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API.py

@@ -6,11 +6,32 @@ from datetime import timedelta
 import pymysql
 from sqlalchemy import create_engine
 from dateutil.relativedelta import relativedelta
+import logging
+import time
+import os
 
+total_start = time.time()
+# 在文件开头添加日志配置
+def setup_logging():
+    log_dir = os.path.join(os.path.dirname(__file__), 'logs')
+    os.makedirs(log_dir, exist_ok=True)
+    
+    logging.basicConfig(
+        level=logging.INFO,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        handlers=[
+            logging.FileHandler(os.path.join(log_dir, 'api.log')),
+            logging.StreamHandler()
+        ]
+    )
+
+setup_logging()
+logger = logging.getLogger(__name__)
 
 # 在API.py开头添加
 import sys
 
+
 # 替换原来的get_user_date函数
 def get_user_date():
     if len(sys.argv) > 1:
@@ -43,7 +64,7 @@ engine = create_engine(f'mysql+pymysql://{username}:{password}@{host}:{port}/{da
 configPath = r'C:\AI trading\config\Rey\test_reinforcement'
 matlabPath = r'D:\Dropbox\Matlab\Rey\MATLAB'
 
-# 修改为你的 Excel 文件路径
+# 修改为 Excel 文件路径
 tempPath = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\皇极经世.xlsx'
 
 # ========== 加载 64 卦映射表 ==========
@@ -58,14 +79,14 @@ Map64GuaOmit = Map64Gua[Map64Gua['change_omit'] == 0]
 # ========== 从数据库加载 24 节气数据 ==========
 def load_solar_terms(conn_params):
     """通过 SQLAlchemy 连接读取 solar_terms 表"""
-    sqlquery = 'SELECT * FROM solar_terms'
+    sqlquery = "SELECT * FROM solar_terms WHERE As_Of_Date > '1744-01-01'"
     df = pd.read_sql(sqlquery, engine)
 
     # 尝试将 As_Of_Date 转为 datetime，如果失败就变成 NaT
     df['As_Of_Date'] = pd.to_datetime(df['As_Of_Date'], errors='coerce')
 
     # 过滤掉早于 1900-01-01 或转换失败的日期
-    df = df[df['As_Of_Date'] >= pd.Timestamp('1900-01-01')]
+    df = df[df['As_Of_Date'] >= pd.Timestamp('1780-01-01')]
     df = df.dropna(subset=['As_Of_Date'])
     # df['As_Of_Date'] = df['As_Of_Date']
     df = df.sort_values('As_Of_Date')
@@ -102,14 +123,51 @@ def get_user_date():
         print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr)
         sys.exit(1)
 # 加载数据并标记重要节气
+load_start = time.time()
 solar_terms = load_solar_terms(engine)
+logger.info(f"节气加载完成，耗时: {time.time() - load_start:.2f}秒")
 important_terms = ['冬至', '雨水', '谷雨', '夏至', '处暑', '霜降']
 solar_terms['isImportant'] = solar_terms['Solar_Terms'].isin(important_terms).astype(int)
 Map24Jieqi = solar_terms.copy()
 
