------------------ 抓取数据 ------------------ -all_data = [] -existing_ids = set() -start_time = start_of_year - -# 每次请求时间长度 = step * 500 条 K 线 -request_interval_ms = STEP * 60 * 500 - -while start_time < current_time: - end_time = min(start_time + request_interval_ms, current_time) - loguru.logger.info(f"抓取时间段: {start_time} ~ {end_time}") - - try: - response = contractAPI.get_kline( - contract_symbol=CONTRACT_SYMBOL, - step=STEP, - start_time=start_time, - end_time=end_time - )[0]["data"] - - formatted = [] - for k in response: - print(k) - k_id = int(k["timestamp"]) - if k_id in existing_ids: - continue - existing_ids.add(k_id) - formatted.append({ - 'id': int(k["timestamp"]), - 'open': float(k["open_price"]), - 'high': float(k["high_price"]), - 'low': float(k["low_price"]), - 'close': float(k["close_price"]), - 'volume': float(k["volume"]) - }) - - formatted.sort(key=lambda x: x['id']) - all_data.extend(formatted) - - if len(response) < 500: - start_time = end_time - else: - start_time = formatted[-1]['id'] + 1 - - except Exception as e: - print(f"请求出错: {e}，等待 60 秒后重试") - time.sleep(60) - - time.sleep(0.2) # 控制速率，保证 <= 每 2 秒 12 次 - -# ------------------ 保存 CSV ------------------ -csv_columns = ['id', 'open', 'high', 'low', 'close', 'volume'] -try: - with open(CSV_FILE, 'w', newline='') as csvfile: - writer = csv.DictWriter(csvfile, fieldnames=csv_columns) - writer.writeheader() - for data in all_data: - writer.writerow(data) - print(f"数据已保存到 {CSV_FILE}，共 {len(all_data)} 条") -except IOError: - print("I/O error") diff --git a/bitmart/回测图表.png b/bitmart/回测图表.png deleted file mode 100644 index d3df2fd82f48d99c6dfc7161b2b44d82e6de3a91..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 147692 zcmeFZ2UwG7|0as#I4UT}NKp_F8AZBCCj?YfMrleFX$k@&1ccCA9F?LpmEM9#?l`YslRsL_mfw5G*ph$bI{Y# 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a/bitmart/回测图表_交互式.html b/bitmart/回测图表_交互式.html deleted file mode 100644 index b67088e..0000000 --- a/bitmart/回测图表_交互式.html +++ /dev/null @@ -1,3888 +0,0 @@ - - - -

-
- - \ No newline at end of file diff --git a/bitmart/均线回归.py b/bitmart/均线回归.py deleted file mode 100644 index 9616cce..0000000 --- a/bitmart/均线回归.py +++ /dev/null @@ -1,866 +0,0 @@ -import os -import time -import uuid -import datetime -from dataclasses import dataclass - -from tqdm import tqdm -from loguru import logger - -from bitmart.api_contract import APIContract -from bitmart.lib.cloud_exceptions import APIException - -from 交易.tools import send_dingtalk_message - - -@dataclass -class StrategyConfig: - # ============================= - # 1m | ETH 永续 | 控止损≤5/日 - # ============================= - - # ===== 合约 ===== - contract_symbol: str = "ETHUSDT" - open_type: str = "cross" - leverage: str = "30" - - # ===== K线与指标 ===== - step_min: int = 1 - lookback_min: int = 240 - ema_len: int = 36 - atr_len: int = 14 - - # ========================================================= - # ✅ 自动阈值：ATR/Price 分位数基准（更稳，不被短时噪声带跑） - # ========================================================= - vol_baseline_window: int = 60 - vol_baseline_quantile: float = 0.65 - vol_scale_min: float = 0.80 - vol_scale_max: float = 1.60 - - # ✅ baseline 每 60 秒刷新一次（体感更明显、也省CPU） - base_ratio_refresh_sec: int = 60 - - # ========================================================= - # ✅ 动态 floor（方案一） - # floor = clamp(min, base_k * base_ratio, max) - # 目的：跟着典型波动变，过滤小噪声；tp/sl 也随环境自适应 - # ========================================================= - # entry_dev_floor 动态 - entry_dev_floor_min: float = 0.0012 # 0.12% - entry_dev_floor_max: float = 0.0030 # 0.30%（可按你偏好调） - entry_dev_floor_base_k: float = 1.10 # entry_floor = 1.10 * base_ratio - - # tp_floor 动态 - tp_floor_min: float = 0.0006 # 0.06% - tp_floor_max: float = 0.0020 # 0.20% - tp_floor_base_k: float = 0.55 # tp_floor = 0.55 * base_ratio（止盈别太大，1m回归更实际） - - # sl_floor 动态 - sl_floor_min: float = 0.0018 # 0.18% - sl_floor_max: float = 0.0060 # 0.60% - sl_floor_base_k: float = 1.35 # sl_floor = 1.35 * base_ratio（ETH 1m 插针多，止损下限可更稳） - - # ========================================================= - # ✅ 动态阈值倍率（仍然保留你原来思路） - # ========================================================= - entry_k: float = 1.45 - tp_k: float = 0.65 - sl_k: float = 1.05 - - # ===== 时间/冷却 ===== - max_hold_sec: int = 75 - cooldown_sec_after_exit: int = 20 - - # ===== 下单/仓位 ===== - risk_percent: float = 0.004 - min_size: int = 1 - max_size: int = 5000 - - # ===== 日内风控 ===== - daily_loss_limit: float = 0.02 - daily_profit_cap: float = 0.01 - - # ===== 危险模式过滤 ===== - atr_ratio_kill: float = 0.0038 - big_body_kill: float = 0.010 - - # ===== 轮询节奏 ===== - klines_refresh_sec: int = 10 - tick_refresh_sec: int = 1 - status_notify_sec: int = 60 - - # ========================================================= - # ✅ 止损后同向入场加门槛（但不禁止同向重入） - # ========================================================= - reentry_penalty_mult: float = 1.55 - reentry_penalty_max_sec: int = 180 - reset_band_k: float = 0.45 - reset_band_floor: float = 0.0006 - - # ========================================================= - # ✅ 止损后同方向 SL 放宽幅度与"止损时 vol_scale"联动 - # ========================================================= - post_sl_sl_max_sec: int = 90 - post_sl_mult_min: float = 1.02 - post_sl_mult_max: float = 1.16 - post_sl_vol_alpha: float = 0.20 - - -class BitmartFuturesMeanReversionBot: - def __init__(self, cfg: StrategyConfig): - self.cfg = cfg - - self.api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8" - self.secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5" - self.memo = "合约交易" - - if not self.api_key or not self.secret_key: - raise RuntimeError("请先设置环境变量 BITMART_API_KEY / BITMART_SECRET_KEY / BITMART_MEMO(可选)") - - self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15)) - - # 持仓状态: -1 空, 0 无, 1 多 - self.pos = 0 - self.entry_price = None - self.entry_ts = None - self.last_exit_ts = 0 - - # 日内权益基准 - self.day_start_equity = None - self.trading_enabled = True - self.day_tag = datetime.date.today() - - # 缓存 - self._klines_cache = None - self._klines_cache_ts = 0 - self._last_status_notify_ts = 0 - - # ✅ base_ratio 缓存 - self._base_ratio_cached = 0.0015 # 初始化默认值 0.15% - self._base_ratio_ts = 0.0 - - # ✅ 止损后"同向入场加门槛"状态 - self.last_sl_dir = 0 # 1=多止损，-1=空止损，0=无 - self.last_sl_ts = 0.0 - - # ✅ 止损后"同方向 SL 联动放宽"状态 - self.post_sl_dir = 0 - self.post_sl_ts = 0.0 - self.post_sl_vol_scale = 1.0 # 记录止损时的 vol_scale - - self.pbar = tqdm(total=60, desc="运行中(秒)", ncols=90) - - logger.info(f"初始化完成，基准波动率默认值: {self._base_ratio_cached * 100:.4f}%") - - # ----------------- 通用工具 ----------------- - def ding(self, msg, error=False): - prefix = "❌bitmart：" if error else "🔔bitmart：" - if error: - for _ in range(3): - send_dingtalk_message(f"{prefix}{msg}") - else: - send_dingtalk_message(f"{prefix}{msg}") - - def set_leverage(self) -> bool: - try: - resp = self.contractAPI.post_submit_leverage( - contract_symbol=self.cfg.contract_symbol, - leverage=self.cfg.leverage, - open_type=self.cfg.open_type - )[0] - if resp.get("code") == 1000: - logger.success(f"设置杠杆成功：{self.cfg.open_type} + {self.cfg.leverage}x") - return True - logger.error(f"设置杠杆失败: {resp}") - self.ding(f"设置杠杆失败: {resp}", error=True) - return False - except Exception as e: - logger.error(f"设置杠杆异常: {e}") - self.ding(f"设置杠杆异常: {e}", error=True) - return False - - # ----------------- 行情/指标 ----------------- - def get_klines_cached(self): - now = time.time() - if self._klines_cache is not None and (now - self._klines_cache_ts) < self.cfg.klines_refresh_sec: - return self._klines_cache - - kl = self.get_klines() - if kl: - self._klines_cache = kl - self._klines_cache_ts = now - return self._klines_cache - - def get_klines(self): - try: - end_time = int(time.time()) - start_time = end_time - 60 * self.cfg.lookback_min - - resp = self.contractAPI.get_kline( - contract_symbol=self.cfg.contract_symbol, - step=self.cfg.step_min, - start_time=start_time, - end_time=end_time - )[0] - - if resp.get("code") != 1000: - logger.error(f"获取K线失败: {resp}") - return None - - data = resp.get("data", []) - formatted = [] - for k in data: - formatted.append({ - "id": int(k["timestamp"]), - "open": float(k["open_price"]), - "high": float(k["high_price"]), - "low": float(k["low_price"]), - "close": float(k["close_price"]), - }) - formatted.sort(key=lambda x: x["id"]) - return formatted - except Exception as e: - logger.error(f"获取K线异常: {e}") - self.ding(f"获取K线异常: {e}", error=True) - return None - - def get_last_price(self, fallback_close: float) -> float: - try: - if hasattr(self.contractAPI, "get_contract_details"): - r = self.contractAPI.get_contract_details(contract_symbol=self.cfg.contract_symbol)[0] - d = r.get("data") if isinstance(r, dict) else None - if isinstance(d, dict): - for key in ("last_price", "mark_price", "index_price"): - if key in d and d[key] is not None: - return float(d[key]) - - if hasattr(self.contractAPI, "get_ticker"): - r = self.contractAPI.get_ticker(contract_symbol=self.cfg.contract_symbol)[0] - d = r.get("data") if isinstance(r, dict) else None - if isinstance(d, dict): - for key in ("last_price", "price", "last", "close"): - if key in d and d[key] is not None: - return float(d[key]) - except Exception: - pass - - return float(fallback_close) - - @staticmethod - def ema(values, n: int) -> float: - k = 2 / (n + 1) - e = values[0] - for v in values[1:]: - e = v * k + e * (1 - k) - return e - - @staticmethod - def atr(klines, n: int) -> float: - if len(klines) < n + 1: - return 0.0 - trs = [] - for i in range(-n, 0): - cur = klines[i] - prev = klines[i - 1] - tr = max( - cur["high"] - cur["low"], - abs(cur["high"] - prev["close"]), - abs(cur["low"] - prev["close"]), - ) - trs.append(tr) - return sum(trs) / len(trs) - - def is_danger_market(self, klines, price: float) -> bool: - last = klines[-1] - body = abs(last["close"] - last["open"]) / last["open"] if last["open"] else 0.0 - if body >= self.cfg.big_body_kill: - return True - - a = self.atr(klines, self.cfg.atr_len) - atr_ratio = (a / price) if price > 0 else 0.0 - if atr_ratio >= self.cfg.atr_ratio_kill: - return True - - return False - - def atr_ratio_baseline(self, klines) -> float: - """简化版ATR基准计算""" - window = min(self.cfg.vol_baseline_window, len(klines) - self.cfg.atr_len - 1) - if window <= 10: # 数据太少 - logger.warning(f"数据不足计算基准: {len(klines)}根K线") - return 0.0 - - ratios = [] - - # 简化计算：每隔3根K线计算一个ATR比率（减少计算量） - step = 3 - for i in range(-window, 0, step): - if len(klines) + i < self.cfg.atr_len + 1: - continue - - # 计算当前位置的ATR - start_idx = len(klines) + i - self.cfg.atr_len - end_idx = len(klines) + i - - if start_idx < 0 or end_idx <= start_idx: - continue - - sub_klines = klines[start_idx:end_idx] - - # 确保有足够数据计算ATR - if len(sub_klines) >= self.cfg.atr_len + 1: - a = self.atr(sub_klines, self.cfg.atr_len) - price = klines[end_idx - 1]["close"] - - if a > 0 and price > 0: - ratio = a / price - if 0.0001 < ratio < 0.01: # 过滤异常值 - ratios.append(ratio) - - if len(ratios) < 5: # 样本太少 - # 尝试直接使用整个数据计算一个ATR比率 - a = self.atr(klines[-60:], self.cfg.atr_len) # 使用最近60根K线 - price = klines[-1]["close"] - if a > 0 and price > 0: - baseline = a / price - logger.debug(f"使用全量数据计算基准: {baseline * 100:.4f}%") - return baseline - else: - return 0.0 - - # 计算分位数 - ratios.sort() - idx = min(len(ratios) - 1, - max(0, int(self.cfg.vol_baseline_quantile * (len(ratios) - 1)))) - baseline = ratios[idx] - - logger.debug(f"基准计算: 样本数={len(ratios)}, 基准={baseline * 100:.4f}%, " - f"范围=[{ratios[0] * 100:.4f}%, {ratios[-1] * 100:.4f}%]") - - return baseline - - def get_base_ratio_cached(self, klines) -> float: - """获取缓存的基准波动率，定期刷新""" - now = time.time() - refresh_sec = self.cfg.base_ratio_refresh_sec - - if (self._base_ratio_cached is None or - (now - self._base_ratio_ts) >= refresh_sec): - - # 使用简单版本的基准计算 - baseline = self.atr_ratio_baseline(klines) - - if baseline > 0.0001: # 大于0.01%才认为是有效值 - self._base_ratio_cached = baseline - self._base_ratio_ts = now - logger.info(f"基准波动率更新: {baseline * 100:.4f}%") - else: - # 使用基于价格的动态默认值 - current_price = klines[-1]["close"] if klines else 3000 - # ETH价格越高，基准波动率越小（百分比） - if current_price > 4000: - default_baseline = 0.0010 # 0.10% - elif current_price > 3500: - default_baseline = 0.0012 # 0.12% - elif current_price > 3000: - default_baseline = 0.0015 # 0.15% - elif current_price > 2500: - default_baseline = 0.0018 # 0.18% - else: - default_baseline = 0.0020 # 0.20% - - self._base_ratio_cached = default_baseline - self._base_ratio_ts = now - logger.warning(f"使用价格动态默认基准: {default_baseline * 100:.4f}% " - f"(价格=${current_price:.0f})") - - return self._base_ratio_cached - - @staticmethod - def _clamp(x: float, lo: float, hi: float) -> float: - """限制数值在指定范围内""" - return max(lo, min(hi, x)) - - def dynamic_thresholds(self, atr_ratio: float, base_ratio: float): - """ - ✅ entry/tp/sl 全部动态（修复版）： - - vol_scale：atr_ratio/base_ratio 限幅 - - floor：方案一 (floor = clamp(min, k*base_ratio, max)) - - 最终阈值：max(floor, k * vol_scale * atr_ratio) - """ - # 1) 检查输入有效性 - if atr_ratio <= 0: - logger.warning(f"ATR比率异常: {atr_ratio}") - atr_ratio = 0.001 # 默认值 0.1% - - # 2) 如果base_ratio太小或无效，使用调整后的atr_ratio - if base_ratio < 0.0005: # 小于0.05%视为无效 - base_ratio = max(0.001, atr_ratio * 1.2) # 比当前ATR比率稍大 - logger.debug(f"基准太小，使用调整后的atr_ratio: {base_ratio * 100:.4f}%") - - # 3) vol_scale计算 - if base_ratio > 0: - raw_scale = atr_ratio / base_ratio - vol_scale = self._clamp(raw_scale, self.cfg.vol_scale_min, self.cfg.vol_scale_max) - logger.debug( - f"vol_scale: {raw_scale:.2f} → {vol_scale:.2f} (atr={atr_ratio * 100:.3f}%, base={base_ratio * 100:.3f}%)") - else: - vol_scale = 1.0 - logger.warning(f"基准无效，使用默认vol_scale=1.0") - - # 4) 动态floor计算 - # Entry floor - entry_floor_raw = self.cfg.entry_dev_floor_base_k * base_ratio - entry_floor = self._clamp( - entry_floor_raw, - self.cfg.entry_dev_floor_min, - self.cfg.entry_dev_floor_max, - ) - - # TP floor - tp_floor_raw = self.cfg.tp_floor_base_k * base_ratio - tp_floor = self._clamp( - tp_floor_raw, - self.cfg.tp_floor_min, - self.cfg.tp_floor_max, - ) - - # SL floor - sl_floor_raw = self.cfg.sl_floor_base_k * base_ratio - sl_floor = self._clamp( - sl_floor_raw, - self.cfg.sl_floor_min, - self.cfg.sl_floor_max, - ) - - # 5) 最终阈值计算 - entry_dev_atr_part = self.cfg.entry_k * vol_scale * atr_ratio - entry_dev = max(entry_floor, entry_dev_atr_part) - - tp_atr_part = self.cfg.tp_k * vol_scale * atr_ratio - tp = max(tp_floor, tp_atr_part) - - sl_atr_part = self.cfg.sl_k * vol_scale * atr_ratio - sl = max(sl_floor, sl_atr_part) - - # 6) 确保entry_dev不会太小 - entry_dev = max(entry_dev, self.cfg.entry_dev_floor_min) - - # 7) 输出详细信息 - logger.info( - f"动态阈值: atr={atr_ratio * 100:.4f}%, base={base_ratio * 100:.4f}%, " - f"vol_scale={vol_scale:.2f}, floor={entry_floor * 100:.4f}%, " - f"atr_part={entry_dev_atr_part * 100:.4f}%, 最终entry_dev={entry_dev * 100:.4f}%" - ) - - return entry_dev, tp, sl, vol_scale, entry_floor, tp_floor, sl_floor - - # ----------------- 账户/仓位 ----------------- - def get_assets_available(self) -> float: - try: - resp = self.contractAPI.get_assets_detail()[0] - if resp.get("code") != 1000: - return 0.0 - data = resp.get("data") - if isinstance(data, dict): - return float(data.get("available_balance", 0)) - if isinstance(data, list): - for asset in data: - if asset.get("currency") == "USDT": - return float(asset.get("available_balance", 0)) - return 0.0 - except Exception as e: - logger.error(f"余额查询异常: {e}") - return 0.0 - - def get_position_status(self) -> bool: - try: - resp = self.contractAPI.get_position(contract_symbol=self.cfg.contract_symbol)[0] - if resp.get("code") != 1000: - return False - - positions = resp.get("data", []) - if not positions: - self.pos = 0 - return True - - p = positions[0] - self.pos = 1 if p["position_type"] == 1 else -1 - return True - except Exception as e: - logger.error(f"持仓查询异常: {e}") - self.ding(f"持仓查询异常: {e}", error=True) - return False - - def get_equity_proxy(self) -> float: - return self.get_assets_available() - - def refresh_daily_baseline(self): - today = datetime.date.today() - if today != self.day_tag: - self.day_tag = today - self.day_start_equity = None - self.trading_enabled = True - self.ding(f"新的一天({today})：重置日内风控基准") - - def risk_kill_switch(self): - self.refresh_daily_baseline() - equity = self.get_equity_proxy() - if equity <= 0: - return - - if self.day_start_equity is None: - self.day_start_equity = equity - logger.info(f"日内权益基准设定：{equity:.2f} USDT") - return - - pnl = (equity - self.day_start_equity) / self.day_start_equity - if pnl <= -self.cfg.daily_loss_limit: - self.trading_enabled = False - self.ding(f"触发日止损：{pnl * 100:.2f}% -> 停机", error=True) - - if pnl >= self.cfg.daily_profit_cap: - self.trading_enabled = False - self.ding(f"达到日盈利封顶：{pnl * 100:.2f}% -> 停机") - - # ----------------- 下单 ----------------- - def calculate_size(self, price: float) -> int: - bal = self.get_assets_available() - if bal < 10: - return 0 - - margin = bal * self.cfg.risk_percent - lev = int(self.cfg.leverage) - - # ⚠️ 沿用你的原假设：1张≈0.001ETH - size = int((margin * lev) / (price * 0.001)) - size = max(self.cfg.min_size, size) - size = min(self.cfg.max_size, size) - return size - - def place_market_order(self, side: int, size: int) -> bool: - if size <= 0: - return False - - client_order_id = f"mr_{int(time.time())}_{uuid.uuid4().hex[:8]}" - try: - resp = self.contractAPI.post_submit_order( - contract_symbol=self.cfg.contract_symbol, - client_order_id=client_order_id, - side=side, - mode=1, - type="market", - leverage=self.cfg.leverage, - open_type=self.cfg.open_type, - size=size - )[0] - - logger.info(f"order_resp: {resp}") - - if resp.get("code") == 1000: - return True - - self.ding(f"下单失败: {resp}", error=True) - return False - - except APIException as e: - logger.error(f"API下单异常: {e}") - self.ding(f"API下单异常: {e}", error=True) - return False - - except Exception as e: - logger.error(f"下单未知异常: {e}") - self.ding(f"下单未知异常: {e}", error=True) - return False - - def close_position_all(self): - if self.pos == 1: - ok = self.place_market_order(3, 999999) - if ok: - self.pos = 0 - elif self.pos == -1: - ok = self.place_market_order(2, 999999) - if ok: - self.pos = 0 - - # ----------------- 止损后机制 ----------------- - def _reentry_penalty_active(self, dev: float, entry_dev: float) -> bool: - """检查是否需要应用重新入场惩罚""" - if self.last_sl_dir == 0: - 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: - """计算止损后SL放宽倍数""" - 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: - """检查是否在冷却期内""" - 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): - """检查并执行入场""" - 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) - - long_th = -entry_dev - short_th = entry_dev - - if penalty_active: - if self.last_sl_dir == 1: - long_th = -entry_dev * self.cfg.reentry_penalty_mult - logger.info( - f"多头止损后惩罚生效: 入场阈值从 {long_th * 100:.3f}% 调整为 {(-entry_dev * self.cfg.reentry_penalty_mult) * 100:.3f}%") - elif self.last_sl_dir == -1: - short_th = entry_dev * self.cfg.reentry_penalty_mult - logger.info( - f"空头止损后惩罚生效: 入场阈值从 {short_th * 100:.3f}% 调整为 {(entry_dev * self.cfg.reentry_penalty_mult) * 100:.3f}%") - - logger.info( - f"入场检查: 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): - 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): - 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): - """检查并执行出场""" - 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 - - 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: - sl_dir = self.pos - - 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 - ) - - self.last_sl_dir = sl_dir - self.last_sl_ts = time.time() - - 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, - entry_floor: float, tp_floor: float, sl_floor: float): - """限频状态通知""" - 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() - - base_age = int(now - self._base_ratio_ts) if self._base_ratio_ts else -1 - - msg = ( - f"【BitMart {self.cfg.contract_symbol}｜1m均值回归(动态阈值)】\n" - f"📊 状态：{direction_str}\n" - f"💰 现价：{price:.2f} | EMA{self.cfg.ema_len}：{ema_value:.2f}\n" - f"📈 偏离：{dev * 100:.3f}% (入场阈值：±{entry_dev * 100:.3f}%)\n" - f"🌊 波动率：ATR比={atr_ratio * 100:.3f}% | 基准={base_ratio * 100:.3f}% | 缩放={vol_scale:.2f}\n" - f"🎯 动态Floor：入场={entry_floor * 100:.3f}% | 止盈={tp_floor * 100:.3f}% | 止损={sl_floor * 100:.3f}%\n" - f"💰 止盈/止损：{tp * 100:.3f}% / {sl * 100:.3f}% (盈亏比：{tp / sl:.2f})\n" - f"🔄 基准刷新：{self.cfg.base_ratio_refresh_sec}s (已过={base_age}s)\n" - f"⚠️ 止损同向加门槛：{'开启' if penalty_active else '关闭'} (方向={self.last_sl_dir})\n" - f"💳 可用余额：{bal:.2f} USDT | 杠杆：{self.cfg.leverage}x\n" - f"⏱️ 持仓限制：{self.cfg.max_hold_sec}s | 冷却：{self.cfg.cooldown_sec_after_exit}s" - ) - self.ding(msg) - - def action(self): - """主循环""" - 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() - - # 1. 获取K线数据 - klines = self.get_klines_cached() - if not klines or len(klines) < (self.cfg.ema_len + 5): - logger.warning("K线数据不足，等待...") - time.sleep(1) - continue - - # 2. 计算技术指标 - 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 - - # 3. 计算波动率相关指标 - a = self.atr(klines, self.cfg.atr_len) - atr_ratio = (a / price) if price > 0 else 0.0 - - base_ratio = self.get_base_ratio_cached(klines) - - # 4. 计算动态阈值 - entry_dev, tp, sl, vol_scale, entry_floor, tp_floor, sl_floor = self.dynamic_thresholds( - atr_ratio, base_ratio - ) - - # 记录调试信息 - logger.debug( - f"循环数据: price={price:.2f}, ema={ema_value:.2f}, dev={dev * 100:.3f}%, " - f"atr_ratio={atr_ratio * 100:.3f}%, base_ratio={base_ratio * 100:.3f}%, " - f"entry_dev={entry_dev * 100:.3f}%" - ) - - # 5. 风控检查 - self.risk_kill_switch() - - # 6. 获取持仓状态 - if not self.get_position_status(): - time.sleep(1) - continue - - # 7. 检查交易是否启用 - if not self.trading_enabled: - if self.pos != 0: - self.close_position_all() - logger.warning("交易被禁用（风控触发），等待...") - time.sleep(5) - continue - - # 8. 检查危险市场 - 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 - - # 9. 执行交易逻辑 - self.maybe_exit(price, tp, sl, vol_scale) - self.maybe_enter(price, ema_value, entry_dev) - - # 10. 状态通知 - bal = self.get_assets_available() - self.notify_status_throttled( - price, ema_value, dev, bal, - atr_ratio, base_ratio, vol_scale, - entry_dev, tp, sl, - entry_floor, tp_floor, sl_floor - ) - - 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) - - # 设置日志级别为INFO以便查看详细计算过程 - logger.remove() - logger.add(lambda msg: tqdm.write(msg, end=""), level="INFO") - - try: - bot.action() - except KeyboardInterrupt: - logger.info("程序被用户中断") - bot.ding("🤖 策略已手动停止") - except Exception as e: - logger.error(f"程序异常退出: {e}") - bot.ding(f"❌ 策略异常退出: {e}", error=True) - raise - -# 目前动态计算阀值的速度是多少 \ No newline at end of file diff --git a/bitmart/均线自动化开单.py b/bitmart/均线自动化开单.py deleted file mode 100644 index 3e896f5..0000000 --- a/bitmart/均线自动化开单.py +++ /dev/null @@ -1,1165 +0,0 @@ -import time -import datetime -from typing import Tuple, Optional, List -from dataclasses import dataclass, field - -from tqdm import tqdm -from loguru import logger -from bitmart.api_contract import APIContract -from DrissionPage import ChromiumPage, ChromiumOptions - -from bit_tools import openBrowser -from 交易.tools import send_dingtalk_message - - -@dataclass -class StrategyConfig: - """针对90%返佣优化的均值回归策略配置""" - - # ============================= - # ETH 永续 | 1分钟K线 | 90%返佣优化 - # ============================= - - # ===== 合约配置 ===== - contract_symbol: str = "ETHUSDT" - open_type: str = "cross" - leverage: str = "30" - - # ===== K线与指标 ===== - step_min: int = 1 - lookback_min: int = 240 - ema_len: int = 36 - atr_len: int = 14 - - # ===== 动态阈值基准 ===== - vol_baseline_window: int = 60 - vol_baseline_quantile: float = 0.65 - vol_scale_min: float = 0.80 - vol_scale_max: float = 1.60 - base_ratio_refresh_sec: int = 60 - - # ===== 动态floor配置（针对低手续费优化） ===== - entry_dev_floor_min: float = 0.0008 # 0.08%（原0.12%） - entry_dev_floor_max: float = 0.0020 # 0.20%（原0.30%） - entry_dev_floor_base_k: float = 1.10 - - tp_floor_min: float = 0.0004 # 0.04%（原0.06%） - tp_floor_max: float = 0.0015 # 0.15%（原0.20%） - tp_floor_base_k: float = 0.55 - - sl_floor_min: float = 0.0012 # 0.12%（原0.18%） - sl_floor_max: float = 0.0040 # 0.40%（原0.60%） - sl_floor_base_k: float = 1.35 - - # ===== 阈值倍率（针对低手续费优化） ===== - entry_k: float = 1.30 # 原1.45 - tp_k: float = 0.55 # 原0.65 - sl_k: float = 0.90 # 原1.05 - - # ===== 时间/冷却（降低以增加频率） ===== - max_hold_sec: int = 60 # 原75秒 - cooldown_sec_after_exit: int = 5 # 原20秒 - opposite_direction_cooldown: int = 30 # 平仓后同向冷却30秒 - - # ===== 仓位管理 ===== - fixed_margin: float = 10.0 # 固定保证金 - min_size: int = 1 - max_size: int = 10 - max_daily_trades: int = 50 # 每日最大交易次数 - - # ===== 日内风控 ===== - daily_loss_limit: float = 0.02 - daily_profit_cap: float = 0.01 - - # ===== 危险模式过滤 ===== - atr_ratio_kill: float = 0.0038 - big_body_kill: float = 0.010 - - # ===== 轮询节奏 ===== - klines_refresh_sec: int = 10 - tick_refresh_sec: int = 1 - status_notify_sec: int = 60 - - # ===== 止损后机制 ===== - reentry_penalty_mult: float = 1.55 - reentry_penalty_max_sec: int = 180 - reset_band_k: float = 0.45 - reset_band_floor: float = 0.0006 - - post_sl_sl_max_sec: int = 90 - post_sl_mult_min: float = 1.02 - post_sl_mult_max: float = 1.16 - post_sl_vol_alpha: float = 0.20 - - # ===== 正常平仓条件（针对低手续费优化） ===== - normal_exit_threshold: float = 0.0002 # 0.02%（原0.03%） - normal_exit_min_profit: float = 0.0001 # 0.01%（原0.02%） - - # ===== 90%返佣配置 ===== - platform_fee_rate: float = 0.0005 # 平台手续费：开仓价值的万分之五 - rebate_rate: float = 0.90 # 返佣比例：90% - - # ===== 新增：趋势过滤 ===== - use_trend_filter: bool = True - trend_ema_len: int = 50 - trend_threshold: float = 0.0005 # 0.05% - - # ===== 新增：成交量确认 ===== - require_volume_confirmation: bool = True - volume_ma_len: int = 20 - volume_threshold: float = 1.2 - - # ===== 新增：连续亏损控制 ===== - max_consecutive_losses: int = 3 - recovery_wait_sec: int = 60 - - -class BitmartFuturesMeanReversionBot: - def __init__(self, cfg: StrategyConfig, bit_id=None): - self.bit_id = bit_id - self.page: Optional[ChromiumPage] = None - self.cfg = cfg - - self.api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8" - self.secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5" - self.memo = "合约交易" - - if not self.api_key or not self.secret_key: - raise RuntimeError("请先设置API密钥") - - self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15)) - - # 持仓状态 - self.pos = 0 # -1 空, 0 无, 1 多 - self.entry_price: Optional[float] = None - self.entry_ts: Optional[float] = None - self.last_exit_ts = 0.0 - - # 新增：记录上次平仓方向 - self.last_exit_direction = 0 # 1=多平, -1=空平 - self.last_exit_price = 0.0 - - # 开仓信息 - self.entry_margin: Optional[float] = None - self.entry_position_value: Optional[float] = None - - # 日内权益基准 - self.day_start_equity: Optional[float] = None - self.trading_enabled = True - self.day_tag = datetime.date.today() - self.today_trade_count = 0 - self.consecutive_losses = 0 - - # 缓存 - self._klines_cache: Optional[List] = None - self._klines_cache_ts = 0.0 - self._last_status_notify_ts = 0.0 - - # 基准波动率缓存 - self._base_ratio_cached = 0.0015 - self._base_ratio_ts = 0.0 - - # 止损后机制状态 - self.last_sl_dir = 0 - self.last_sl_ts = 0.0 - self.post_sl_dir = 0 - self.post_sl_ts = 0.0 - self.post_sl_vol_scale = 1.0 - - self.pbar = tqdm(total=60, desc="运行中(秒)", ncols=90) - - logger.info(f"初始化完成 - 合约:{cfg.contract_symbol}, 杠杆:{cfg.leverage}x, 返佣:{cfg.rebate_rate * 100}%") - - # ----------------- 工具函数 ----------------- - def ding(self, msg: str, error: bool = False): - """发送钉钉通知""" - prefix = "❌bitmart：" if error else "🔔bitmart：" - if error: - for _ in range(1): - send_dingtalk_message(f"{prefix}{msg}") - else: - send_dingtalk_message(f"{prefix}{msg}") - - def set_leverage(self) -> bool: - """设置杠杆""" - try: - resp = self.contractAPI.post_submit_leverage( - contract_symbol=self.cfg.contract_symbol, - leverage=self.cfg.leverage, - open_type=self.cfg.open_type - )[0] - if resp.get("code") == 1000: - logger.success(f"设置杠杆成功：{self.cfg.open_type} + {self.cfg.leverage}x") - return True - logger.error(f"设置杠杆失败: {resp}") - return False - except Exception as e: - logger.error(f"设置杠杆异常: {e}") - return False - - # ----------------- 行情数据 ----------------- - def get_klines_cached(self) -> Optional[List]: - """获取缓存的K线数据""" - now = time.time() - if self._klines_cache is not None and (now - self._klines_cache_ts) < self.cfg.klines_refresh_sec: - return self._klines_cache - - kl = self.get_klines() - if kl: - self._klines_cache = kl - self._klines_cache_ts = now - return self._klines_cache - - def get_klines(self) -> Optional[List]: - """获取K线数据""" - try: - end_time = int(time.time()) - start_time = end_time - 60 * self.cfg.lookback_min - - resp = self.contractAPI.get_kline( - contract_symbol=self.cfg.contract_symbol, - step=self.cfg.step_min, - start_time=start_time, - end_time=end_time - )[0] - - if resp.get("code") != 1000: - logger.error(f"获取K线失败: {resp}") - return None - - data = resp.get("data", []) - formatted = [] - for k in data: - formatted.append({ - "id": int(k["timestamp"]), - "open": float(k["open_price"]), - "high": float(k["high_price"]), - "low": float(k["low_price"]), - "close": float(k["close_price"]), - }) - formatted.sort(key=lambda x: x["id"]) - return formatted - except Exception as e: - logger.error(f"获取K线异常: {e}") - return None - - def get_last_price(self, fallback_close: float) -> float: - """获取最新价格""" - try: - if hasattr(self.contractAPI, "get_contract_details"): - r = self.contractAPI.get_contract_details(contract_symbol=self.cfg.contract_symbol)[0] - d = r.get("data") if isinstance(r, dict) else None - if isinstance(d, dict): - for key in ("last_price", "mark_price", "index_price"): - if key in d and d[key] is not None: - return float(d[key]) - - if hasattr(self.contractAPI, "get_ticker"): - r = self.contractAPI.get_ticker(contract_symbol=self.cfg.contract_symbol)[0] - d = r.get("data") if isinstance(r, dict) else None - if isinstance(d, dict): - for key in ("last_price", "price", "last", "close"): - if key in d and d[key] is not None: - return float(d[key]) - except Exception: - pass - - return float(fallback_close) - - @staticmethod - def ema(values: List[float], n: int) -> float: - """计算EMA""" - k = 2 / (n + 1) - e = values[0] - for v in values[1:]: - e = v * k + e * (1 - k) - return e - - @staticmethod - def atr(klines: List[dict], n: int) -> float: - """计算ATR""" - if len(klines) < n + 1: - return 0.0 - trs = [] - for i in range(-n, 0): - cur = klines[i] - prev = klines[i - 1] - tr = max( - cur["high"] - cur["low"], - abs(cur["high"] - prev["close"]), - abs(cur["low"] - prev["close"]), - ) - trs.append(tr) - return sum(trs) / len(trs) - - # ----------------- 风控检查 ----------------- - def is_danger_market(self, klines: List[dict], price: float) -> bool: - """检查是否危险市场""" - last = klines[-1] - body = abs(last["close"] - last["open"]) / last["open"] if last["open"] else 0.0 - if body >= self.cfg.big_body_kill: - logger.warning(f"大实体K线: {body * 100:.2f}%") - return True - - a = self.atr(klines, self.cfg.atr_len) - atr_ratio = (a / price) if price > 0 else 0.0 - if atr_ratio >= self.cfg.atr_ratio_kill: - logger.warning(f"高ATR比率: {atr_ratio * 100:.2f}%") - return True - - return False - - def check_trend_filter(self, price: float) -> bool: - """趋势过滤器""" - if not self.cfg.use_trend_filter: - return True - - klines = self.get_klines_cached() - if not klines or len(klines) < self.cfg.trend_ema_len: - return True - - try: - closes = [k["close"] for k in klines[-(self.cfg.trend_ema_len + 1):]] - trend_ema = self.ema(closes, self.cfg.trend_ema_len) - trend_dev = (price - trend_ema) / trend_ema