support quant by A market

config.py

@@ -134,6 +134,43 @@ US_STOCK_MONITOR_CONFIG = {
     }
 }
 
+A_STOCK_MONITOR_CONFIG = {
+    "volume_monitor": {
+        "symbols": [
+            "600276.SH",
+            "002714.SZ",
+            "600111.SH",
+            "603019.SH",
+            "600036.SH",
+            "300474.SZ",
+            "600519.SH",
+            "300750.SZ",
+            "000858.SZ",
+            "000651.SZ",
+            "000333.SZ",
+            "002230.SZ",
+            "300308.SZ",
+            "002475.SZ"
+        ],
+        "bars": ["1D", "1W", "1M"],
+        "initial_date": "2015-01-01 00:00:00",
+    },
+}
+
+A_INDEX_MONITOR_CONFIG = {
+    "volume_monitor": {
+        "symbols": [
+            "000001.SH",
+            "399006.SZ",
+            "000300.SH",
+            "399001.SZ",
+            "000852.SH",
+        ],
+        "bars": ["1D", "1W", "1M"],
+        "initial_date": "2015-01-01 00:00:00",
+    },
+}
+
 WINDOW_SIZE = {"window_sizes": [50, 80, 100, 120]}
 
 BAR_THRESHOLD = {
@@ -146,7 +183,7 @@ BAR_THRESHOLD = {
     "1D": 1000 * 60 * 60 * 24,
 }
 
-# MYSQL_CONFIG = {
+# COIN_MYSQL_CONFIG = {
 #     "host": "localhost",
 #     "port": 3306,
 #     "user": "xch",
@@ -154,7 +191,7 @@ BAR_THRESHOLD = {
 #     "database": "okx",
 # }
 
-MYSQL_CONFIG = {
+COIN_MYSQL_CONFIG = {
     "host": "218.17.89.43",
     "port": 11013,
     "user": "xch",
@@ -162,6 +199,14 @@ MYSQL_CONFIG = {
     "database": "okx",
 }
 
+A_MYSQL_CONFIG = {
+    "host": "43.139.95.249",
+    "port": 3306,
+    "user": "root",
+    "password": "bengbu_200!",
+    "database": "astock",
+}
+
 WECHAT_CONFIG = {
     "general_key": "11e6f7ac-efa9-418a-904c-9325a9f5d324",
     "btc_key": "529e135d-843b-43dc-8aca-677a860f4b4b",

core/db/db_astock.py

@@ -0,0 +1,125 @@
+import pandas as pd
+from sqlalchemy import create_engine, exc, text
+import re
+from core.utils import get_current_date_time
+import core.logger as logging
+from core.utils import transform_data_type
+
+logger = logging.logger
+
+
+class DBAStockData:
+    def __init__(
+        self,
+        db_url: str,
+    ):
+        self.db_url = db_url
+        self.db_engine = create_engine(
+            self.db_url,
+            pool_size=25,  # 连接池大小
+            max_overflow=10,  # 允许的最大溢出连接
+            pool_timeout=30,  # 连接超时时间（秒）
+            pool_recycle=60,  # 连接回收时间（秒），避免长时间闲置
+        )
+
+    def query_data(self, sql: str, condition_dict: dict, return_multi: bool = True):
+        """
+        查询数据
+        :param sql: 查询SQL
+        :param db_url: 数据库连接URL
+        """
+        try:
+            with self.db_engine.connect() as conn:
+                result = conn.execute(text(sql), condition_dict)
+                if return_multi:
+                    result = result.fetchall()
+                    if result:
+                        result_list = [
+                            transform_data_type(dict(row._mapping)) for row in result
+                        ]
+                        return result_list
+                    else:
+                        return None
+                else:
+                    result = result.fetchone()
+                    if result:
+                        result_dict = transform_data_type(dict(result._mapping))
+                        return result_dict
+                    else:
+                        return None
+        except Exception as e:
+            logger.error(f"查询数据出错: {e}")
+            return None
+
+    def query_market_data_by_symbol_bar(
+        self,
+        symbol: str,
+        bar: str,
+        fields: list = None,
+        start: str = None,
+        end: str = None,
+        table_name: str = "index_daily_price_from_2021",
+    ):
+        """
+        根据交易对和K线周期查询数据
+        :param symbol: 交易对
+        :param bar: K线周期
+        :param fields: 字段列表
+        :param start: 开始时间
+        :param end: 结束时间
+        """
+        if fields is None:
+            fields = ["*"]
+        fields_str = ", ".join(fields)
+        if table_name is None:
+            table_name = "index_daily_price_from_2021"
+            join_table = "all_index"
+        if table_name.startswith("index"):
+            join_table = "all_index"
+        else:
+            join_table = "all_stock"
+
+        if start is None and end is None:
+            sql = f"""
+                SELECT {fields_str} FROM {table_name} a
+                INNER JOIN {join_table} b ON a.ts_code = b.ts_code
+                WHERE a.ts_code = :symbol
+                ORDER BY a.trade_date ASC
+                """
+            condition_dict = {"symbol": symbol}
+        else:
+            if start is not None and end is not None:
+                start = start.replace("-", "")
+                end = end.replace("-", "")
+                if start > end:
+                    start, end = end, start
+                sql = f"""
+                    SELECT {fields_str} FROM {table_name} a
+                    INNER JOIN {join_table} b ON a.ts_code = b.ts_code
+                    WHERE a.ts_code = :symbol AND a.trade_date BETWEEN :start AND :end
+                    ORDER BY a.trade_date ASC
+                    """
+                condition_dict = {
+                    "symbol": symbol,
+                    "start": start,
+                    "end": end,
+                }
+            elif start is not None:
+                start = start.replace("-", "")
+                sql = f"""
+                    SELECT {fields_str} FROM {table_name} a
+                    INNER JOIN {join_table} b ON a.ts_code = b.ts_code
+                    WHERE a.ts_code = :symbol AND a.trade_date >= :start
+                    ORDER BY a.trade_date ASC
+                    """
+                condition_dict = {"symbol": symbol, "start": start}
+            elif end is not None:
+                end = end.replace("-", "")
+                sql = f"""
+                    SELECT {fields_str} FROM {table_name} a
+                    INNER JOIN {join_table} b ON a.ts_code = b.ts_code
+                    WHERE a.ts_code = :symbol AND a.trade_date <= :end
+                    ORDER BY a.trade_date ASC
+                    """
+                condition_dict = {"symbol": symbol, "end": end}
+        return self.query_data(sql, condition_dict, return_multi=True)

core/db/db_binance_data.py

@@ -480,6 +480,7 @@ class DBBinanceData:
         fields: list = None,
         start: str = None,
         end: str = None,
+        table_name: str = "crypto_binance_data",
     ):
         """
         根据交易对和K线周期查询数据
@@ -494,7 +495,7 @@ class DBBinanceData:
         fields_str = ", ".join(fields)
         if start is None and end is None:
             sql = f"""
-                SELECT {fields_str} FROM crypto_binance_data
+                SELECT {fields_str} FROM {table_name}
                 WHERE symbol = :symbol AND bar = :bar
                 ORDER BY timestamp ASC
                 """
@@ -514,7 +515,7 @@ class DBBinanceData:
                 if start > end:
                     start, end = end, start
                 sql = f"""
-                    SELECT {fields_str} FROM crypto_binance_data
+                    SELECT {fields_str} FROM {table_name}
                     WHERE symbol = :symbol AND bar = :bar AND timestamp BETWEEN :start AND :end
                     ORDER BY timestamp ASC
                     """
@@ -526,14 +527,14 @@ class DBBinanceData:
                 }
             elif start is not None:
                 sql = f"""
-                    SELECT {fields_str} FROM crypto_binance_data
+                    SELECT {fields_str} FROM {table_name}
                     WHERE symbol = :symbol AND bar = :bar AND timestamp >= :start
                     ORDER BY timestamp ASC
                     """
                 condition_dict = {"symbol": symbol, "bar": bar, "start": start}
             elif end is not None:
                 sql = f"""
-                    SELECT {fields_str} FROM crypto_binance_data
+                    SELECT {fields_str} FROM {table_name}
                     WHERE symbol = :symbol AND bar = :bar AND timestamp <= :end
                     ORDER BY timestamp ASC
                     """

core/db/db_market_data.py

@@ -7,10 +7,7 @@ logger = logging.logger
 
 
 class DBMarketData:
-    def __init__(
+    def __init__(self, db_url: str):
-        self, 
-        db_url: str
-    ):
         self.db_url = db_url
         self.table_name = "crypto_market_data"
         self.columns = [
@@ -143,7 +140,9 @@ class DBMarketData:
         condition_dict = {"symbol": symbol, "bar": bar}
         return self.db_manager.query_data(sql, condition_dict, return_multi=False)
 