 # ========== 读取CSV文件并处理每个日期的卦象 ==========
+read_start = time.time()
 csv_path = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\python1\2020 - 2030年每天卦.csv'
 table = pd.read_csv(csv_path)
+logger.info(f"读取csv文件完成，耗时: {time.time() - read_start:.2f}秒")
+try:
+    piwen_path = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\python1\批文.xlsx'
+    piwen_data = pd.read_excel(piwen_path)
+    
+    # 打印列名用于调试
+    print("批文文件列名:", piwen_data.columns.tolist(), file=sys.stderr)
+    
+    # 检查必要的列是否存在
+    if not all(col in piwen_data.columns for col in ['卦名', '命卦批文', '八个字基本盘']):
+        print("批文文件缺少必要列，请检查Excel文件列名", file=sys.stderr)
+        piwen_data = pd.DataFrame(columns=['卦名', '命卦批文', '八个字基本盘'])
+except Exception as e:
+    print(f"读取批文文件失败: {str(e)}", file=sys.stderr)
+    piwen_data = pd.DataFrame(columns=['卦名', '命卦批文', '八个字基本盘'])
+
+def get_piwen_info(trigram_name):
+    """根据卦名获取批文和基本盘信息"""
+    if not isinstance(trigram_name, str):
+        trigram_name = str(trigram_name)
+    
+    try:
+        match = piwen_data[piwen_data['卦名'] == trigram_name]
+        if not match.empty:
+            return {
+                'piwen': match.iloc[0]['命卦批文'],
+                'basic_info': match.iloc[0]['八个字基本盘']
+            }
+        else:
+            print(f"未找到卦名 {trigram_name} 的批文信息", file=sys.stderr)
+            return {'piwen': '暂无批文信息', 'basic_info': '暂无基本盘信息'}
+    except Exception as e:
+        print(f"获取批文信息出错: {str(e)}", file=sys.stderr)
+        return {'piwen': '暂无批文信息', 'basic_info': '暂无基本盘信息'}
 # 获取用户输入
 kDate = get_user_date()
 #print("\n计算日期:", kDate.strftime('%Y-%m-%d'))
@@ -125,16 +183,23 @@ import json  # 导入 JSON 库
 
 if __name__ == "__main__":
     print("=== 调试开始 ===", file=sys.stderr)  # 打印到 stderr 不会干扰 stdout 的 JSON
-    kDate = get_user_date()
     try:
+        input_start = time.time()
+        kDate = get_user_date()
+        logger.info(f"获取用户输入完成，耗时: {time.time() - input_start:.2f}秒")
+         # 计算卦象
+        calc_start = time.time()
         Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi(
             Map64Gua, Map24Jieqi, kDate
         )
+        logger.info(f"卦象计算完成，耗时: {time.time() - calc_start:.2f}秒")
         # # 计算10年前（当前日期减10年）
         # Yearpre10 = kDate.replace(year=kDate.year - 10)
         # # 计算10年后（当前日期加10年）
         # Yearpast10 = kDate.replace(year=kDate.year + 10)
         # 或者使用relativedelta（更精确处理闰年等情况）
+        # 计算年份卦象
+        year_start = time.time()
         Yearpre10 = datetime(2010, 1, 1)
         Yearpast10 = datetime(2030, 1, 1,)
 
@@ -154,9 +219,12 @@ if __name__ == "__main__":
             })
 
         yearGuaMap = pd.DataFrame(year_gua_list)
+        logger.info(f"年份卦象计算完成，耗时: {time.time() - year_start:.2f}秒")
         #========== 计算年份吉凶 ==========
+        # 计算年份吉凶
+        luck_start = time.time()
         LuckYear = luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck)
-
+        logger.info(f"吉凶计算完成，耗时: {time.time() - luck_start:.2f}秒")
         # # 检查 Gua1Day 的类型并正确处理
         # if isinstance(Gua1Day, pd.DataFrame):
         #     # 如果是 DataFrame，提取第一行
@@ -171,8 +239,20 @@ if __name__ == "__main__":
         #     raise ValueError("Gua1Day 的类型不支持，必须是 DataFrame、Series 或 dict")
         def format_gua_data(gua_data):
             """通用格式化卦象数据的函数"""
-            if isinstance(gua_data, (pd.DataFrame, pd.Series)):
+            if isinstance(gua_data, pd.DataFrame):
-                data = gua_data.iloc[0] if isinstance(gua_data, pd.DataFrame) else gua_data
+                # DataFrame类型 - 取第一行转为字典
+                data = gua_data.iloc[0].to_dict()
+            elif isinstance(gua_data, pd.Series):
+                # Series类型 - 直接转为字典
+                data = gua_data.to_dict()
+            elif isinstance(gua_data, dict):
+                # 已经是字典类型
+                data = gua_data
+            else:
+                # 未知类型返回空字典
+                return {}
+            
+            # 统一处理字典数据
             return {
                 'id': int(data.get('id', 0)),
                 'trigram': str(data.get('trigram', '')),
@@ -187,10 +267,6 @@ if __name__ == "__main__":
                 'change_omit': int(data.get('change_omit', 0)),
                 'type': str(data.get('Type', 'unknown'))
             }
-            elif isinstance(gua_data, dict):
-                return gua_data
-            else:
-                return {}
 
