modify dirs

src/config/bak.py

@@ -17,6 +17,11 @@ log_dir_prefix = '../log'
 global_share_data_dir = '/root/sharedata'
 global_stock_data_dir = '/root/hostdir/stock_data'
 
+# 获取当前文件所在目录
+current_dir = os.path.dirname(os.path.abspath(__file__))
+# 获取项目根目录（假设当前文件在 src/strategy 下）
+project_root = os.path.abspath(os.path.join(current_dir, '..', '..'))
+
 # 获取log目录
 def get_log_directory():
     """

src/config/config.py

@@ -0,0 +1,38 @@
+import os
+from pathlib import Path
+
+# MySQL 配置
+db_config = {
+    'host': 'testdb',
+    'user': 'root',
+    'password': 'mysqlpw',
+    'database': 'stockdb'
+}
+
+global_share_data_dir = '/root/sharedata'
+global_stock_data_dir = '/root/hostdir/stock_data'
+
+# 获取当前文件所在目录
+current_dir = Path(__file__).resolve().parent
+
+# 找到项目根目录，假设项目根目录下有一个 src 文件夹
+project_root = current_dir
+while project_root.name != 'src' and project_root != project_root.parent:
+    project_root = project_root.parent
+
+# 获取 src 目录
+def get_src_directory():
+    return project_root
+
+# 获取 src/config 目录
+def get_src_config_directory():
+    return project_root / 'config'
+
+# 获取 log 目录
+def get_log_directory():
+    """
+    获取与 src 平行的 log 目录路径。如果 log 目录不存在，则自动创建。
+    """
+    log_dir = project_root.parent / 'log'
+    log_dir.mkdir(parents=True, exist_ok=True)
+    return log_dir

src/logger/logger.py

@@ -0,0 +1,43 @@
+import logging
+import os
+import inspect
+from datetime import datetime
+from pathlib import Path
+from src.config.config import get_log_directory, get_src_directory
+
+def get_caller_filename():
+    # 获取调用栈
+    stack = inspect.stack()
+    # 当前脚本文件名
+    current_script = os.path.basename(__file__)
+    # 遍历栈帧，找到不是当前脚本的调用者
+    for frame_info in stack[1:]:
+        if os.path.basename(frame_info.filename) != current_script:
+            caller_path = Path(frame_info.filename)
+            # 尝试找到 src 目录
+            try:
+                relative_path = caller_path.relative_to(get_src_directory())
+                # 去除扩展名
+                relative_path_without_ext = relative_path.with_suffix('')
+                # 替换路径分隔符为下划线
+                return str(relative_path_without_ext).replace(os.sep, '-')
+            except ValueError:
+                # 如果无法获取相对于 src 的路径，使用原文件名
+                return os.path.splitext(os.path.basename(frame_info.filename))[0]
+    return None
+
+# 设置日志配置
+def setup_logging(log_filename=None):
+    # 如果未传入 log_filename，则使用当前脚本名称作为日志文件名
+    if log_filename is None:
+        caller_filename = get_caller_filename()
+        common_log_dir = get_log_directory()
+        current_date = datetime.now().strftime('%Y%m%d')
+        # 拼接 log 文件名，将日期加在扩展名前
+        log_filename = f'{common_log_dir}/{caller_filename}_{current_date}.log'
+
+    logging.basicConfig(level=logging.INFO, format='%(asctime)s %(levelname)s [%(filename)s:%(lineno)d] (%(funcName)s) - %(message)s',
+                        handlers=[
+                            logging.FileHandler(log_filename),
+                            logging.StreamHandler()
+                        ])

src/main.py

@@ -0,0 +1,11 @@
+import logging
+import src.config.config as config
+import src.logger.logger as log_conf
+
+log_conf.setup_logging()
+def test():
+    logging.info(f'test logging')
+
+
+if __name__ == "__main__":
+    test()

src/static/bak_stat_growth_rate.py

@@ -17,12 +17,12 @@ import pymysql
 import pandas as pd
 import time
 from datetime import datetime
-import logging
-import config 
+import src.logger.logger as logger
+import src.config.config as config
 
 # 设置日志
-config.setup_logging()
-logger = logging.getLogger()
+logger.setup_logging()
+logger = logger.getLogger()
 
 # 数据库连接函数
 def connect_to_db():

src/static/stat_growth_em.py

@@ -18,16 +18,17 @@ import pymysql
 import logging
 import csv
 import os
-import config
 import time
 from datetime import datetime
 from futu import OpenQuoteContext, RET_OK  # Futu API client
 from futu import *
-import crawling.stock_hist_em as his_em
 import argparse
+import src.crawling.stock_hist_em as his_em
+import src.logger.logger as logger
+import src.config.config as config
 