-    def query_data_before_timestamp(self, symbol: str, bar: str, timestamp: int, limit: int = 100):
+    def query_data_before_timestamp(
+        self, symbol: str, bar: str, timestamp: int, limit: int = 100
+    ):
         """
         根据时间戳查询之前的数据
         :param symbol: 交易对
@@ -157,7 +156,12 @@ class DBMarketData:
         ORDER BY timestamp DESC
         LIMIT :limit
         """
-        condition_dict = {"symbol": symbol, "bar": bar, "timestamp": timestamp, "limit": limit}
+        condition_dict = {
+            "symbol": symbol,
+            "bar": bar,
+            "timestamp": timestamp,
+            "limit": limit,
+        }
         return self.db_manager.query_data(sql, condition_dict, return_multi=True)
 
     def query_data_by_technical_indicators(
@@ -170,7 +174,7 @@ class DBMarketData:
         kdj_signal: str = None,
         rsi_signal: str = None,
         boll_signal: str = None,
-        ma_cross: str = None
+        ma_cross: str = None,
     ):
         """
         根据技术指标查询数据
@@ -230,7 +234,7 @@ class DBMarketData:
         bar: str,
         signal: str = None,
         start: str = None,
-        end: str = None
+        end: str = None,
     ):
         """
         查询MACD信号数据
@@ -275,7 +279,7 @@ class DBMarketData:
         signal: str = None,
         pattern: str = None,
         start: str = None,
-        end: str = None
+        end: str = None,
     ):
         """
         查询KDJ信号数据
@@ -325,7 +329,7 @@ class DBMarketData:
         long_short: str = None,
         divergence: str = None,
         start: str = None,
-        end: str = None
+        end: str = None,
     ):
         """
         查询均线信号数据
@@ -378,7 +382,7 @@ class DBMarketData:
         signal: str = None,
         pattern: str = None,
         start: str = None,
-        end: str = None
+        end: str = None,
     ):
         """
         查询布林带信号数据
@@ -421,11 +425,7 @@ class DBMarketData:
         return self.db_manager.query_data(sql, condition_dict, return_multi=True)
 
     def get_technical_statistics(
-        self, 
+        self, symbol: str, bar: str, start: str = None, end: str = None
-        symbol: str, 
-        bar: str, 
-        start: str = None, 
-        end: str = None
     ):
         """
         获取技术指标统计信息
@@ -473,7 +473,15 @@ class DBMarketData:
 
         return self.db_manager.query_data(sql, condition_dict, return_multi=False)
 
-    def query_market_data_by_symbol_bar(self, symbol: str, bar: str, fields: list = None, start: str = None, end: str = None):
+    def query_market_data_by_symbol_bar(
+        self,
+        symbol: str,
+        bar: str,
+        fields: list = None,
+        start: str = None,
+        end: str = None,
+        table_name: str = "crypto_market_data",
+    ):
         """
         根据交易对和K线周期查询数据
         :param symbol: 交易对
@@ -487,7 +495,7 @@ class DBMarketData:
         fields_str = ", ".join(fields)
         if start is None and end is None:
             sql = f"""
-                SELECT {fields_str} FROM crypto_market_data
+                SELECT {fields_str} FROM {table_name}
                 WHERE symbol = :symbol AND bar = :bar
                 ORDER BY timestamp ASC
                 """
@@ -507,21 +515,26 @@ class DBMarketData:
                 if start > end:
                     start, end = end, start
                 sql = f"""
-                    SELECT {fields_str} FROM crypto_market_data
+                    SELECT {fields_str} FROM {table_name}
                     WHERE symbol = :symbol AND bar = :bar AND timestamp BETWEEN :start AND :end
                     ORDER BY timestamp ASC
                     """
-                condition_dict = {"symbol": symbol, "bar": bar, "start": start, "end": end}
+                condition_dict = {
+                    "symbol": symbol,
+                    "bar": bar,
+                    "start": start,
+                    "end": end,
+                }
             elif start is not None:
                 sql = f"""
-                    SELECT {fields_str} FROM crypto_market_data
+                    SELECT {fields_str} FROM {table_name}
                     WHERE symbol = :symbol AND bar = :bar AND timestamp >= :start
                     ORDER BY timestamp ASC
                     """
                 condition_dict = {"symbol": symbol, "bar": bar, "start": start}
             elif end is not None:
                 sql = f"""
-                    SELECT {fields_str} FROM crypto_market_data
+                    SELECT {fields_str} FROM {table_name}
                     WHERE symbol = :symbol AND bar = :bar AND timestamp <= :end
                     ORDER BY timestamp ASC
                     """

core/statistics/price_volume_stats.py

@@ -12,7 +12,7 @@ from openpyxl.drawing.image import Image
 import openpyxl
 from openpyxl.styles import Font
 from PIL import Image as PILImage
-from config import OKX_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE
+from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
 from core.db.db_market_data import DBMarketData
 from core.db.db_huge_volume_data import DBHugeVolumeData
 from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
@@ -25,13 +25,13 @@ logger = logging.logger
 
 class PriceVolumeStats:
     def __init__(self):
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
         self.db_market_data = DBMarketData(self.db_url)

core/trade/ma_break_statistics.py

@@ -17,11 +17,16 @@ from PIL import Image as PILImage
 from config import (
     OKX_MONITOR_CONFIG,
     US_STOCK_MONITOR_CONFIG,
-    MYSQL_CONFIG,
+    COIN_MYSQL_CONFIG,
+    A_MYSQL_CONFIG,
     WINDOW_SIZE,
     BINANCE_MONITOR_CONFIG,
+    A_STOCK_MONITOR_CONFIG,
+    A_INDEX_MONITOR_CONFIG,
 )
+from core.biz.metrics_calculation import MetricsCalculation
 from core.db.db_market_data import DBMarketData
+from core.db.db_astock import DBAStockData
 from core.db.db_binance_data import DBBinanceData
 from core.db.db_huge_volume_data import DBHugeVolumeData
 from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
@@ -44,21 +49,40 @@ class MaBreakStatistics:
     def __init__(
         self,
         is_us_stock: bool = False,
-        is_binance: bool = False,
+        is_astock: bool = False,
+        is_aindex: bool = False,
+        is_binance: bool = True,
+        buy_by_long_period: dict = {"by_week": False, "by_month": False},
+        long_period_condition: dict = {"ma5>ma10": True, "ma10>ma20": False, "macd_diff>0": True, "macd>0": True},
         commission_per_share: float = 0.0008,
     ):
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        if is_astock or is_aindex:
-        mysql_password = MYSQL_CONFIG.get("password", "")
+            mysql_user = A_MYSQL_CONFIG.get("user", "root")
+            mysql_password = A_MYSQL_CONFIG.get("password", "")
             if not mysql_password:
                 raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+            mysql_host = A_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+            mysql_port = A_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+            mysql_database = A_MYSQL_CONFIG.get("database", "astock")
+        else:
+            mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
+            mysql_password = COIN_MYSQL_CONFIG.get("password", "")
+            if not mysql_password:
+                raise ValueError("MySQL password is not set")
+            mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
+            mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
+            mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
 
         self.db_huge_volume_data = DBHugeVolumeData(self.db_url)
         self.is_us_stock = is_us_stock
+        self.is_astock = is_astock
+        self.is_aindex = is_aindex
+        if self.is_us_stock:
+            self.date_time_field = "date_time_us"
+        else:
+            self.date_time_field = "date_time"
         self.is_binance = is_binance
         if is_us_stock:
             self.symbols = US_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
@@ -71,6 +95,28 @@ class MaBreakStatistics:
                 "initial_date", "2014-11-30 00:00:00"
             )
             self.db_market_data = DBMarketData(self.db_url)
+        elif is_astock:
+            self.symbols = A_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
+                "symbols", ["000001.SH"]
+            )
+            self.bars = A_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
+                "bars", ["5m"]
+            )
+            self.initial_date = A_STOCK_MONITOR_CONFIG.get("volume_monitor", {}).get(
+                "initial_date", "2014-11-30 00:00:00"
+            )
+            self.db_market_data = DBAStockData(self.db_url)
+        elif is_aindex:
+            self.symbols = A_INDEX_MONITOR_CONFIG.get("volume_monitor", {}).get(
+                "symbols", ["000001.SH"]
+            )
+            self.bars = A_INDEX_MONITOR_CONFIG.get("volume_monitor", {}).get(
+                "bars", ["5m"]
+            )
+            self.initial_date = A_INDEX_MONITOR_CONFIG.get("volume_monitor", {}).get(
+                "initial_date", "2014-11-30 00:00:00"
+            )
+            self.db_market_data = DBAStockData(self.db_url)
         else:
             if is_binance:
                 self.symbols = BINANCE_MONITOR_CONFIG.get("volume_monitor", {}).get(
@@ -98,12 +144,36 @@ class MaBreakStatistics:
         self.commission_per_share = commission_per_share
         self.trade_strategy_config = self.get_trade_strategy_config()
         self.main_strategy = self.trade_strategy_config.get("均线系统策略", None)
+        self.buy_by_long_period = buy_by_long_period
+        self.long_period_condition = long_period_condition
 
     def get_trade_strategy_config(self):
         with open("./json/trade_strategy.json", "r", encoding="utf-8") as f:
             trade_strategy_config = json.load(f)
         return trade_strategy_config
 