         # 构建结果字典，确保所有值是 Python 原生类型
         # result = {
@@ -211,28 +287,52 @@ if __name__ == "__main__":
         #     }
         # }
         # 构建完整结果
+        build_start = time.time()
         result = {
             'date': kDate.strftime('%Y-%m-%d'),
-            'year_gua': format_gua_data(Gua1Year),
+            'year_gua': {
-            'month_gua': format_gua_data(Gua1Month),
+                **format_gua_data(Gua1Year),
-            'day_gua': format_gua_data(Gua1Day),
+                **get_piwen_info(format_gua_data(Gua1Year).get('trigram', ''))
-            'hour_gua': format_gua_data(Gua1Hour),
+            },
-            'luck_gua': format_gua_data(GuaLuck),
+            'month_gua': {
+                **format_gua_data(Gua1Month),
+                **get_piwen_info(format_gua_data(Gua1Month).get('trigram', ''))
+            },
+            'day_gua': {
+                **format_gua_data(Gua1Day),
+                **get_piwen_info(format_gua_data(Gua1Day).get('trigram', ''))
+            },
+            'hour_gua': {
+                **format_gua_data(Gua1Hour),
+                **get_piwen_info(format_gua_data(Gua1Hour).get('trigram', ''))
+            },
+            'luck_gua': {
+                **format_gua_data(GuaLuck),
+                **get_piwen_info(format_gua_data(GuaLuck).get('trigram', ''))
+            },
             'luck_years': [
                 {
                     'year': row['Year'],
                     'trigram': row['trigram'],
-                    'yaoAll': row['yaoAll']
+                    'yaoAll': row['yaoAll'],
+                    **get_piwen_info(row['trigram'])
                 } for _, row in LuckYear.iterrows()
             ] if isinstance(LuckYear, pd.DataFrame) else []
         }
+        logger.info(f"结果构建完成，耗时: {time.time() - build_start:.2f}秒")
+
         # 在打印 JSON 前检查内容
         print("=== 要输出的 JSON 内容 ===", file=sys.stderr)
         print(result, file=sys.stderr)
         # 输出 JSON 格式的结果
         # print(json.dumps(result, ensure_ascii=False, indent=4))  # 添加 indent 参数更好查看格式
+                # 输出结果
+        output_start = time.time()
         print(json.dumps(result, ensure_ascii=False, indent=2))
+        logger.info(f"结果输出完成，耗时: {time.time() - output_start:.2f}秒")
 
+        total_time = time.time() - total_start
+        logger.info(f"=== API 执行完成，总耗时: {total_time:.2f}秒 ===")
     except Exception as e:
         import traceback
         traceback.print_exc(file=sys.stderr)  # 打印错误堆栈，帮助调试

server.py

@@ -4,60 +4,118 @@ import sys
 from datetime import datetime
 import os
 import json
+# 在server.py顶部添加
+import pandas as pd
+import logging
+from logging.handlers import RotatingFileHandler
+import time
+
 app = Flask(__name__)
 
+# 在Flask应用初始化后添加
+@app.before_first_request
+def load_batch_data():
+    # 读取批文Excel文件
+    batch_path = r'C:\Users\24011\Documents\WeChat Files\wxid_k4ep58f81rx421\FileStorage\File\2025-04\tuigua_huangjijingshi - 副本\tuigua_huangjijingshi - 副本\python1\批文.xlsx'
+    app.batch_data = pd.read_excel(batch_path)
+
+    # 在 Flask 应用初始化后添加日志配置
+def setup_logging():
+    # 创建日志目录（如果不存在）
+    log_dir = os.path.join(os.path.dirname(__file__), 'logs')
+    os.makedirs(log_dir, exist_ok=True)
+    
+    # 配置根日志
+    logging.basicConfig(
+        level=logging.INFO,
+        format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
+        handlers=[
+            RotatingFileHandler(
+                os.path.join(log_dir, 'app.log'),
+                maxBytes=1024*1024*5,  # 5MB
+                backupCount=5
+            ),
+            logging.StreamHandler()
+        ]
+    )
+
+# 在应用初始化后调用
+setup_logging()
+logger = logging.getLogger(__name__)
 @app.route('/')
 def home():
     return render_template('index.html')
 