 # 配置日志
-config.setup_logging()
+logger.setup_logging()
 
 current_date = datetime.now().strftime("%Y%m%d")
 current_year = datetime.now().strftime("%Y")

src/static/test_log.py

@@ -0,0 +1,11 @@
+import logging
+import src.config.config as config
+import src.config.log_config as log_conf
+
+log_conf.setup_logging()
+def test():
+    logging.info(f'test logging')
+
+
+if __name__ == "__main__":
+    test()

src/strategy/KC.csv

@@ -0,0 +1,255 @@
+Price,Close,High,Low,Open,Volume,5d_change,20d_change,60d_change
+Ticker,KC,KC,KC,KC,KC,,,
+Date,,,,,,,,
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src/strategy/test.py

@@ -0,0 +1,94 @@
+import numpy as np
+import pandas as pd
+import yfinance as yf
+
+stock_code = 'MSFT'
+
+def fetch_stock_data(stock_code, start_date='2024-01-01', end_date='2025-01-01'):
+    # 拉取数据
+    df = yf.download(stock_code, start=start_date, end=end_date)
+    df['5d_change'] = df['Close'].pct_change(5) * 100
+    df['20d_change'] = df['Close'].pct_change(20) * 100
+    df['60d_change'] = df['Close'].pct_change(60) * 100
+    # 将数据保存为 CSV 文件
+    df.to_csv(f'{stock_code}.csv')
+    return df
+
+def calculate_rsi(data, window=14):
+    delta = data['Close'].diff()
+    gain = np.where(delta > 0, delta, 0).ravel()
+    loss = np.where(delta < 0, -delta, 0).ravel()
+
+    avg_gain = pd.Series(gain).rolling(window=window).mean()
+    avg_loss = pd.Series(loss).rolling(window=window).mean()
+
+    rs = avg_gain / avg_loss
+    rsi = 100 - (100 / (1 + rs))
+    data['RSI'] = rsi
+    return data
+
+def calculate_rsi2(data, window=14):
+    delta = data['Close'].diff()
+    gain = delta.clip(lower=0)
+    loss = -delta.clip(upper=0)
+
+    avg_gain = gain.rolling(window=window).mean()
+    avg_loss = loss.rolling(window=window).mean()
+
+    rs = avg_gain / avg_loss
+    rsi = 100 - (100 / (1 + rs))
+    data['RSI'] = rsi
+    return data
+
+'''
+df = fetch_stock_data(stock_code)
+df = calculate_rsi2(df)
+# 输出RSI值为NaN的行
+nan_rsi_rows = df[df['RSI'].isna()]
+print("RSI值为NaN的行：")
+print(nan_rsi_rows['RSI'])
+
+# 统计非NaN的行数
+non_nan_count = df['RSI'].count()
+print(f"RSI值非NaN的行数：{non_nan_count}")
+
+'''
+
+def calculate_macd(data, short_window=12, long_window=26, signal_window=9):
+    data['EMA12'] = data['Close'].ewm(span=short_window, adjust=False).mean()
+    data['EMA26'] = data['Close'].ewm(span=long_window, adjust=False).mean()
+    data['MACD'] = data['EMA12'] - data['EMA26']
+    data['Signal_Line'] = data['MACD'].ewm(span=signal_window, adjust=False).mean()
+    return data
+
+def strategy(data):
+    # 策略条件：超跌 + RSI低于30 + MACD金叉
+    buy_signals = (data['5d_change'] < -10) & (data['20d_change'] < -20) &  (data['RSI'] < 30) & (data['MACD'] > data['Signal_Line'])
+    buy_signals2 = (data['5d_change'] < -10) & (data['20d_change'] < -20) 
+    buy_signals3 = (data['5d_change'] < -10) &  (data['RSI'] < 30) & (data['MACD'] > data['Signal_Line'])
+    buy_signals4 = (data['5d_change'] < -10) &  (data['RSI'] < 30) 
+    sell_signals = (data['Close'].pct_change() < -0.05) | (data['Close'].pct_change() > 0.1)
+    
+    data['Buy_Signal'] = buy_signals4
+    data['Sell_Signal'] = sell_signals
+    return data
+
+# 主函数
+def run_strategy(stock_code):
+    df = fetch_stock_data(stock_code)
+    df = calculate_rsi2(df)
+    df = calculate_macd(df)
+    df = strategy(df)
+
+    buy_signal_df = df[df['Buy_Signal']]
+    print(buy_signal_df[['Close', '5d_change', 'RSI', 'MACD', 'Signal_Line', 'Buy_Signal', 'Sell_Signal']])
+
+    sell_signal_df = df[df['Sell_Signal']]
+    print(sell_signal_df[['Close', '5d_change', 'RSI', 'MACD', 'Signal_Line', 'Buy_Signal', 'Sell_Signal']])
+
+    #signal_df = df[(df['Buy_Signal']) | (df['Sell_Signal'])]
+    #print(signal_df[['Close', '5d_change', 'RSI', 'MACD', 'Signal_Line', 'Buy_Signal', 'Sell_Signal']])
+    #print(df[['Close', '5d_change', 'RSI', 'MACD', 'Signal_Line', 'Buy_Signal', 'Sell_Signal']].tail(20))
+
+# 示例：运行策略
+run_strategy('KC')