if trend_ema else 0.0 - - if abs(trend_dev) > self.cfg.trend_threshold: - logger.debug(f"趋势过滤触发: 偏差={trend_dev * 100:.3f}%, 阈值={self.cfg.trend_threshold * 100:.3f}%") - return False - - return True - except Exception as e: - logger.error(f"趋势过滤异常: {e}") - return True - - # ----------------- 波动率计算 ----------------- - def atr_ratio_baseline(self, klines: List[dict]) -> float: - """计算ATR比率基准""" - window = min(self.cfg.vol_baseline_window, len(klines) - self.cfg.atr_len - 1) - if window <= 10: - logger.warning(f"数据不足计算基准: {len(klines)}根K线") - return 0.0 - - ratios = [] - step = 3 - - for i in range(-window, 0, step): - if len(klines) + i < self.cfg.atr_len + 1: - continue - - start_idx = len(klines) + i - self.cfg.atr_len - end_idx = len(klines) + i - - if start_idx < 0 or end_idx <= start_idx: - continue - - sub_klines = klines[start_idx:end_idx] - if len(sub_klines) >= self.cfg.atr_len + 1: - a = self.atr(sub_klines, self.cfg.atr_len) - price = klines[end_idx - 1]["close"] - if a > 0 and price > 0: - ratio = a / price - if 0.0001 < ratio < 0.01: - ratios.append(ratio) - - if len(ratios) < 5: - a = self.atr(klines[-60:], self.cfg.atr_len) - price = klines[-1]["close"] - if a > 0 and price > 0: - baseline = a / price - logger.debug(f"使用全量数据计算基准: {baseline * 100:.4f}%") - return baseline - else: - return 0.0 - - ratios.sort() - idx = min(len(ratios) - 1, - max(0, int(self.cfg.vol_baseline_quantile * (len(ratios) - 1)))) - baseline = ratios[idx] - - logger.debug(f"基准计算: 样本数={len(ratios)}, 基准={baseline * 100:.4f}%") - return baseline - - def get_base_ratio_cached(self, klines: List[dict]) -> float: - """获取缓存的基准波动率""" - now = time.time() - refresh_sec = self.cfg.base_ratio_refresh_sec - - if (self._base_ratio_cached is None or - (now - self._base_ratio_ts) >= refresh_sec): - - baseline = self.atr_ratio_baseline(klines) - - if baseline > 0.0001: - self._base_ratio_cached = baseline - self._base_ratio_ts = now - logger.info(f"基准波动率更新: {baseline * 100:.4f}%") - else: - current_price = klines[-1]["close"] if klines else 3000 - if current_price > 4000: - default_baseline = 0.0010 - elif current_price > 3500: - default_baseline = 0.0012 - elif current_price > 3000: - default_baseline = 0.0015 - elif current_price > 2500: - default_baseline = 0.0018 - else: - default_baseline = 0.0020 - - self._base_ratio_cached = default_baseline - self._base_ratio_ts = now - logger.warning(f"使用价格动态默认基准: {default_baseline * 100:.4f}%") - - return self._base_ratio_cached - - @staticmethod - def _clamp(x: float, lo: float, hi: float) -> float: - """限制数值在指定范围内""" - return max(lo, min(hi, x)) - - # ----------------- 动态阈值计算 ----------------- - def dynamic_thresholds(self, atr_ratio: float, base_ratio: float) -> Tuple[ - float, float, float, float, float, float, float]: - """计算动态阈值""" - if atr_ratio <= 0: - logger.warning(f"ATR比率异常: {atr_ratio}") - atr_ratio = 0.001 - - if base_ratio < 0.0005: - base_ratio = max(0.001, atr_ratio * 1.2) - logger.debug(f"基准太小，使用调整后的atr_ratio: {base_ratio * 100:.4f}%") - - # vol_scale计算 - if base_ratio > 0: - raw_scale = atr_ratio / base_ratio - vol_scale = self._clamp(raw_scale, self.cfg.vol_scale_min, self.cfg.vol_scale_max) - else: - vol_scale = 1.0 - - # 动态floor计算 - entry_floor_raw = self.cfg.entry_dev_floor_base_k * base_ratio - entry_floor = self._clamp( - entry_floor_raw, - self.cfg.entry_dev_floor_min, - self.cfg.entry_dev_floor_max, - ) - - tp_floor_raw = self.cfg.tp_floor_base_k * base_ratio - tp_floor = self._clamp( - tp_floor_raw, - self.cfg.tp_floor_min, - self.cfg.tp_floor_max, - ) - - sl_floor_raw = self.cfg.sl_floor_base_k * base_ratio - sl_floor = self._clamp( - sl_floor_raw, - self.cfg.sl_floor_min, - self.cfg.sl_floor_max, - ) - - # 最终阈值 - entry_dev_atr_part = self.cfg.entry_k * vol_scale * atr_ratio - entry_dev = max(entry_floor, entry_dev_atr_part) - - tp_atr_part = self.cfg.tp_k * vol_scale * atr_ratio - tp = max(tp_floor, tp_atr_part) - - sl_atr_part = self.cfg.sl_k * vol_scale * atr_ratio - sl = max(sl_floor, sl_atr_part) - - entry_dev = max(entry_dev, self.cfg.entry_dev_floor_min) - - logger.info( - f"动态阈值: entry={entry_dev * 100:.4f}%, tp={tp * 100:.4f}%, sl={sl * 100:.4f}%, " - f"vol_scale={vol_scale:.2f}" - ) - - return entry_dev, tp, sl, vol_scale, entry_floor, tp_floor, sl_floor - - # ----------------- 账户仓位管理 ----------------- - def get_assets_available(self) -> float: - """获取可用余额""" - try: - resp = self.contractAPI.get_assets_detail()[0] - if resp.get("code") != 1000: - return 0.0 - data = resp.get("data") - if isinstance(data, dict): - return float(data.get("available_balance", 0)) - if isinstance(data, list): - for asset in data: - if asset.get("currency") == "USDT": - return float(asset.get("available_balance", 0)) - return 0.0 - except Exception as e: - logger.error(f"余额查询异常: {e}") - return 0.0 - - def get_position_status(self) -> bool: - """获取持仓状态""" - try: - resp = self.contractAPI.get_position(contract_symbol=self.cfg.contract_symbol)[0] - if resp.get("code") != 1000: - return False - - positions = resp.get("data", []) - if not positions: - self.pos = 0 - return True - - p = positions[0] - self.pos = 1 if p["position_type"] == 1 else -1 - return True - except Exception as e: - logger.error(f"持仓查询异常: {e}") - return False - - def get_equity_proxy(self) -> float: - """获取权益""" - return self.get_assets_available() - - def refresh_daily_baseline(self): - """刷新日内基准""" - today = datetime.date.today() - if today != self.day_tag: - self.day_tag = today - self.day_start_equity = None - self.trading_enabled = True - self.today_trade_count = 0 - self.consecutive_losses = 0 - logger.info(f"新的一天({today})：重置日内风控基准") - - def risk_kill_switch(self): - """风险控制开关""" - self.refresh_daily_baseline() - equity = self.get_equity_proxy() - if equity <= 0: - return - - if self.day_start_equity is None: - self.day_start_equity = equity - logger.info(f"日内权益基准设定：{equity:.2f} USDT") - return - - pnl = (equity - self.day_start_equity) / self.day_start_equity - if pnl <= -self.cfg.daily_loss_limit: - self.trading_enabled = False - self.ding(f"触发日止损：{pnl * 100:.2f}% -> 停机", error=True) - - if pnl >= self.cfg.daily_profit_cap: - self.trading_enabled = False - self.ding(f"达到日盈利封顶：{pnl * 100:.2f}% -> 停机") - - def calculate_size(self, price: float) -> int: - """计算仓位大小""" - bal = self.get_assets_available() - if bal < self.cfg.fixed_margin: - logger.warning(f"余额不足：{bal:.2f} USDT < {self.cfg.fixed_margin} USDT") - return 0 - - margin = self.cfg.fixed_margin - lev = int(self.cfg.leverage) - size = int((margin * lev) / (price * 0.001)) - size = max(self.cfg.min_size, size) - size = min(self.cfg.max_size, size) - - logger.debug(f"计算仓位：保证金={margin}u, 杠杆={lev}x, size={size}") - return size - - # ----------------- 浏览器操作 ----------------- - def openBrowser(self) -> bool: - """打开浏览器""" - try: - bit_port = openBrowser(id=self.bit_id) - co = ChromiumOptions() - co.set_local_port(port=bit_port) - self.page = ChromiumPage(addr_or_opts=co) - return True - except Exception as e: - logger.error(f"打开浏览器失败: {e}") - return False - - def click_safe(self, xpath: str, sleep: float = 0.5) -> bool: - """安全点击""" - try: - ele = self.page.ele(xpath) - if not ele: - return False - ele.scroll.to_see(center=True) - time.sleep(sleep) - ele.click() - return True - except Exception as e: - logger.error(f"点击失败: {e}") - return False - - # ----------------- 订单执行 ----------------- - def place_market_order(self, side: int, size: int) -> bool: - """下市价单""" - if size <= 0: - return False - size = 10 - try: - # 确保size在合理范围内 - size = max(self.cfg.min_size, min(self.cfg.max_size, size)) - - # 开多单 - if side == 1: - self.click_safe('x://button[normalize-space(text()) ="市价"]') - self.page.ele('x://*[@id="size_0"]').input(str(size), clear=True) - self.click_safe('x://span[normalize-space(text()) ="买入/做多"]') - logger.info(f"✅ 开多单: size={size}") - return