340 lines
15 KiB
Python
340 lines
15 KiB
Python
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import pandas as pd
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import numpy as np
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from datetime import datetime
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from datetime import timedelta
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import pymysql
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from sqlalchemy import create_engine
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from dateutil.relativedelta import relativedelta
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import logging
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import time
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import os
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total_start = time.time()
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# 在文件开头添加日志配置
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def setup_logging():
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log_dir = os.path.join(os.path.dirname(__file__), 'logs')
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os.makedirs(log_dir, exist_ok=True)
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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handlers=[
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logging.FileHandler(os.path.join(log_dir, 'api.log')),
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logging.StreamHandler()
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]
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)
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setup_logging()
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logger = logging.getLogger(__name__)
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# 在API.py开头添加
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import sys
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# 替换原来的get_user_date函数
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def get_user_date():
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if len(sys.argv) > 1:
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datetime_input = sys.argv[1]
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try:
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return datetime.strptime(datetime_input, '%Y-%m-%d %H:%M:%S')
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except ValueError:
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print("日期格式不正确，请使用YYYY-MM-DD HH:MM:SS格式", file=sys.stderr)
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sys.exit(1)
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else:
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print("没有传入日期时间参数", file=sys.stderr)
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sys.exit(1)
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# 导入自定义卦象计算模块
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from guaCalc_huangjijingshi import guaCalc_huangjijingshi
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from luckCalc_huangjijingshi import luckCalc_huangjijingshi
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# ========== 数据库连接配置 ==========
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# 你的账号、密码、主机、端口
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username = 'cn_ainvest_db'
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password = 'cn_ainvest_sd3a1'
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host = 'rm-2zewagytttzk6f24xno.mysql.rds.aliyuncs.com'
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port = 3306
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database = 'ai_strategy' # 这里改成你要的数据库
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# 创建 SQLAlchemy engine
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engine = create_engine(f'mysql+pymysql://{username}:{password}@{host}:{port}/{database}')
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# ========== 文件路径配置 ==========
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configPath = r'C:\AI trading\config\Rey\test_reinforcement'
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matlabPath = r'D:\Dropbox\Matlab\Rey\MATLAB'
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# 修改为 Excel 文件路径
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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'
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# ========== 加载 64 卦映射表 ==========
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Map64Gua = pd.read_excel(tempPath, sheet_name="bagua")
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# 转换爻数据为整数
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for col in ['yao1', 'yao2', 'yao3', 'yao4', 'yao5', 'yao6']:
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Map64Gua[col] = Map64Gua[col].apply(lambda x: int(x) if str(x).isdigit() else x)
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Map64GuaOmit = Map64Gua[Map64Gua['change_omit'] == 0]
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# ========== 从数据库加载 24 节气数据 ==========
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def load_solar_terms(conn_params):
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"""通过 SQLAlchemy 连接读取 solar_terms 表"""
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sqlquery = "SELECT * FROM solar_terms WHERE As_Of_Date > '1744-01-01'"
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df = pd.read_sql(sqlquery, engine)
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# 尝试将 As_Of_Date 转为 datetime，如果失败就变成 NaT
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df['As_Of_Date'] = pd.to_datetime(df['As_Of_Date'], errors='coerce')
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# 过滤掉早于 1900-01-01 或转换失败的日期
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df = df[df['As_Of_Date'] >= pd.Timestamp('1780-01-01')]
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df = df.dropna(subset=['As_Of_Date'])
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# df['As_Of_Date'] = df['As_Of_Date']
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df = df.sort_values('As_Of_Date')
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return df
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# ========== 用户输入日期 ==========
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# def get_user_date():
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# if len(sys.argv) > 1: # 命令行参数方式
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# date_input = sys.argv[1]
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# else: # 标准输入方式
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# date_input = sys.stdin.read().strip()
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# try:
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# year, month, day = map(int, date_input.split('-'))
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# return datetime(year, month, day, 0, 0, 0)
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# except ValueError:
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# print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr)
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# sys.exit(1)
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# 获取用户输入
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def get_user_date():
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# date_input = sys.stdin.read().strip() if len(sys.argv) == 1 else sys.argv[1]
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if len(sys.argv) > 1:
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datetime_input = sys.argv[1]