+    def get_by_long_period_desc(self):
+        by_week = self.buy_by_long_period.get("by_week", False)
+        by_month = self.buy_by_long_period.get("by_month", False)
+        by_long_period = ""
+        if by_week:
+            by_long_period += "1W"
+        if by_month:
+            by_long_period += "1M"
+        if by_long_period == "":
+            return "no_long_period_judge"
+        by_condition = ""
+        if self.long_period_condition.get("ma5>ma10", False):
+            by_condition += "ma5gtma10"
+        if self.long_period_condition.get("ma10>ma20", False):
+            by_condition += "_ma10gtma20"
+        if self.long_period_condition.get("macd_diff>0", False):
+            by_condition += "_macd_diffgt0"
+        if self.long_period_condition.get("macd>0", False):
+            by_condition += "_macdgt0"
+        return by_long_period + "_" + by_condition
+        
+
     def batch_statistics(self, strategy_name: str = "全均线策略"):
         if self.is_us_stock:
             self.stats_output_dir = (
@@ -119,6 +189,38 @@ class MaBreakStatistics:
             self.stats_chart_dir = (
                 f"./output/trade_sandbox/ma_strategy/binance/chart/{strategy_name}/"
             )
+        elif self.is_astock:
+            long_period_desc = self.get_by_long_period_desc()
+            if len(long_period_desc) > 0:
+                self.stats_output_dir = (
+                    f"./output/trade_sandbox/ma_strategy/astock/{long_period_desc}/excel/{strategy_name}/"
+                )
+                self.stats_chart_dir = (
+                    f"./output/trade_sandbox/ma_strategy/astock/{long_period_desc}/chart/{strategy_name}/"
+                )
+            else:
+                self.stats_output_dir = (
+                    f"./output/trade_sandbox/ma_strategy/astock/excel/{strategy_name}/"
+                )
+                self.stats_chart_dir = (
+                    f"./output/trade_sandbox/ma_strategy/astock/chart/{strategy_name}/"
+                )
+        elif self.is_aindex:
+            long_period_desc = self.get_by_long_period_desc()
+            if len(long_period_desc) > 0:
+                self.stats_output_dir = (
+                    f"./output/trade_sandbox/ma_strategy/aindex/{long_period_desc}/excel/{strategy_name}/"
+                )
+                self.stats_chart_dir = (
+                    f"./output/trade_sandbox/ma_strategy/aindex/{long_period_desc}/chart/{strategy_name}/"
+                )
+            else:
+                self.stats_output_dir = (
+                    f"./output/trade_sandbox/ma_strategy/aindex/excel/{strategy_name}/"
+                )
+                self.stats_chart_dir = (
+                    f"./output/trade_sandbox/ma_strategy/aindex/chart/{strategy_name}/"
+                )
         else:
             self.stats_output_dir = (
                 f"./output/trade_sandbox/ma_strategy/okx/excel/{strategy_name}/"
@@ -192,9 +294,11 @@ class MaBreakStatistics:
                         total_commission = round(total_commission, 4)
                         total_buy_commission = round(total_buy_commission, 4)
                         total_sell_commission = round(total_sell_commission, 4)
+                        symbol_name = str(symbol_bar_data["symbol_name"].iloc[0])
                         account_value_chg_list.append({
                             "strategy_name": strategy_name,
                             "symbol": symbol,
+                            "symbol_name": symbol_name,
                             "bar": bar,
                             "total_buy_commission": total_buy_commission,
                             "total_sell_commission": total_sell_commission,
@@ -209,6 +313,7 @@ class MaBreakStatistics:
                 [
                     "strategy_name",
                     "symbol",
+                    "symbol_name",
                     "bar",
                     "total_buy_commission",
                     "total_sell_commission",
@@ -221,7 +326,7 @@ class MaBreakStatistics:
             ]
 
             account_value_statistics_df = (
-                ma_break_market_data.groupby(["symbol", "bar"])["end_account_value"]
+                ma_break_market_data.groupby(["symbol", "symbol_name", "bar"])["end_account_value"]
                 .agg(
                     account_value_max="max",
                     account_value_min="min",
@@ -237,6 +342,7 @@ class MaBreakStatistics:
                 [
                     "strategy_name",
                     "symbol",
+                    "symbol_name",
                     "bar",
                     "account_value_max",
                     "account_value_min",
@@ -249,7 +355,7 @@ class MaBreakStatistics:
 
             # 依据symbol和bar分组，统计每个symbol和bar的interval_minutes的max, min, mean, std, median, count
             interval_minutes_df = (
-                ma_break_market_data.groupby(["symbol", "bar"])["interval_minutes"]
+                ma_break_market_data.groupby(["symbol", "symbol_name", "bar"])["interval_minutes"]
                 .agg(
                     interval_minutes_max="max",
                     interval_minutes_min="min",
@@ -265,6 +371,7 @@ class MaBreakStatistics:
                 [
                     "strategy_name",
                     "symbol",
+                    "symbol_name",
                     "bar",
                     "interval_minutes_max",
                     "interval_minutes_min",
@@ -335,6 +442,23 @@ class MaBreakStatistics:
             strategy_info["买入策略"] = buy_and_text + " 或者 \n" + buy_or_text
         else:
             strategy_info["买入策略"] = buy_and_text
+        
+        # 假如根据长周期判断买入，则需要设置长周期策略
+        by_week = self.buy_by_long_period.get("by_week", False)
+        by_month = self.buy_by_long_period.get("by_month", False)
+        if by_week:
+            strategy_info["买入策略"] += "根据周线指标，\n"
+        if by_month:
+            strategy_info["买入策略"] += "根据月线指标，\n"
+        if self.long_period_condition.get("ma5>ma10", False):
+            strategy_info["买入策略"] += "ma5>ma10, \n"
+        if self.long_period_condition.get("ma10>ma20", False):
+            strategy_info["买入策略"] += "ma10>ma20, \n"
+        if self.long_period_condition.get("macd_diff>0", False):
+            strategy_info["买入策略"] += "macd_diff>0, \n"
+        if self.long_period_condition.get("macd>0", False):
+            strategy_info["买入策略"] += "macd>0, \n"
+        strategy_info["买入策略"] = strategy_info["买入策略"].strip()
         sell_dict = strategy_config.get("sell", {})
         sell_and_list = sell_dict.get("and", [])
         sell_or_list = sell_dict.get("or", [])
@@ -349,6 +473,7 @@ class MaBreakStatistics:
             strategy_info["卖出策略"] = sell_and_text + " 或者 \n" + sell_or_text
         else:
             strategy_info["卖出策略"] = sell_and_text
+        strategy_info["卖出策略"] = strategy_info["卖出策略"].strip()
         # 将strategy_info转换为pd.DataFrame
         strategy_info_df = pd.DataFrame([strategy_info])
         return strategy_info_df
@@ -384,22 +509,24 @@ class MaBreakStatistics:
             market_data.reset_index(drop=True, inplace=True)
             ma_break_market_data_pair_list = []
             ma_break_market_data_pair = {}
-            if self.is_us_stock:
-                date_time_field = "date_time_us"
-            else:
-                date_time_field = "date_time"
             close_mean = market_data["close"].mean()
             self.update_initial_capital(close_mean)
             logger.info(
-                f"成功获取{symbol}数据：{len(market_data)}根{bar}K线,开始日期={market_data[date_time_field].min()}，结束日期={market_data[date_time_field].max()}"
+                f"成功获取{symbol}数据：{len(market_data)}根{bar}K线,开始日期={market_data[self.date_time_field].min()}，结束日期={market_data[self.date_time_field].max()}"
             )
 
             account_value = self.initial_capital
 
             for index, row in market_data.iterrows():
+                if self.is_astock:
+                    symbol_name = row["symbol_name"]
+                elif self.is_aindex:
+                    symbol_name = row["symbol_name"]
+                else:
+                    symbol_name = row["symbol"]
                 ma_cross = row["ma_cross"]
                 timestamp = row["timestamp"]
-                date_time = row[date_time_field]
+                date_time = row[self.date_time_field]
                 close = row["close"]
                 ma5 = row["ma5"]
                 ma10 = row["ma10"]
@@ -411,7 +538,6 @@ class MaBreakStatistics:
                 if ma_break_market_data_pair.get("begin_timestamp", None) is None:
                     buy_condition = self.fit_strategy(
                         strategy_name=strategy_name,
-                        market_data=market_data,
                         row=row,
                         behavior="buy",
                     )
@@ -431,6 +557,7 @@ class MaBreakStatistics:
 