True - - # 开空单 - elif side == 4: - self.click_safe('x://button[normalize-space(text()) ="市价"]') - self.page.ele('x://*[@id="size_0"]').input(str(size), clear=True) - self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]') - logger.info(f"✅ 开空单: size={size}") - return True - - # 平多单 - elif side == 2: - self.click_safe('x://span[normalize-space(text()) ="市价"]') - time.sleep(0.3) - self.page.ele('x://*[@id="size_0"]').input(str(size), clear=True) - time.sleep(0.3) - self.click_safe('x://span[normalize-space(text()) ="卖出/做空"]') - logger.info(f"✅ 平多单: size={size}") - return True - - # 平空单 - elif side == 3: - self.click_safe('x://span[normalize-space(text()) ="市价"]') - time.sleep(0.3) - self.page.ele('x://*[@id="size_0"]').input(str(size), clear=True) - time.sleep(0.3) - self.click_safe('x://span[normalize-space(text()) ="买入/做多"]') - logger.info(f"✅ 平空单: size={size}") - return True - - else: - logger.error(f"未知的订单方向: side={side}") - return False - - except Exception as e: - logger.error(f"下单异常: {e}") - return False - - def calculate_fee(self, position_value: float) -> float: - """计算手续费（考虑90%返佣）""" - platform_fee = position_value * self.cfg.platform_fee_rate - actual_fee = platform_fee * (1 - self.cfg.rebate_rate) - return actual_fee - - def calculate_net_pnl(self, price: float) -> Tuple[float, float, float]: - """计算净盈亏""" - if self.pos == 0 or self.entry_price is None or self.entry_margin is None or self.entry_position_value is None: - return 0.0, 0.0, 0.0 - - leverage = int(self.cfg.leverage) - - # 计算价格变动比例 - if self.pos == 1: - price_change_ratio = (price - self.entry_price) / self.entry_price - else: - price_change_ratio = (self.entry_price - price) / self.entry_price - - # 计算毛盈亏比例（考虑杠杆） - gross_pnl_ratio = leverage * price_change_ratio - - # 计算手续费 - entry_fee = self.calculate_fee(self.entry_position_value) - exit_position_value = self.entry_position_value - exit_fee = self.calculate_fee(exit_position_value) - total_fee = entry_fee + exit_fee - - # 手续费相对于保证金的比率 - fee_ratio = total_fee / self.entry_margin - - # 净盈亏 = 毛盈亏 - 手续费比率 - net_pnl_ratio = gross_pnl_ratio - fee_ratio - - return net_pnl_ratio, total_fee, gross_pnl_ratio - - def close_position_all(self) -> bool: - """平掉所有持仓""" - if self.pos == 0: - logger.info("当前无持仓，无需平仓") - return True - - max_retries = 3 - retry_delay = 1.0 - - for attempt in range(1, max_retries + 1): - logger.info(f"平仓尝试 {attempt}/{max_retries}...") - old_pos = self.pos - - # 执行平仓操作 - if self.pos == 1: - ok = self.place_market_order(2, 999999) - if not ok: - logger.warning(f"平多单操作失败 (尝试 {attempt}/{max_retries})") - if attempt < max_retries: - time.sleep(retry_delay) - continue - else: - self.ding(f"平多单失败：已重试{max_retries}次仍失败", error=True) - return False - elif self.pos == -1: - ok = self.place_market_order(3, 999999) - if not ok: - logger.warning(f"平空单操作失败 (尝试 {attempt}/{max_retries})") - if attempt < max_retries: - time.sleep(retry_delay) - continue - else: - self.ding(f"平空单失败：已重试{max_retries}次仍失败", error=True) - return False - else: - return True - - # 等待订单执行 - time.sleep(1.5) - - # 验证是否平仓成功 - verify_success = self._verify_position_closed(old_pos) - if verify_success: - self.pos = 0 - logger.success(f"✅ 平仓成功 (尝试 {attempt}/{max_retries})") - return True - else: - logger.warning(f"平仓验证失败 (尝试 {attempt}/{max_retries})") - if attempt < max_retries: - time.sleep(retry_delay) - self.get_position_status() - else: - self.ding(f"平仓失败：已重试{max_retries}次", error=True) - return False - - return False - - def _verify_position_closed(self, expected_old_pos: int) -> bool: - """验证持仓是否已平仓""" - try: - resp = self.contractAPI.get_position(contract_symbol=self.cfg.contract_symbol)[0] - - if resp.get("code") != 1000: - logger.warning(f"查询持仓状态失败: {resp}") - return False - - positions = resp.get("data", []) - if not positions or len(positions) == 0: - logger.info("✅ SDK验证：持仓已平仓") - return True - - for p in positions: - position_type = p.get("position_type", 0) - current_pos = 1 if position_type == 1 else -1 - if current_pos == expected_old_pos: - logger.warning(f"⚠️ SDK验证：持仓仍存在") - return False - - logger.info("✅ SDK验证：持仓已平仓或已改变") - return True - - except Exception as e: - logger.error(f"验证持仓状态异常: {e}") - return False - - # ----------------- 止损后机制 ----------------- - def _reentry_penalty_active(self, dev: float, entry_dev: float) -> bool: - """检查是否需要应用重新入场惩罚""" - if self.last_sl_dir == 0: - 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: - """计算止损后SL放宽倍数""" - 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) - return max(self.cfg.post_sl_mult_min, min(self.cfg.post_sl_mult_max, raw)) - - # ----------------- 交易逻辑（核心修复） ----------------- - def in_cooldown(self) -> bool: - """检查是否在冷却期内""" - 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): - """ - 检查并执行入场 - 修复版 - 修复问题：避免平仓后立即开反向仓位 - """ - # 基础检查 - if self.pos != 0: - return - - if self.in_cooldown(): - return - - if not self.trading_enabled: - return - - # 连续亏损控制 - if self.consecutive_losses >= self.cfg.max_consecutive_losses: - logger.warning(f"连续亏损{self.consecutive_losses}次，暂停交易{self.cfg.recovery_wait_sec}秒") - time.sleep(self.cfg.recovery_wait_sec) - return - - # 日内交易次数限制 - if self.today_trade_count >= self.cfg.max_daily_trades: - logger.info(f"达到日交易次数上限: {self.today_trade_count}") - return - - # 趋势过滤 - if not self.check_trend_filter(price): - return - - dev = (price - ema_value) / ema_value if ema_value else 0.0 - size = self.calculate_size(price) - if size <= 0: - return - - # 方向过滤：避免平仓后立即反向开仓 - if self.last_exit_direction != 0: - time_since_exit = time.time() - self.last_exit_ts - - # 如果是平多后（做空方向），且在冷却期内，避免立即开多 - if (self.last_exit_direction == 1 and # 上次是多平 - time_since_exit < self.cfg.opposite_direction_cooldown and - dev <= 0): # 当前适合开多 - logger.info(f"平多后{int(time_since_exit)}秒内，避免开多") - return - - # 如果是平空后（做多方向），且在冷却期内，避免立即开空 - if (self.last_exit_direction == -1 and # 上次是空平 - time_since_exit < self.cfg.opposite_direction_cooldown and - dev >= 0): # 当前适合开空 - logger.info(f"平空后{int(time_since_exit)}秒内，避免开空") - return - - penalty_active = self._reentry_penalty_active(dev, entry_dev) - long_th = -entry_dev - short_th = entry_dev - - 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"入场检查: 偏离={dev * 100:.3f}%, 阈值=[{long_th * 100:.3f}%, {short_th * 100:.3f}%], " - f"size={size}, 连续亏损={self.consecutive_losses}" - ) - - # 开多条件：价格显著低于EMA - if dev <= long_th: - if self.place_market_order(1, size): - self.pos = 1 - self.entry_price = price - self.entry_ts = time.time() - self.entry_margin = self.cfg.fixed_margin - self.entry_position_value = self.entry_margin * int(self.cfg.leverage) - self.ding(f"✅开多：偏离={dev * 100:.3f}%, 价格={price:.2f}") - - # 开空条件：价格显著高于EMA - elif dev >= short_th: - if self.place_market_order(4, size): - self.pos = -1 - self.entry_price = price - self.entry_ts = time.time() - self.entry_margin = self.cfg.fixed_margin - self.entry_position_value = self.entry_margin * int(self.cfg.leverage) - self.ding(f"✅开空：偏离={dev * 100:.3f}%, 价格={price:.2f}") - - def maybe_exit(self, price: float, ema_value: float, tp: float, sl: float, vol_scale: float): - """ - 检查并执行出场 - 记录平仓方向，用于后续入场过滤 - """ - if self.pos == 0 or self.entry_price is None or self.entry_ts is None: - return - - hold = time.time() - self.entry_ts - net_pnl, total_fee, gross_pnl = self.calculate_net_pnl(price) - dev = (price - ema_value) / ema_value if ema_value else 0.0 - - # 计算止损倍数 - 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 - - # 记录平仓前的方向 - old_pos = self.pos - - # 条件1：正常平仓（价格回归EMA） - if abs(dev) <= self.cfg.normal_exit_threshold: - if net_pnl >= self.cfg.normal_exit_min_profit: # 净盈利达到最小要求 - if self.close_position_all(): - self._record_exit(price, old_pos, net_pnl, total_fee, gross_pnl, "正常平仓") - return - else: - logger.error("正常平仓失败") - return - - # 条件2：止盈 - if gross_pnl >= tp: - if net_pnl > 0: # 扣除手续费后仍有盈利 - if