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else:
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print("没有传入日期时间参数", file=sys.stderr)
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sys.exit(1)
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try:
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# 解析包含时间的日期
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return datetime.strptime(datetime_input, '%Y-%m-%d %H:%M:%S')
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# # 确保日期格式为 YYYY-MM-DD
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# return datetime.strptime(date_input, '%Y-%m-%d')
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except ValueError:
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print("日期格式不正确，请使用YYYY-MM-DD格式", file=sys.stderr)
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sys.exit(1)
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# 加载数据并标记重要节气
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load_start = time.time()
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solar_terms = load_solar_terms(engine)
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logger.info(f"节气加载完成，耗时: {time.time() - load_start:.2f}秒")
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important_terms = ['冬至', '雨水', '谷雨', '夏至', '处暑', '霜降']
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solar_terms['isImportant'] = solar_terms['Solar_Terms'].isin(important_terms).astype(int)
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Map24Jieqi = solar_terms.copy()
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# ========== 读取CSV文件并处理每个日期的卦象 ==========
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read_start = time.time()
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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'
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table = pd.read_csv(csv_path)
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logger.info(f"读取csv文件完成，耗时: {time.time() - read_start:.2f}秒")
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try:
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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'
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piwen_data = pd.read_excel(piwen_path)
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# 打印列名用于调试
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print("批文文件列名:", piwen_data.columns.tolist(), file=sys.stderr)
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# 检查必要的列是否存在
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if not all(col in piwen_data.columns for col in ['卦名', '命卦批文', '八个字基本盘']):
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print("批文文件缺少必要列，请检查Excel文件列名", file=sys.stderr)
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piwen_data = pd.DataFrame(columns=['卦名', '命卦批文', '八个字基本盘'])
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except Exception as e:
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print(f"读取批文文件失败: {str(e)}", file=sys.stderr)
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piwen_data = pd.DataFrame(columns=['卦名', '命卦批文', '八个字基本盘'])
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def get_piwen_info(trigram_name):
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"""根据卦名获取批文和基本盘信息"""
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if not isinstance(trigram_name, str):
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trigram_name = str(trigram_name)
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try:
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match = piwen_data[piwen_data['卦名'] == trigram_name]
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if not match.empty:
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return {
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'piwen': match.iloc[0]['命卦批文'],
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'basic_info': match.iloc[0]['八个字基本盘']
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}
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else:
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print(f"未找到卦名 {trigram_name} 的批文信息", file=sys.stderr)
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return {'piwen': '暂无批文信息', 'basic_info': '暂无基本盘信息'}
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except Exception as e:
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print(f"获取批文信息出错: {str(e)}", file=sys.stderr)
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return {'piwen': '暂无批文信息', 'basic_info': '暂无基本盘信息'}
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# 获取用户输入
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kDate = get_user_date()
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#print("\n计算日期:", kDate.strftime('%Y-%m-%d'))
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# 计算卦象
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Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi(
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Map64Gua, Map24Jieqi, kDate
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)
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# print("日卦:", Gua1Day)
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import json # 导入 JSON 库
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# ========== 计算并返回 JSON 格式的结果 ==========
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# ========== 计算并返回 JSON 格式的结果 ==========
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if __name__ == "__main__":
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print("=== 调试开始 ===", file=sys.stderr) # 打印到 stderr 不会干扰 stdout 的 JSON
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try:
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input_start = time.time()
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kDate = get_user_date()
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logger.info(f"获取用户输入完成，耗时: {time.time() - input_start:.2f}秒")
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# 计算卦象
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calc_start = time.time()
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Gua1Hour, Gua1Day, Gua1Month, Gua1Year, GuaLuck = guaCalc_huangjijingshi(
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Map64Gua, Map24Jieqi, kDate
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)
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logger.info(f"卦象计算完成，耗时: {time.time() - calc_start:.2f}秒")
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# # 计算10年前（当前日期减10年）
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# Yearpre10 = kDate.replace(year=kDate.year - 10)
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# # 计算10年后（当前日期加10年）
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# Yearpast10 = kDate.replace(year=kDate.year + 10)
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# 或者使用relativedelta（更精确处理闰年等情况）
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# 计算年份卦象
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year_start = time.time()
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Yearpre10 = datetime(2010, 1, 1)
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Yearpast10 = datetime(2030, 1, 1,)
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# 生成日期范围（修正end参数）
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date_range = pd.date_range(
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start=Yearpre10.replace(month=1, day=1), # 确保从1月1日开始
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end=Yearpast10.replace(month=1, day=1), # 确保到1月1日结束
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freq='YS' # 每年第一天