                         ma_break_market_data_pair = {}
                         ma_break_market_data_pair["symbol"] = symbol
+                        ma_break_market_data_pair["symbol_name"] = symbol_name
                         ma_break_market_data_pair["bar"] = bar
                         ma_break_market_data_pair["begin_timestamp"] = timestamp
                         ma_break_market_data_pair["begin_date_time"] = date_time
@@ -449,12 +576,12 @@ class MaBreakStatistics:
                 else:
                     sell_condition = self.fit_strategy(
                         strategy_name=strategy_name,
-                        market_data=market_data,
                         row=row,
                         behavior="sell",
                     )
 
-                    if sell_condition:
+                    if sell_condition or index == len(market_data) - 1:
+                        # 达到卖出条件或者最后一条数据，则卖出
                         shares = ma_break_market_data_pair["shares"]
                         entry_price = ma_break_market_data_pair["begin_close"]
                         exit_price = close
@@ -525,8 +652,10 @@ class MaBreakStatistics:
                     * 100
                 )
                 pct_chg = round(pct_chg, 4)
+                symbol_name = ma_break_market_data["symbol_name"].iloc[0]
                 market_data_pct_chg = {
                     "symbol": symbol,
+                    "symbol_name": symbol_name,
                     "bar": bar,
                     "pct_chg": pct_chg,
                     "initial_capital": self.initial_capital,
@@ -604,6 +733,50 @@ class MaBreakStatistics:
         data = pd.DataFrame()
         start_date = datetime.strptime(self.initial_date, "%Y-%m-%d")
         end_date = datetime.strptime(self.end_date, "%Y-%m-%d") + timedelta(days=1)
+        table_name = ""
+        if self.is_astock:
+            if bar == "1D":
+                table_name = "stock_daily_price_from_2021"
+            elif bar == "1W":
+                table_name = "stock_weekly_price_from_2020"
+            elif bar == "1M":
+                table_name = "stock_monthly_price_from_2015"
+        elif self.is_aindex:
+            if bar == "1D":
+                table_name = "index_daily_price_from_2021"
+            elif bar == "1W":
+                table_name = "index_weekly_price_from_2020"
+            elif bar == "1M":
+                table_name = "index_monthly_price_from_2015"
+        elif self.is_us_stock:
+            table_name = "crypto_market_data"
+        elif self.is_binance:
+            table_name = "crypto_binance_data"
+        else:
+            table_name = "crypto_binance_data"
+
+        if self.is_astock or self.is_aindex:
+            fields = [
+                "a.ts_code as symbol",
+                "b.name as symbol_name",
+                f"'{bar}' as bar",
+                "0 as timestamp",
+                "trade_date as date_time",
+                "open",
+                "high",
+                "low",
+                "close",
+                "vol as volume",
+                "MA5 as ma5",
+                "MA10 as ma10",
+                "MA20 as ma20",
+                "MA30 as ma30",
+                "均线交叉 as ma_cross",
+                "DIF as dif",
+                "DEA as dea",
+                "MACD as macd",
+            ]
+        else:
             fields = [
                 "symbol",
                 "bar",
@@ -631,25 +804,120 @@ class MaBreakStatistics:
             current_end_date_str = current_end_date.strftime("%Y-%m-%d")
             logger.info(f"获取{symbol}数据：{start_date_str}至{current_end_date_str}")
             current_data = self.db_market_data.query_market_data_by_symbol_bar(
-                symbol, bar, fields, start=start_date_str, end=current_end_date_str
+                symbol, bar, fields, start=start_date_str, end=current_end_date_str, table_name=table_name
             )
             if current_data is not None and len(current_data) > 0:
                 current_data = pd.DataFrame(current_data)
                 data = pd.concat([data, current_data])
             start_date = current_end_date
         data.drop_duplicates(inplace=True)
-        if self.is_us_stock:
+        data.sort_values(by=self.date_time_field, inplace=True)
-            date_time_field = "date_time_us"
-        else:
-            date_time_field = "date_time"
-        data.sort_values(by=date_time_field, inplace=True)
         data.reset_index(drop=True, inplace=True)
+        if self.is_astock or self.is_aindex:
+            data = self.update_data(data)
         return data
     