 @app.route('/calculate', methods=['POST'])
 def calculate():
+    start_time = time.time()
+    logger.info("开始处理计算请求")
+    
     date_str = request.form.get('date')
-    time_str = request.form.get('time', '00:00:00')  # 默认为00:00:00
+    time_str = request.form.get('time', '00:00:00')
     
     try:
         # 验证日期和时间格式
-        datetime.strptime(date_str, '%Y-%m-%d')  # 先单独验证日期
+        datetime.strptime(date_str, '%Y-%m-%d')
-        datetime.strptime(time_str, '%H:%M:%S')  # 再验证时间
+        datetime.strptime(time_str, '%H:%M:%S')
-
-        # 组合日期和时间
         datetime_str = f"{date_str} {time_str}"
         
         api_path = os.path.join(os.path.dirname(__file__), 'API.py')
+        logger.info(f"准备调用API.py，参数: {datetime_str}")
+        
+        api_start = time.time()
         result = subprocess.run(
             [sys.executable, api_path, datetime_str],
             capture_output=True,
-            text=True,  # 确保输出是文本
+            text=True,
             check=True
         )
+        api_time = time.time() - api_start
+        logger.info(f"API.py执行完成，耗时: {api_time:.2f}秒")
         
-        # 打印完整输出用于调试
+        logger.debug("=== API.py 原始输出 ===")
-        print("=== API.py 原始输出 ===")
+        logger.debug(f"stdout: {result.stdout[:200]}...")  # 只记录前200字符
-        print("stdout:", result.stdout)
+        logger.debug(f"stderr: {result.stderr[:200]}...")
-        print("stderr:", result.stderr)
         
         try:
+            json_start = time.time()
             json_output = json.loads(result.stdout)
+            json_time = time.time() - json_start
+            logger.info(f"JSON解析完成，耗时: {json_time:.2f}秒")
+            
+            total_time = time.time() - start_time
+            logger.info(f"请求处理完成，总耗时: {total_time:.2f}秒")
             return jsonify({'success': True, 'result': json_output})
+            
         except json.JSONDecodeError as e:
-            print("JSON 解析失败:", e)
+            error_msg = f'JSON解析失败: {str(e)}'
-            print("原始输出:", result.stdout)
+            logger.error(error_msg)
+            logger.error(f"原始输出: {result.stdout[:500]}")
             return jsonify({
                 'success': False, 
-                'error': f'JSON解析失败: {str(e)}',
+                'error': error_msg,
-                'raw_output': result.stdout  # 返回原始输出用于调试
+                'raw_output': result.stdout[:500]
             })
     
-    except ValueError:
+    except ValueError as e:
-        return jsonify({'success': False, 'error': '无效的日期格式'})
+        error_msg = f'无效的日期格式: {str(e)}'
+        logger.error(error_msg)
+        return jsonify({'success': False, 'error': error_msg})
+        
     except subprocess.CalledProcessError as e:
+        error_msg = f'计算失败: {e.stderr}'
+        logger.error(error_msg)
+        logger.error(f"stdout: {e.stdout[:500]}")
         return jsonify({
             'success': False, 
-            'error': f'计算失败: {e.stderr}',
+            'error': error_msg,
-            'stdout': e.stdout
+            'stdout': e.stdout[:500]
         })
+        
     except Exception as e:
-        return jsonify({'success': False, 'error': str(e)})
+        error_msg = f'服务器错误: {str(e)}'
+        logger.error(error_msg, exc_info=True)
+        return jsonify({'success': False, 'error': error_msg})
 
 if __name__ == '__main__':
     app.run(debug=True,host='0.0.0.0',port=5000)