self.close_position_all(): - self._record_exit(price, old_pos, net_pnl, total_fee, gross_pnl, "止盈") - return - else: - logger.error("止盈平仓失败") - return - - # 条件3：止损 - if gross_pnl <= -effective_sl: - if self.close_position_all(): - self._record_exit(price, old_pos, net_pnl, total_fee, gross_pnl, "止损") - - # 记录止损状态 - sl_dir = old_pos - self.last_sl_dir = sl_dir - self.last_sl_ts = time.time() - self.post_sl_dir = sl_dir - self.post_sl_ts = time.time() - self.post_sl_vol_scale = float(vol_scale) - return - else: - logger.error("止损平仓失败") - return - - # 条件4：超时平仓 - if hold >= self.cfg.max_hold_sec: - if net_pnl > 0: # 扣除手续费后仍有盈利 - if self.close_position_all(): - self._record_exit(price, old_pos, net_pnl, total_fee, gross_pnl, "超时平仓") - return - else: - logger.error("超时平仓失败") - return - else: - logger.debug(f"超时但净盈亏为负，继续持有") - - def _record_exit(self, price: float, old_pos: int, net_pnl: float, - total_fee: float, gross_pnl: float, exit_type: str): - """记录平仓信息""" - self.entry_price = None - self.entry_ts = None - self.entry_margin = None - self.entry_position_value = None - self.last_exit_ts = time.time() - self.last_exit_direction = old_pos - self.last_exit_price = price - self.today_trade_count += 1 - - # 更新连续亏损计数 - if net_pnl < 0: - self.consecutive_losses += 1 - else: - self.consecutive_losses = 0 - - self.ding( - f"📊{exit_type}：方向={'多' if old_pos == 1 else '空'}, " - f"毛盈亏={gross_pnl * 100:.3f}%, 净盈亏={net_pnl * 100:.3f}%, " - f"手续费={total_fee:.4f}u, 价格={price:.2f}" - ) - - # ----------------- 状态通知 ----------------- - 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, - entry_floor: float, tp_floor: float, sl_floor: float): - """限频状态通知""" - 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") - - # 计算当前盈亏 - current_net_pnl, current_fee, current_gross_pnl = 0.0, 0.0, 0.0 - if self.pos != 0 and self.entry_price: - current_net_pnl, current_fee, current_gross_pnl = self.calculate_net_pnl(price) - - msg = ( - f"【BitMart {self.cfg.contract_symbol}｜1m均值回归(90%返佣优化)】\n" - f"📊 状态：{direction_str} | 今日交易：{self.today_trade_count}/{self.cfg.max_daily_trades}\n" - f"💰 现价：{price:.2f} | EMA{self.cfg.ema_len}：{ema_value:.2f} | 偏离：{dev * 100:.3f}%\n" - f"🎯 阈值：入场±{entry_dev * 100:.3f}% | 止盈{tp * 100:.3f}% | 止损{sl * 100:.3f}%\n" - f"🌊 波动率：ATR={atr_ratio * 100:.3f}% | 基准={base_ratio * 100:.3f}% | 缩放={vol_scale:.2f}\n" - f"💳 余额：{bal:.2f} USDT | 杠杆：{self.cfg.leverage}x | 保证金：{self.cfg.fixed_margin}u\n" - ) - - if self.pos != 0: - msg += ( - f"📈 当前盈亏：毛={current_gross_pnl * 100:.3f}% | 净={current_net_pnl * 100:.3f}% | " - f"手续费={current_fee:.4f}u\n" - f"⚠️ 连续亏损：{self.consecutive_losses}次\n" - ) - - self.ding(msg) - - # ----------------- 主循环 ----------------- - def action(self): - """主循环""" - if not self.set_leverage(): - self.ding("杠杆设置失败，停止运行", error=True) - return - - # 打开浏览器 - if not self.openBrowser(): - self.ding("打开 TGE 失败！", error=True) - return - logger.info("TGE 端口获取成功") - - self.page.get("https://derivatives.bitmart.com/zh-CN/futures/ETHUSDT") - time.sleep(3) # 等待页面加载 - - logger.info("策略启动 - 90%返佣优化版") - logger.info("策略特点：低阈值、高频次、严格方向过滤") - - while True: - now_dt = datetime.datetime.now() - self.pbar.n = now_dt.second - self.pbar.refresh() - - # 1. 获取K线数据 - klines = self.get_klines_cached() - if not klines or len(klines) < (self.cfg.ema_len + 5): - logger.warning("K线数据不足，等待...") - time.sleep(1) - continue - - # 2. 计算技术指标 - 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 - - # 3. 计算波动率指标 - a = self.atr(klines, self.cfg.atr_len) - atr_ratio = (a / price) if price > 0 else 0.0 - base_ratio = self.get_base_ratio_cached(klines) - - # 4. 计算动态阈值 - entry_dev, tp, sl, vol_scale, entry_floor, tp_floor, sl_floor = self.dynamic_thresholds( - atr_ratio, base_ratio - ) - - # 5. 风控检查 - self.risk_kill_switch() - - # 6. 获取持仓状态 - if not self.get_position_status(): - time.sleep(1) - continue - - # 7. 检查交易是否启用 - if not self.trading_enabled: - if self.pos != 0: - if self.close_position_all(): - logger.info("交易被禁用，已平仓") - else: - logger.error("交易被禁用，但平仓失败") - logger.warning("交易被禁用，等待...") - time.sleep(5) - continue - - # 8. 检查危险市场 - if self.is_danger_market(klines, price): - logger.warning("危险模式，暂停开仓") - self.maybe_exit(price, ema_value, tp, sl, vol_scale) - time.sleep(self.cfg.tick_refresh_sec) - continue - - # 9. 执行交易逻辑 - # 先检查平仓 - self.maybe_exit(price, ema_value, tp, sl, vol_scale) - # 再检查开仓 - self.maybe_enter(price, ema_value, entry_dev) - - # 10. 状态通知 - bal = self.get_assets_available() - self.notify_status_throttled( - price, ema_value, dev, bal, - atr_ratio, base_ratio, vol_scale, - entry_dev, tp, sl, - entry_floor, tp_floor, sl_floor - ) - - 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, bit_id="f2320f57e24c45529a009e1541e25961") - - # 设置日志级别 - logger.remove() - logger.add(lambda msg: tqdm.write(msg, end=""), level="INFO") - - logger.info(""" - ==================================================== - 90%返佣优化策略说明： - - 策略特点： - 1. 针对90%返佣优化，阈值降低30-50% - 2. 增加方向过滤，避免平仓后立即反向开仓 - 3. 冷却时间从20秒减至5秒，提高交易频率 - 4. 添加连续亏损控制和趋势过滤 - 5. 日内交易次数限制：50次 - - 核心修复： - 1. 避免平仓后立即反向开仓（原策略最大问题） - 2. 修复平仓后可能立即开反向仓位的问题 - 3. 增加对同方向冷却的控制 - ==================================================== - """) - - try: - bot.action() - except KeyboardInterrupt: - logger.info("程序被用户中断") - bot.ding("🤖 策略已手动停止") - except Exception as e: - logger.error(f"程序异常退出: {e}") - bot.ding(f"❌ 策略异常退出: {e}", error=True) - raise diff --git a/bitmart/抓取数据_30分钟.py b/bitmart/抓取数据_30分钟.py deleted file mode 100644 index b1c52f2..0000000 --- a/bitmart/抓取数据_30分钟.py +++ /dev/null @@ -1,169 +0,0 @@ -""" -BitMart 15分钟K线数据抓取脚本 -从 BitMart API 获取15分钟K线数据并存储到数据库 -""" - -import time -from loguru import logger -from bitmart.api_contract import APIContract -from models.bitmart_15 import BitMart15 - - -class BitMartDataCollector: - def __init__(self): - self.api_key = "a0fb7b98464fd9bcce67e7c519d58ec10d0c38a8" - self.secret_key = "4eaeba78e77aeaab1c2027f846a276d164f264a44c2c1bb1c5f3be50c8de1ca5" - self.memo = "数据抓取" - self.contract_symbol = "ETHUSDT" - self.contractAPI = APIContract(self.api_key, self.secret_key, self.memo, timeout=(5, 15)) - - def get_klines(self, start_time=None, end_time=None, limit=200): - """ - 获取K线数据 - :param start_time: 开始时间戳（秒级） - :param end_time: 结束时间戳（秒级） - :param limit: 获取数量限制 - :return: K线数据列表 - """ - try: - if not end_time: - end_time = int(time.time()) - if not start_time: - start_time = end_time - 3600 * 24 * 1 # 默认获取最近7天 - - response = self.contractAPI.get_kline( - contract_symbol=self.contract_symbol, - step=15, # 15分钟 - start_time=start_time, - end_time=end_time - )[0] - - if response['code'] != 1000: - logger.error(f"获取K线失败: {response}") - return [] - - klines = response.get('data', []) - formatted = [] - for k in klines: - # BitMart API 返回的时间戳是秒级，需要转换为毫秒级 - # 根据 bitmart/框架.py 中的使用方式，API返回的是秒级时间戳 - timestamp_ms = int(k["timestamp"]) * 1000 - - formatted.append({ - 'id': timestamp_ms, - 'open': float(k["open_price"]), - 'high': float(k["high_price"]), - 'low': float(k["low_price"]), - 'close': float(k["close_price"]) - }) - - # 按时间戳排序 - formatted.sort(key=lambda x: x['id']) - return formatted - except Exception as e: - logger.error(f"获取K线异常: {e}") - return [] - - def save_klines(self, klines): - """ - 保存K线数据到数据库 - :param klines: K线数据列表 - :return: 保存的数量 - """ - saved_count = 0 - for kline in klines: - try: - BitMart15.get_or_create( - id=kline['id'], - defaults={ - 'open': kline['open'], - 'high': kline['high'], - 'low': kline['low'], - 'close': kline['close'], - } - ) - saved_count += 1 - except Exception as e: - logger.error(f"保存K线数据失败 {kline['id']}: {e}") - - return saved_count - - def collect_historical_data(self, start_date=None, days=None): - """ - 抓取历史数据（从指定日期到现在） - :param start_date: 起始日期字符串，格式 'YYYY-MM-DD'，如 '2025-01-01' - :param days: 如果不指定 start_date，则抓取最近多少天的数据 - """ - import datetime - - now = int(time.time()) - - if start_date: - # 解析起始日期 - start_dt = datetime.datetime.strptime(start_date, '%Y-%m-%d') - target_start_time = int(start_dt.timestamp()) - logger.info(f"开始抓取 BitMart {self.contract_symbol} 从 {start_date} 到现在的15分钟K线数据") - elif days: - target_start_time = now - 3600 * 24 * days - logger.info(f"开始抓取 BitMart {self.contract_symbol} 最近 {days} 天的15分钟K线数据") - else: - target_start_time = now - 3600 * 24 * 30 # 默认30天 - logger.info(f"开始抓取 BitMart {self.contract_symbol} 最近 30 天的15分钟K线数据") - - # 分批获取，每次获取5天的数据（15分钟K线数据量较大） - batch_days = 5 - total_saved = 0 - fail_count = 0 - max_fail = 3 # 连续失败超过3次则停止 - - current_end = now - while current_end > target_start_time: - current_start = max(current_end - 3600 * 24 * batch_days, target_start_time) - - logger.info(f"抓取时间段: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(current_start))} " - f"到 {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(current_end))}") - - klines = self.get_klines(start_time=current_start, end_time=current_end) - if klines: - saved = self.save_klines(klines) - total_saved += saved - logger.info(f"本批次保存 {saved} 条数据，累计 {total_saved} 条") - fail_count = 0 # 重置失败计数 - else: - fail_count += 1 - logger.warning(f"本批次未获取到数据 (连续失败 {fail_count} 次)") - if fail_count >= max_fail: - logger.error(f"连续 {max_fail} 次获取数据失败，可能已达到 API 历史数据限制，停止抓取") - break - - current_end = current_start - time.sleep(1) # 避免请求过快 - - logger.success(f"数据抓取完成，共保存 {total_saved} 条K线数据") - - def collect_realtime_data(self): - """ - 实时抓取最新数据（用于定时任务） - """ - logger.info("开始抓取 BitMart 最新15分钟K线数据") - - # 获取最近1小时的数据（确保能获取到最新的K线） - end_time = int(time.time()) - start_time = end_time - 3600 * 2 # 最近2小时 - - klines = self.get_klines(start_time=start_time, end_time=end_time) - if klines: - saved = self.save_klines(klines) - logger.success(f"保存 {saved} 条最新K线数据") - else: - logger.warning("未获取到最新数据") - - -if __name__ == '__main__': - collector = BitMartDataCollector() - - # 抓取从 2025-01-01 到现在的15分钟K线历史数据 - collector.collect_historical_data(start_date='2025-01-01') - - # 如果需要实时抓取，可以取消下面的注释 - # collector.collect_realtime_data() diff --git a/mexc/30分钟.py b/mexc/30分钟.py index 217b511..7c6fa4c 100644 --- a/mexc/30分钟.py +++ b/mexc/30分钟.py @@ -41,6 +41,57 @@ from models.mexc import Mexc30 # ========================= 工具函数 ========================= +# 交易对的最小价格单位（tick size）配置 +# 格式：交易对符号 -> 最小单位 +TICK_SIZE_MAP = { + 'SOLUSDT': 0.01, + 'BTCUSDT': 0.1, + 'ETHUSDT': 0.01, + 'BNBUSDT': 0.01, + # 可以根据需要添加更多交易对 +} + +# 默认最小单位（如果交易对不在配置中） +DEFAULT_TICK_SIZE = 0.01 + + +def get_tick_size(symbol: str) -> float: + """ + 获取交易对的最小价格单位 + :param symbol: 交易对符号，如 'SOLUSDT' + :return: 最小单位，如 0.01 + """ + return TICK_SIZE_MAP.get(symbol.upper(), DEFAULT_TICK_SIZE) + + +def adjust_price_for_trade(price: float, direction: str, symbol: str = 'SOLUSDT') -> float: + """ + 根据交易方向调整价格，考虑买卖价差 + + 买入（开多/平空）：价格 + tick_size + 卖出（开空/平多）：价格 - tick_size + + :param price: 原始价格（K线开盘价或收盘价） + :param direction: 交易方向，'long' 表示买入，'short' 表示卖出 + :param symbol: 交易对符号，用于获取最小单位 + :return: 调整后的价格 + """ + tick_size = get_tick_size(symbol) + + if direction == 'long': + # 买入：价格 + tick_size + adjusted = price + tick_size + elif direction == 'short': + # 卖出：价格 - tick_size + adjusted = price - tick_size + else: + # 未知方向，返回原价 + adjusted = price + + # 确保价格不会为负 + return max(adjusted, tick_size) + + def is_bullish(c): # 阳线 return float(c['close']) > float(c['open']) @@ -109,7 +160,7 @@ def get_data_by_date(model, date_str: str): # ========================= 回测逻辑 ========================= -def backtest_15m_trend_optimized(dates: List[str]): +def backtest_15m_trend_optimized(dates: List[str], symbol: str = 'SOLUSDT'): """ 回测策略逻辑： 1. 开仓条件（信号出现时，下一根K线开盘价开仓）： @@ -182,7 +233,9 @@ def backtest_15m_trend_optimized(dates: List[str]): if current_position is None: if direction: # 信号出现（prev和curr形成信号），在下一根K线（next_bar）的开盘价开仓 - entry_price = float(next_bar['open']) + # 应用买卖价差：买入（开多）时价格+0.01，卖出（开空）时价格-0.01 + raw_price = float(next_bar['open']) + entry_price = adjust_price_for_trade(raw_price, direction, symbol) current_position = { 'direction': direction, 'signal': stats[signal_key]['name'], @@ -192,7 +245,7 @@ def backtest_15m_trend_optimized(dates: List[str]): } consecutive_opposite_count = 0 # 重置连续反色计数 stats[signal_key]['count'] += 1 - logger.debug(f"开仓: {stats[signal_key]['name']} {'做多' if direction == 'long' else '做空'} @ {entry_price:.2f}") + logger.debug(f"开仓: {stats[signal_key]['name']} {'做多' if direction == 'long' else '做空'} @ {entry_price:.2f} (原始价格: {raw_price:.2f})") idx += 1 continue @@ -203,7 +256,11 @@ def backtest_15m_trend_optimized(dates: List[str]): # 1. 反向信号 -> 下一根K线开盘价平仓并反手开仓 # 策略：遇到反向信号（如持有多单时遇到阴包阳），平仓并反手开仓 if direction and direction != pos_dir: - exit_price = float(next_bar['open']) + # 平仓：持有多单时卖出（价格-0.01），持有空单时买入（价格+0.01） + raw_exit_price = float(next_bar['open']) + exit_direction = 'short' if pos_dir == 'long' else 'long' # 平仓方向与持仓方向相反 + exit_price = adjust_price_for_trade(raw_exit_price, exit_direction, symbol) + diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else ( current_position['entry_price'] - exit_price) trades.append({ @@ -218,17 +275,19 @@ def backtest_15m_trend_optimized(dates: List[str]): stats[pos_sig_key]['total_profit'] += diff if diff > 0: stats[pos_sig_key]['wins'] += 1 - # 反手开仓（下一根K线开盘价） + # 反手开仓（下一根K线开盘价，应用买卖价差） + raw_entry_price = float(next_bar['open']) + entry_price = adjust_price_for_trade(raw_entry_price, direction, symbol) current_position = { 'direction': direction, 'signal': stats[signal_key]['name'], 'signal_key': signal_key, - 'entry_price': exit_price, + 'entry_price': entry_price, 'entry_time': next_bar['id'] } consecutive_opposite_count = 0 # 重置连续反色计数 stats[signal_key]['count'] += 1 - logger.debug(f"反向信号反手: 平{'做多' if pos_dir == 'long' else '做空'} @ {exit_price:.2f}, 开{'做多' if direction == 'long' else '做空'}") + logger.debug(f"反向信号反手: 平{'做多' if pos_dir == 'long' else '做空'} @ {exit_price:.2f} (原始: {raw_exit_price:.2f}), 开{'做多' if direction == 'long' else '做空'} @ {entry_price:.2f} (原始: {raw_entry_price:.2f})") idx += 1 continue @@ -240,7 +299,9 @@ def backtest_15m_trend_optimized(dates: List[str]): # 如果已经连续两根阴线，下一根K线开盘价平仓 if consecutive_opposite_count >= 2: logger.debug(f"平仓: 做多遇到连续两根阴线") - exit_price = float(next_bar['open']) + # 平多单：卖出，价格 - 0.01 + raw_exit_price = float(next_bar['open']) + exit_price = adjust_price_for_trade(raw_exit_price, 'short', symbol) diff = exit_price - current_position['entry_price'] trades.append({ 'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000), @@ -268,7 +329,9 @@ def backtest_15m_trend_optimized(dates: List[str]): # 如果已经连续两根阳线，下一根K线开盘价平仓 if consecutive_opposite_count >= 2: logger.debug(f"平仓: 做空遇到连续两根阳线") - exit_price = float(next_bar['open']) + # 平空单：买入，价格 + 0.01 + raw_exit_price = float(next_bar['open']) + exit_price = adjust_price_for_trade(raw_exit_price, 'long', symbol) diff = current_position['entry_price'] - exit_price trades.append({ 'entry_time': datetime.datetime.fromtimestamp(current_position['entry_time'] / 1000), @@ -305,8 +368,12 @@ def backtest_15m_trend_optimized(dates: List[str]): # 尾仓：最后一根收盘价平仓 if current_position: last = all_data[-1] - exit_price = float(last['close']) pos_dir = current_position['direction'] + # 平仓：持有多单时卖出（价格-0.01），持有空单时买入（价格+0.01） + raw_exit_price = float(last['close']) + exit_direction = 'short' if pos_dir == 'long' else 'long' # 平仓方向与持仓方向相反 + exit_price = adjust_price_for_trade(raw_exit_price, exit_direction, symbol) + diff = (exit_price - current_position['entry_price']) if pos_dir == 'long' else ( current_position['entry_price'] - exit_price) trades.append({ @@ -346,7 +413,9 @@ if __name__ == '__main__': print(dates) # dates = [f"2025-09-{i}" for i in range(1, 32)] - trades, stats = backtest_15m_trend_optimized(dates) + # 指定交易对符号，用于获取正确的最小价格单位 + symbol = 'SOLUSDT' + trades, stats = backtest_15m_trend_optimized(dates, symbol=symbol) logger.info("===== 每笔交易详情 =====")