+    def get_long_period_data(self, symbol: str, bar: str, end_date: str):
+        """
+        获取长周期数据
+        :param data: 数据
+        :return: 长周期数据
+        """
+        if not (self.is_astock or self.is_aindex):
+            return None
+        table_name = ""
+        if self.is_astock:
+            if bar == "1M":
+                table_name = "stock_monthly_price_from_2015"
+            elif bar == "1W":
+                table_name = "stock_weekly_price_from_2020"
+            else:
+                pass
+        elif self.is_aindex:
+            if bar == "1M":
+                table_name = "index_monthly_price_from_2015"
+            elif bar == "1W":
+                table_name = "index_weekly_price_from_2020"
+            else:
+                pass
+        if len(end_date) != 10:
+            end_date = self.change_date_format(end_date)
+        if bar == "1M":
+            # 获取上两个月的日期
+            last_date = datetime.strptime(end_date, "%Y-%m-%d") - timedelta(days=60)
+            last_date = last_date.strftime("%Y-%m-%d")
+        elif bar == "1W":
+            # 获取上两周的日期
+            last_date = datetime.strptime(end_date, "%Y-%m-%d") - timedelta(days=14)
+            last_date = last_date.strftime("%Y-%m-%d")
+        else:
+            last_date = None
+        
+        if len(table_name) == 0 or last_date is None:
+            return None
+        fields = [
+                "a.ts_code as symbol",
+                "b.name as symbol_name",
+                f"'{bar}' as bar",
+                "0 as timestamp",
+                "trade_date as date_time",
+                "open",
+                "high",
+                "low",
+                "close",
+                "vol as volume",
+                "MA5 as ma5",
+                "MA10 as ma10",
+                "MA20 as ma20",
+                "MA30 as ma30",
+                "均线交叉 as ma_cross",
+                "DIF as dif",
+                "DEA as dea",
+                "MACD as macd",
+            ]
+        data = self.db_market_data.query_market_data_by_symbol_bar(
+            symbol, bar, fields, start=last_date, end=end_date, table_name=table_name
+        )
+        if data is not None and len(data) > 0:
+            data = pd.DataFrame(data)
+            data.sort_values(by="date_time", inplace=True)
+            latest_row = data.iloc[-1]
+            if (latest_row["ma5"] is None or 
+            latest_row["ma10"] is None or 
+            latest_row["ma20"] is None or 
+            latest_row["dif"] is None or 
+            latest_row["macd"] is None):
+                return None
+            return latest_row
+        else:
+            return None
+
+    
+    def update_data(self, data: pd.DataFrame):
+        """
+        更新数据
+        1. 将date_time列中的20210104这种格式，替换为2021-01-04的格式
+        2. 将date_time转换为timestamp，并更新timestamp列
+        3. 通过MetricsCalculation的ma5102030方法更新ma_cross列
+        :param data: 数据
+        :return: 更新后的数据
+        """
+        data["date_time"] = data["date_time"].apply(lambda x: self.change_date_format(x))
+        data["timestamp"] = data["date_time"].apply(lambda x: transform_date_time_to_timestamp(x))
+        metrics_calculation = MetricsCalculation()
+        data = metrics_calculation.ma5102030(data)
+        return data
+    
+    def change_date_format(self, date_text: str):
+        # 将20210104这种格式，替换为2021-01-04的格式
+        if len(date_text) == 8:
+            return date_text[0:4] + "-" + date_text[4:6] + "-" + date_text[6:8]
+        else:
+            return date_text
+
     def fit_strategy(
         self,
         strategy_name: str = "全均线策略",
-        market_data: pd.DataFrame = None,
         row: pd.Series = None,
         behavior: str = "buy",
     ):
@@ -661,6 +929,45 @@ class MaBreakStatistics:
         if condition_dict is None:
             logger.error(f"策略{strategy_name}的{behavior}条件不存在")
             return False
+
+        and_list = condition_dict.get("and", [])
+
+        condition = True
+        condition = self.get_judge_result(row, and_list, "and", condition)
+        or_list = condition_dict.get("or", [])
+        condition = self.get_judge_result(row, or_list, "or", condition)
+
+        if behavior == "buy" and condition:
+            # 如果满足条件，则判断是否根据长周期指标买入
+            bar = row["bar"]
+            if (self.is_astock or self.is_aindex) and bar == "1D":
+                date_time = row["date_time"]
+                long_period_condition_list = []
+                if self.long_period_condition.get("ma5>ma10", False):
+                    long_period_condition_list.append("ma5>ma10")
+                if self.long_period_condition.get("ma10>ma20", False):
+                    long_period_condition_list.append("ma10>ma20")
+                if self.long_period_condition.get("macd_diff>0", False):
+                    long_period_condition_list.append("macd_diff>0")
+                if self.long_period_condition.get("macd>0", False):
+                    long_period_condition_list.append("macd>0")
+                if len(long_period_condition_list) > 0:
+                    if self.buy_by_long_period.get("by_week", False):
+                        long_period_data = self.get_long_period_data(row["symbol"], "1W", date_time)
+                        if long_period_data is not None:
+                            condition = self.get_judge_result(long_period_data, long_period_condition_list, "and", condition)
+                            if not condition:
+                                logger.info(f"根据周线指标，{row['symbol']}不满足买入条件")
+                    if self.buy_by_long_period.get("by_month", False):
+                        long_period_data = self.get_long_period_data(row["symbol"], "1M", date_time)
+                        if long_period_data is not None:
+                            condition = self.get_judge_result(long_period_data, long_period_condition_list, "and", condition)
+                            if not condition:
+                                logger.info(f"根据月线指标，{row['symbol']}不满足买入条件")
+
+        return condition
+    
+    def get_judge_result(self, row: pd.Series, condition_list: list, and_or: str = "and", raw_condition: bool = True):
         ma_cross = row["ma_cross"]
         if pd.isna(ma_cross) or ma_cross is None:
             ma_cross = ""
@@ -670,107 +977,107 @@ class MaBreakStatistics:
         ma20 = float(row["ma20"])
         ma30 = float(row["ma30"])
         close = float(row["close"])
+        if "volume_pct_chg" in list(row.index) and row["volume_pct_chg"] is not None:
             volume_pct_chg = float(row["volume_pct_chg"])
+        else:
+            volume_pct_chg = None
         macd_diff = float(row["dif"])
         macd_dea = float(row["dea"])
         macd = float(row["macd"])
-
+        if and_or == "and":
-        and_list = condition_dict.get("and", [])
+           for and_condition in condition_list:
-
-        condition = True
-        for and_condition in and_list:
             if and_condition == "5上穿10":
-                condition = condition and ("5上穿10" in ma_cross)
+                raw_condition = raw_condition and ("5上穿10" in ma_cross)
             elif and_condition == "10上穿20":
-                condition = condition and ("10上穿20" in ma_cross)
+                raw_condition = raw_condition and ("10上穿20" in ma_cross)
             elif and_condition == "20上穿30":
-                condition = condition and ("20上穿30" in ma_cross)
+                raw_condition = raw_condition and ("20上穿30" in ma_cross)
             elif and_condition == "ma5>ma10":
-                condition = condition and (ma5 > ma10)
+                raw_condition = raw_condition and (ma5 > ma10)
             elif and_condition == "ma10>ma20":
-                condition = condition and (ma10 > ma20)
+                raw_condition = raw_condition and (ma10 > ma20)
             elif and_condition == "ma20>ma30":
-                condition = condition and (ma20 > ma30)
+                raw_condition = raw_condition and (ma20 > ma30)
             elif and_condition == "close>ma20":
-                condition = condition and (close > ma20)
+                raw_condition = raw_condition and (close > ma20)
-            elif and_condition == "volume_pct_chg>0.2":
+            elif and_condition == "volume_pct_chg>0.2" and volume_pct_chg is not None:
-                condition = condition and (volume_pct_chg > 0.2)
+                raw_condition = raw_condition and (volume_pct_chg > 0.2)
             elif and_condition == "macd_diff>0":
-                condition = condition and (macd_diff > 0)
+                raw_condition = raw_condition and (macd_diff > 0)
             elif and_condition == "macd_dea>0":
-                condition = condition and (macd_dea > 0)
+                raw_condition = raw_condition and (macd_dea > 0)
             elif and_condition == "macd>0":
-                condition = condition and (macd > 0)
+                raw_condition = raw_condition and (macd > 0)
             elif and_condition == "10下穿5":
-                condition = condition and ("10下穿5" in ma_cross)
+                raw_condition = raw_condition and ("10下穿5" in ma_cross)
             elif and_condition == "20下穿10":
-                condition = condition and ("20下穿10" in ma_cross)
+                raw_condition = raw_condition and ("20下穿10" in ma_cross)
             elif and_condition == "30下穿20":
-                condition = condition and ("30下穿20" in ma_cross)
+                raw_condition = raw_condition and ("30下穿20" in ma_cross)
             elif and_condition == "ma5<ma10":
-                condition = condition and (ma5 < ma10)
+                raw_condition = raw_condition and (ma5 < ma10)
             elif and_condition == "ma10<ma20":
-                condition = condition and (ma10 < ma20)
+                raw_condition = raw_condition and (ma10 < ma20)
             elif and_condition == "ma20<ma30":
-                condition = condition and (ma20 < ma30)
+                raw_condition = raw_condition and (ma20 < ma30)
             elif and_condition == "close<ma20":
-                condition = condition and (close < ma20)
+                raw_condition = raw_condition and (close < ma20)
             elif and_condition == "macd_diff<0":
-                condition = condition and (macd_diff < 0)
+                raw_condition = raw_condition and (macd_diff < 0)
             elif and_condition == "macd_dea<0":
-                condition = condition and (macd_dea < 0)
+                raw_condition = raw_condition and (macd_dea < 0)
             elif and_condition == "macd<0":
-                condition = condition and (macd < 0)
+                raw_condition = raw_condition and (macd < 0)
             else:
                 pass
-        if not condition:
+        elif and_or == "or":
-            or_list = condition_dict.get("or", [])
+            for or_condition in condition_list:
-            for or_condition in or_list:
                 if or_condition == "5上穿10":
-                    condition = condition or ("5上穿10" in ma_cross)
+                    raw_condition = raw_condition or ("5上穿10" in ma_cross)
                 elif or_condition == "10上穿20":
-                    condition = condition or ("10上穿20" in ma_cross)
+                    raw_condition = raw_condition or ("10上穿20" in ma_cross)
                 elif or_condition == "20上穿30":
-                    condition = condition or ("20上穿30" in ma_cross)
+                    raw_condition = raw_condition or ("20上穿30" in ma_cross)
                 elif or_condition == "ma5>ma10":
-                    condition = condition or (ma5 > ma10)
+                    raw_condition = raw_condition or (ma5 > ma10)
                 elif or_condition == "ma10>ma20":
-                    condition = condition or (ma10 > ma20)
+                    raw_condition = raw_condition or (ma10 > ma20)
                 elif or_condition == "ma20>ma30":
-                    condition = condition or (ma20 > ma30)
+                    raw_condition = raw_condition or (ma20 > ma30)
                 elif or_condition == "close>ma20":
-                    condition = condition or (close > ma20)
+                    raw_condition = raw_condition or (close > ma20)
-                elif or_condition == "volume_pct_chg>0.2":
+                elif or_condition == "volume_pct_chg>0.2" and volume_pct_chg is not None:
-                    condition = condition or (volume_pct_chg > 0.2)
+                    raw_condition = raw_condition or (volume_pct_chg > 0.2)
                 elif or_condition == "macd_diff>0":
-                    condition = condition or (macd_diff > 0)
+                    raw_condition = raw_condition or (macd_diff > 0)
                 elif or_condition == "macd_dea>0":
-                    condition = condition or (macd_dea > 0)
+                    raw_condition = raw_condition or (macd_dea > 0)
                 elif or_condition == "macd>0":
-                    condition = condition or (macd > 0)
+                    raw_condition = raw_condition or (macd > 0)
                 elif or_condition == "10下穿5":
-                    condition = condition or ("10下穿5" in ma_cross)
+                    raw_condition = raw_condition or ("10下穿5" in ma_cross)
                 elif or_condition == "20下穿10":
-                    condition = condition or ("20下穿10" in ma_cross)
+                    raw_condition = raw_condition or ("20下穿10" in ma_cross)
                 elif or_condition == "30下穿20":
-                    condition = condition or ("30下穿20" in ma_cross)
+                    raw_condition = raw_condition or ("30下穿20" in ma_cross)
                 elif or_condition == "ma5<ma10":
-                    condition = condition or (ma5 < ma10)
+                    raw_condition = raw_condition or (ma5 < ma10)
                 elif or_condition == "ma10<ma20":
-                    condition = condition or (ma10 < ma20)
+                    raw_condition = raw_condition or (ma10 < ma20)
                 elif or_condition == "ma20<ma30":
-                    condition = condition or (ma20 < ma30)
+                    raw_condition = raw_condition or (ma20 < ma30)
                 elif or_condition == "close<ma20":
-                    condition = condition or (close < ma20)
+                    raw_condition = raw_condition or (close < ma20)
                 elif or_condition == "macd_diff<0":
-                    condition = condition or (macd_diff < 0)
+                    raw_condition = raw_condition or (macd_diff < 0)
                 elif or_condition == "macd_dea<0":
-                    condition = condition or (macd_dea < 0)
+                    raw_condition = raw_condition or (macd_dea < 0)
                 elif or_condition == "macd<0":
-                    condition = condition or (macd < 0)
+                    raw_condition = raw_condition or (macd < 0)
                 else:
                     pass
-        return condition
+        return raw_condition
+
 
     def draw_quant_pct_chg_bar_chart(
         self, data: pd.DataFrame, strategy_name: str = "全均线策略"
@@ -812,8 +1119,8 @@ class MaBreakStatistics:
                 width = 0.35  # 柱状图宽度
 
                 # 确保symbol列是字符串类型，避免matplotlib警告
-                bar_data["symbol"] = bar_data["symbol"].astype(str)
+                # bar_data["symbol"] = bar_data["symbol"].astype(str)
-
+                bar_data["symbol_name"] = bar_data["symbol_name"].astype(str)
                 # 绘制量化策略涨跌柱状图（蓝色渐变色）
                 bars1 = plt.bar(
                     x - width / 2,
@@ -840,7 +1147,7 @@ class MaBreakStatistics:
                 )
                 plt.xlabel("Symbol", fontsize=12)
                 plt.ylabel("涨跌幅(%)", fontsize=12)
-                plt.xticks(x, bar_data["symbol"], rotation=45, ha="right")
+                plt.xticks(x, bar_data["symbol_name"], rotation=45, ha="right")
                 plt.legend()
                 plt.grid(True, alpha=0.3)
 
@@ -907,13 +1214,13 @@ class MaBreakStatistics:
         :param strategy_name: 策略名称
         :return: None
         """
-        symbols = data["symbol"].unique()
+        symbols = data["symbol_name"].unique()
         bars = data["bar"].unique()
         chart_dict = {}
         for symbol in symbols:
             for bar in bars:
                 symbol_bar_data = data[
-                    (data["symbol"] == symbol) & (data["bar"] == bar)
+                    (data["symbol_name"] == symbol) & (data["bar"] == bar)
                 ]
                 if symbol_bar_data.empty:
                     continue
@@ -922,7 +1229,7 @@ class MaBreakStatistics:
                 first_row = symbol_bar_data.iloc[0].copy()
                 initial_capital = int(
                     market_data_pct_chg_df.loc[
-                        (market_data_pct_chg_df["symbol"] == symbol)
+                        (market_data_pct_chg_df["symbol_name"] == symbol)
                         & (market_data_pct_chg_df["bar"] == bar),
                         "initial_capital",
                     ].values[0]

core/trade/mean_reversion_sandbox.py

@@ -11,7 +11,7 @@ from openpyxl.drawing.image import Image
 import openpyxl
 from openpyxl.styles import Font
 from PIL import Image as PILImage
-from config import OKX_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE
+from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
 import core.logger as logging
 from core.db.db_merge_market_huge_volume import DBMergeMarketHugeVolume
 from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
@@ -24,13 +24,13 @@ logger = logging.logger
 
 class MeanReversionSandbox:
     def __init__(self, solution: str):
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
         self.db_merge_market_huge_volume = DBMergeMarketHugeVolume(self.db_url)

core/trade/orb_trade.py

@@ -12,7 +12,7 @@ from PIL import Image as PILImage
 from datetime import datetime, timedelta
 
 import core.logger as logging
-from config import OKX_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE
+from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
 from core.db.db_market_data import DBMarketData
 from core.db.db_binance_data import DBBinanceData
 from core.db.db_huge_volume_data import DBHugeVolumeData
@@ -92,13 +92,13 @@ class ORBStrategy:
         self.data = None  # 存储K线数据
         self.trades = []  # 存储交易记录
         self.equity_curve = None  # 存储账户净值曲线
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
         self.is_us_stock = is_us_stock
         self.is_binance = is_binance
 

doc/biz_code_file_brief.md

@@ -0,0 +1,62 @@
+- core/biz/huge_volume.py
+  - 作用: 放量(巨量)检测与后续涨跌统计的核心逻辑。
+  - 要点:
+    - 基于滑窗计算 volume_ma、volume_std、volume_threshold=均值+N倍标准差，生成 huge_volume、volume_ratio、spike_intensity。
+    - 可选价格分位检查：对 close/high/low 计算 80/20、90/10 分位并标注高低点命中位。
+    - next_periods_rise_or_fall: 以未来 N 周期涨跌结果做分组统计，输出明细与汇总。
+
+- core/biz/huge_volume_chart.py
+  - 作用: 将“巨量后走势统计”数据绘图（热力图/折线图）。
+  - 要点:
+    - 输入统计 DataFrame，支持是否包含热力图/折线图。
+    - 被 `huge_volume_main.plot_huge_volume_data` 调用，输出到 `./output/huge_volume_statistics/`。
+
+- core/biz/market_data.py
+  - 作用: 行情获取统一封装（OKX 为主，Linux 环境下支持 Binance，且支持美股模式）。
+  - 要点:
+    - get_realtime_kline_data / get_historical_kline_data：统一返回 DataFrame，含 `timestamp/date_time/date_time_us/symbol/bar/...`，自动数值化与排序。
+    - 历史数据分页向后抓取，含时间边界、去重与交易时段过滤（美股）。
+    - 提供 `get_realtime_candlesticks_from_binance/okx` 与基本 trade 聚合辅助（buy_sz/sell_sz 预留）。
+
+- core/biz/market_data_from_itick.py
+  - 作用: 从 iTick 等源拉取美股K线（供 `market_data_from_itick_main.py` 使用）。
+  - 要点:
+    - 封装美股数据下载，适配 `MarketData` 历史数据流程，统一列结构。
+
+- core/biz/market_monitor.py
+  - 作用: 实时监控报表生成（面向企业微信推送的Markdown文案）。
+  - 要点:
+    - create_metrics_report: 基于一根最新K线及全量数据，汇总价量、分位、MACD/KDJ/RSI/BOLL、均线多空/发散等信号，生成可读文本。
+    - get_last_huge_volume_record: 最近一次巨量回溯与十周期内巨量次数。
+    - get_long_short_over_buy_sell: 跨周期或对标BTC的多空/超买超卖对比说明。
+    - 依赖 `METRICS_CONFIG` 的权重与阈值映射。
+
+- core/biz/metrics_calculation.py
+  - 作用: 技术指标与形态计算的总入口。
+  - 要点:
+    - 指标: pre_close/pct_chg、MACD(含金叉死叉)、KDJ(K/D/J+信号)、RSI、BOLL(上下轨与形态)、SAR(多/空/观望)。
+    - 均线: ma5/10/20/30、交叉组合信号、价格-均线相对百分比、`ma_long_short`（多/空/震荡）与 `ma_divergence`（发散/粘合等），提供多策略判定：weighted_voting/trend_strength/ma_alignment/statistical/hybrid。
+    - K线形态: k_length（短/中/长/超长）、k_shape（吊锤线、倒T、十字星、超大实体、光头光脚等），基于统计分布和Z-score自适应阈值。
+    - MACD 背离: 标准版与滑窗版两套检测。
+
+- core/biz/quant_trader.py
+  - 作用: OKX 交易封装（账户、下单、行情、公共数据）。
+  - 要点:
+    - 余额查询（USDT/现货币/合约）、当前价格、K线拉取。
+    - 现货市价单买卖；合约侧设置杠杆、开空(卖出)与平空(买入)流程。
+    - 计算合约所需保证金与推荐保证金（含缓冲比例）。
+
+- core/biz/strategy.py
+  - 作用: 策略抽象/占位（被 `trade_main.py` 中的 `QuantStrategy` 引用）。
+  - 要点:
+    - 用于承载策略接口或具体策略实现（与 `quant_trader` 协作下单）。
+
+- core/biz/trade_data.py
+  - 作用: 交易明细获取与存储封装（供 `TradeDataMain` 使用）。
+  - 要点:
+    - 负责对接交易API、落库与查询，支持按时间段增量补齐。
+
+- core/biz/market_data_from_itick.py（若存在）
+  - 作用: iTick 美股数据源适配器。
+  - 要点:
+    - 输出结构与 OKX/Binance 对齐，便于统一后续指标/巨量检测流程。

doc/main_code_file_brief.md

@@ -0,0 +1,78 @@
+- market_monitor_main.py
+  - 功能: 实时监控市场K线（优先OKX，Linux下可切换Binance），计算技术指标与巨量信号，生成监控报告并推送企业微信。
+  - 要点:
+    - 直接API拉取最近K线，不访问DB以保证速度。
+    - 固定滑窗window_size=100，实时判定huge_volume与价格分位异常。
+    - 通过最新时间戳与本地记录去重，避免重复推送。
+    - 支持过滤条件：仅巨量、仅超过均量、仅上涨。
+    - 依赖 Wechat 推送、DBMarketMonitor 记录、OKX_REALTIME_MONITOR_CONFIG 配置。
+
+- trade_ma_strategy_main.py
+  - 功能: 批量运行“均线突破/相关”策略的统计回测（主要是MACD命名策略）。
+  - 要点:
+    - 入口类 TradeMaStrategyMain -> MaBreakStatistics 批量统计。
+    - 聚合多个策略结果输出合并的资金曲线/收益数据。
+    - 可配置是否美股/是否Binance、佣金参数等。
+
+- trade_sandbox_main.py
+  - 功能: 均值回归策略沙盒回测，批量跑不同方案并输出Excel和图表。
+  - 要点:
+    - 批量维度：symbols × bars × solutions。
+    - 统计指标：止盈/止损次数与占比、收益分布、均值等，按 `symbol, bar` 分组。
+    - 自动绘制2×2面板图（不同bar），嵌入Excel文件。
+    - 可仅跑5m，也可多周期。
+
+- market_data_from_itick_main.py
+  - 功能: 按时间段分片下载美股/ETF数据（示例使用AlphaVantage类命名），处理并保存CSV，展示统计。
+  - 要点:
+    - 配置symbol/interval/分段天数，降低单次请求压力。
+    - 下载→处理→保存→打印统计的串行流程。
+    - 作为离线数据拉取脚本模版使用。
+
+- auto_schedule.py
+  - 功能: 简易定时调度器，周期性运行 `huge_volume_main.py`。
+  - 要点:
+    - 使用 schedule 每小时执行一次；记录执行时间与耗时。
+    - 兼容不同当前工作目录定位脚本路径。
+    - 适合本地常驻调度。
+
+- auto_update_market_data.py
+  - 功能: 同上，定时运行 `huge_volume_main.py`（与 auto_schedule.py 功能基本一致）。
+  - 要点:
+    - 同样是每小时执行，日志与输出一致。
+    - 可按需要二选一保留，避免重复。
+
+- update_data_main.py
+  - 功能: 批量更新数据库中行情数据的技术指标与美东时间字段。
+  - 要点:
+    - 从DB读取全量数据→按timestamp排序→更新 `date_time_us` 与 `SAR` 指标→回写DB。
+    - 支持美股/加密两套symbols与bars配置。
+    - 严格校验MySQL配置是否存在密码。
+
+- trade_data_main.py
+  - 功能: 交易明细拉取与补齐（API与DB结合），返回时间段内整理过的交易数据。
+  - 要点:
+    - 依据DB现有最早/最新时间决定是否调用API补齐前段或后段。
+    - 默认时间范围从配置初始时间到当前；最终结果从DB聚合、排序、去重。
+    - 依赖 TradeData 实现API交互与DB写入。
+
+- statistics_main.py
+  - 功能: 批量价格/成交量统计。
+  - 要点:
+    - 调用 PriceVolumeStats 批处理，返回价格统计、成交量统计与联动统计结果。
+    - 用作一次性统计入口，便于离线分析。
+
+- trade_main.py
+  - 功能: 交易流程演示脚本（三段式示例：开空→现货卖出→平空）。
+  - 要点:
+    - 封装 QuantTrader，对接实盘/模拟（由配置SANDBOX决定）。
+    - 展示下单参数：逐仓/全仓、张数、杠杆、缓冲比例；以及余额检查、下单、平仓流程。
+    - 以日志形式串联完整交易生命周期，适合作为交易API联通性验证与流程Demo。
+
+- huge_volume_main.py
+  - 功能: 巨量成交检测与统计分析的核心入口（OKX与Binance均支持）。
+  - 要点:
+    - 从行情表读取K线，计算滑窗放量、价格分位等；支持初始化、按窗口增量更新。
+    - Binance 支持CSV历史导入，导入后联动更新巨量表。
+    - 提供后续N周期涨跌统计、Excel导出与可视化，以及企业微信推送过滤（如volume_ratio>10且极值价位）。
+    - 多窗口（50/80/100/120）与多周期（1m~1D）批量处理能力，MySQL落库去重。

doc/trade_code_file_brief.md

@@ -0,0 +1,23 @@
+- ma_break_statistics.py
+  - 功能: 统计“均线突破”后的收益表现，批量跑不同标的/周期，生成统计与图表/Excel。
+  - 要点:
+    - 数据源可切换：OKX/Binance/美股；时间范围从配置读取。
+    - 关注 MA5/10/20/30 多组“上穿/下穿”组合，度量突破后的区间收益。
+    - 可配置手续费率，输出多策略合并结果，落地到指定 output 目录。
+    - 与数据库类 `DBMarketData/DBBinanceData/DBHugeVolumeData` 协同，读取K线、过滤区间。
+
+- mean_reversion_sandbox.py
+  - 功能: 均值回归策略沙盒（回测器），按多种“买入/止损/止盈方案”跑批评估，生成统计+图表+Excel。
+  - 要点:
+    - 条件以“价格分位+巨量”触发为主：如 close_10_low=1 或 close_80/90_high=1 且近2根K线任一巨量。
+    - 多个方案（solution_1/2/3）策略化定义（止盈可用波段中位数、分位、高位形态等）。
+    - 读自合并视图 `DBMergeMarketHugeVolume`（含价量与巨量事件），统一回测窗口与分组汇总。
+    - 自动出图（seaborn/matplotlib）并将图贴入 Excel，结果分 symbol×bar 汇总。
+
+- orb_trade.py
+  - 功能: ORB（Opening Range Breakout）日内策略回测与可视化。
+  - 要点:
+    - 以开盘第一根5分钟K线的高低（High1/Low1）作为区间，第二根K线产生多空信号；入场价=第二根开盘价，止损价=第一根极值；盈亏基于 $R（entry-stop）。
+    - 支持参数：账户初始资金、最大杠杆、单笔风险比例、佣金、盈利目标倍数、仅做多/仅做空/双向、是否参考 SAR、是否参考 1H 形态等。
+    - 数据获取两路：优先本地DB（OKX/Binance），也提供 yfinance 拉取美股数据的流程；自动调整初始资金规模以适配价格量级。
+    - 回测输出交易清单、资金曲线，生成图表与Excel摘要到 output 目录。

huge_volume_main.py

@@ -11,7 +11,7 @@ import core.logger as logging
 from config import (
     OKX_MONITOR_CONFIG,
     US_STOCK_MONITOR_CONFIG,
-    MYSQL_CONFIG,
+    COIN_MYSQL_CONFIG,
     WINDOW_SIZE,
     BINANCE_MONITOR_CONFIG,
 )
@@ -30,13 +30,13 @@ class HugeVolumeMain:
         is_us_stock: bool = False,
         is_binance: bool = False,
     ):
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
         self.huge_volume = HugeVolume()

market_data_main.py

@@ -21,7 +21,7 @@ from config import (
     OKX_MONITOR_CONFIG,
     BINANCE_MONITOR_CONFIG,
     US_STOCK_MONITOR_CONFIG,
-    MYSQL_CONFIG,
+    COIN_MYSQL_CONFIG,
     BAR_THRESHOLD,
 )
 
@@ -67,13 +67,13 @@ class MarketDataMain:
             self.initial_date = OKX_MONITOR_CONFIG.get("volume_monitor", {}).get(
                 "initial_date", "2025-07-01 00:00:00"
             )
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
         if is_binance:

market_monitor_main.py

@@ -4,7 +4,7 @@ from huge_volume_main import HugeVolumeMain
 from core.biz.market_monitor import create_metrics_report
 from core.db.db_market_monitor import DBMarketMonitor
 from core.wechat import Wechat
-from config import OKX_MONITOR_CONFIG, OKX_REALTIME_MONITOR_CONFIG, MYSQL_CONFIG, WECHAT_CONFIG
+from config import OKX_MONITOR_CONFIG, OKX_REALTIME_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WECHAT_CONFIG
 from core.utils import timestamp_to_datetime, transform_date_time_to_timestamp
 import core.logger as logging
 
@@ -31,13 +31,13 @@ class MarketMonitorMain:
         self.output_folder = "./output/report/market_monitor/"
         os.makedirs(self.output_folder, exist_ok=True)
 
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
 

play.py

@@ -2,7 +2,7 @@ import logging
 from core.biz.quant_trader import QuantTrader
 from core.biz.strategy import QuantStrategy
 
-from config import MYSQL_CONFIG
+from config import COIN_MYSQL_CONFIG
 from sqlalchemy import create_engine, exc, text
 import pandas as pd
 
@@ -100,13 +100,13 @@ def main() -> None:
 
 
 def test_query():
-    mysql_user = MYSQL_CONFIG.get("user", "xch")
+    mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-    mysql_password = MYSQL_CONFIG.get("password", "")
+    mysql_password = COIN_MYSQL_CONFIG.get("password", "")
     if not mysql_password:
         raise ValueError("MySQL password is not set")
-    mysql_host = MYSQL_CONFIG.get("host", "localhost")
+    mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-    mysql_port = MYSQL_CONFIG.get("port", 3306)
+    mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-    mysql_database = MYSQL_CONFIG.get("database", "okx")
+    mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
     db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
     db_engine = create_engine(
                 db_url,

test_ma_methods.py

@@ -10,7 +10,7 @@ import matplotlib.pyplot as plt
 from core.db.db_market_data import DBMarketData
 from core.biz.metrics_calculation import MetricsCalculation
 import logging
-from config import OKX_MONITOR_CONFIG, MYSQL_CONFIG, WINDOW_SIZE
+from config import OKX_MONITOR_CONFIG, COIN_MYSQL_CONFIG, WINDOW_SIZE
 # plt支持中文
 plt.rcParams['font.family'] = ['SimHei']
 
@@ -18,13 +18,13 @@ plt.rcParams['font.family'] = ['SimHei']
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 
 def get_real_data(symbol, bar, start, end):
-    mysql_user = MYSQL_CONFIG.get("user", "xch")
+    mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-    mysql_password = MYSQL_CONFIG.get("password", "")
+    mysql_password = COIN_MYSQL_CONFIG.get("password", "")
     if not mysql_password:
         raise ValueError("MySQL password is not set")
-    mysql_host = MYSQL_CONFIG.get("host", "localhost")
+    mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-    mysql_port = MYSQL_CONFIG.get("port", 3306)
+    mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-    mysql_database = MYSQL_CONFIG.get("database", "okx")
+    mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
     db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
     db_market_data = DBMarketData(db_url)

trade_data_main.py

@@ -10,7 +10,7 @@ from config import (
     PASSPHRASE,
     SANDBOX,
     OKX_MONITOR_CONFIG,
-    MYSQL_CONFIG,
+    COIN_MYSQL_CONFIG,
 )
 
 logger = logging.logger
@@ -18,13 +18,13 @@ logger = logging.logger
 
 class TradeDataMain:
     def __init__(self):
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
         self.trade_data = TradeData(

trade_ma_strategy_main.py

@@ -18,7 +18,6 @@ from config import (
     PASSPHRASE,
     SANDBOX,
     OKX_MONITOR_CONFIG,
-    MYSQL_CONFIG,
     BAR_THRESHOLD,
 )
 
@@ -29,13 +28,21 @@ class TradeMaStrategyMain:
     def __init__(
         self,
         is_us_stock: bool = False,
+        is_astock: bool = False,
+        is_aindex: bool = True,
         is_binance: bool = False,
         commission_per_share: float = 0,
+        buy_by_long_period: dict = {"by_week": False, "by_month": False},
+        long_period_condition: dict = {"ma5>ma10": False, "ma10>ma20": False, "macd_diff>0": False, "macd>0": False},
     ):
         self.ma_break_statistics = MaBreakStatistics(
             is_us_stock=is_us_stock,
+            is_astock=is_astock,
+            is_aindex=is_aindex,
             is_binance=is_binance,
             commission_per_share=commission_per_share,
+            buy_by_long_period=buy_by_long_period,
+            long_period_condition=long_period_condition,
         )
 
     def batch_ma_break_statistics(self):
@@ -60,12 +67,51 @@ class TradeMaStrategyMain:
         logger.info("开始统计account_value_chg")
 
 
+def test_single_symbol():
+    ma_break_statistics = MaBreakStatistics(
+        is_us_stock=False,
+        is_astock=True,
+        is_aindex=False,
+        is_binance=False,
+        commission_per_share=0,
+    )
+    symbol = "600111.SH"
+    bar = "1D"
+    ma_break_statistics.trade_simulate(symbol=symbol, bar=bar, strategy_name="均线macd结合策略2")
+
+
 if __name__ == "__main__":
     commission_per_share_list = [0, 0.0008]
+    buy_by_long_period_list = [{"by_week": True, "by_month": True}, 
+    {"by_week": True, "by_month": False}, 
+    {"by_week": False, "by_month": True},
+    {"by_week": False, "by_month": False}]
+    long_period_condition_list = [{"ma5>ma10": True, "ma10>ma20": True, "macd_diff>0": True, "macd>0": True},
+    {"ma5>ma10": True, "ma10>ma20": False, "macd_diff>0": True, "macd>0": True},
+    {"ma5>ma10": False, "ma10>ma20": True, "macd_diff>0": True, "macd>0": True}]
+    
     for commission_per_share in commission_per_share_list:
+        for buy_by_long_period in buy_by_long_period_list:
+            for long_period_condition in long_period_condition_list:
+                logger.info(f"开始计算, 主要参数：commission_per_share: {commission_per_share}, buy_by_long_period: {buy_by_long_period}, long_period_condition: {long_period_condition}")
                 trade_ma_strategy_main = TradeMaStrategyMain(
                     is_us_stock=False,
-            is_binance=True,
+                    is_astock=False,
+                    is_aindex=True,
+                    is_binance=False,
                     commission_per_share=commission_per_share,
+                    buy_by_long_period=buy_by_long_period,
+                    long_period_condition=long_period_condition,
+                )
+                trade_ma_strategy_main.batch_ma_break_statistics()
+
+                trade_ma_strategy_main = TradeMaStrategyMain(
+                    is_us_stock=False,
+                    is_astock=True,
+                    is_aindex=False,
+                    is_binance=False,
+                    commission_per_share=commission_per_share,
+                    buy_by_long_period=buy_by_long_period,
+                    long_period_condition=long_period_condition,
                 )
                 trade_ma_strategy_main.batch_ma_break_statistics()

update_data_main.py

@@ -2,20 +2,20 @@ import pandas as pd
 
 from core.db.db_market_data import DBMarketData
 from core.biz.metrics_calculation import MetricsCalculation
-from config import MYSQL_CONFIG, US_STOCK_MONITOR_CONFIG, OKX_MONITOR_CONFIG
+from config import COIN_MYSQL_CONFIG, US_STOCK_MONITOR_CONFIG, OKX_MONITOR_CONFIG
 import core.logger as logging
 
 logger = logging.logger
 
 class UpdateDataMain:
     def __init__(self):
-        mysql_user = MYSQL_CONFIG.get("user", "xch")
+        mysql_user = COIN_MYSQL_CONFIG.get("user", "xch")
-        mysql_password = MYSQL_CONFIG.get("password", "")
+        mysql_password = COIN_MYSQL_CONFIG.get("password", "")
         if not mysql_password:
             raise ValueError("MySQL password is not set")
-        mysql_host = MYSQL_CONFIG.get("host", "localhost")
+        mysql_host = COIN_MYSQL_CONFIG.get("host", "localhost")
-        mysql_port = MYSQL_CONFIG.get("port", 3306)
+        mysql_port = COIN_MYSQL_CONFIG.get("port", 3306)
-        mysql_database = MYSQL_CONFIG.get("database", "okx")
+        mysql_database = COIN_MYSQL_CONFIG.get("database", "okx")
 
         self.db_url = f"mysql+pymysql://{mysql_user}:{mysql_password}@{mysql_host}:{mysql_port}/{mysql_database}"
         self.db_market_data = DBMarketData(self.db_url)