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)
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#date_range = pd.date_range(start=Yearpre10, end=Yearpast10, freq='YS') # 每年第一天
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year_gua_list = []
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for date in date_range:
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_, _, _, Gua1Year, _ = guaCalc_huangjijingshi(Map64Gua, Map24Jieqi, date)
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year_gua_list.append({
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'Year': date.year,
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'Trigram': Gua1Year.trigram if hasattr(Gua1Year, 'trigram') else None,
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})
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yearGuaMap = pd.DataFrame(year_gua_list)
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logger.info(f"年份卦象计算完成，耗时: {time.time() - year_start:.2f}秒")
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#========== 计算年份吉凶 ==========
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# 计算年份吉凶
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luck_start = time.time()
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LuckYear = luckCalc_huangjijingshi(Map64Gua, yearGuaMap, GuaLuck)
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logger.info(f"吉凶计算完成，耗时: {time.time() - luck_start:.2f}秒")
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# # 检查 Gua1Day 的类型并正确处理
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# if isinstance(Gua1Day, pd.DataFrame):
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# # 如果是 DataFrame，提取第一行
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# day_data = Gua1Day.iloc[0]
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# elif isinstance(Gua1Day, pd.Series):
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# # 如果是 Series，直接使用
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# day_data = Gua1Day
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# elif isinstance(Gua1Day, dict):
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# # 如果是字典，直接使用
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# day_data = Gua1Day
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# else:
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# raise ValueError("Gua1Day 的类型不支持，必须是 DataFrame、Series 或 dict")
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def format_gua_data(gua_data):
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"""通用格式化卦象数据的函数"""
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if isinstance(gua_data, pd.DataFrame):
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# DataFrame类型 - 取第一行转为字典
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data = gua_data.iloc[0].to_dict()
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elif isinstance(gua_data, pd.Series):
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# Series类型 - 直接转为字典
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data = gua_data.to_dict()
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elif isinstance(gua_data, dict):
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# 已经是字典类型
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data = gua_data
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else:
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# 未知类型返回空字典
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return {}
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# 统一处理字典数据
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return {
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'id': int(data.get('id', 0)),
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'trigram': str(data.get('trigram', '')),
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'yaoAll': str(data.get('yaoAll', '')),
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'yao1': int(data.get('yao1', 0)),
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'yao2': int(data.get('yao2', 0)),
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'yao3': int(data.get('yao3', 0)),
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'yao4': int(data.get('yao4', 0)),
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'yao5': int(data.get('yao5', 0)),
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'yao6': int(data.get('yao6', 0)),
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'value_2binary': int(data.get('value_2binary', 0)),
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'change_omit': int(data.get('change_omit', 0)),
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'type': str(data.get('Type', 'unknown'))
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}
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# 构建结果字典，确保所有值是 Python 原生类型
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# result = {
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# 'date': kDate.strftime('%Y-%m-%d'),
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# 'day_gua': {
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# 'id': int(day_data.get('id', 0)), # 如果没有值，使用默认值 0
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# 'trigram': str(day_data.get('trigram', '')), # 如果没有值，使用空字符串
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# 'yaoAll': str(day_data.get('yaoAll', '')), # 如果没有值，使用空字符串
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# 'yao1': int(day_data.get('yao1', 0)), # 如果没有值，使用默认值 0
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# 'yao2': int(day_data.get('yao2', 0)), # 如果没有值，使用默认值 0
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# 'yao3': int(day_data.get('yao3', 0)), # 如果没有值，使用默认值 0
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# 'yao4': int(day_data.get('yao4', 0)), # 如果没有值，使用默认值 0
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# 'yao5': int(day_data.get('yao5', 0)), # 如果没有值，使用默认值 0
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# 'yao6': int(day_data.get('yao6', 0)), # 如果没有值，使用默认值 0
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# 'value_2binary': int(day_data.get('value_2binary', 0)), # 如果没有值，使用默认值 0
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# 'change_omit': int(day_data.get('change_omit', 0)), # 如果没有值，使用默认值 0
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# 'type': str(day_data.get('Type', 'day')) # 如果没有值，使用默认值 'day'
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# }
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# }
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# 构建完整结果
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build_start = time.time()
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result = {
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'date': kDate.strftime('%Y-%m-%d'),
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'year_gua': {
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**format_gua_data(Gua1Year),
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**get_piwen_info(format_gua_data(Gua1Year).get('trigram', ''))
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},
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'month_gua': {
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**format_gua_data(Gua1Month),
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**get_piwen_info(format_gua_data(Gua1Month).get('trigram', ''))
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},
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'day_gua': {
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**format_gua_data(Gua1Day),
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**get_piwen_info(format_gua_data(Gua1Day).get('trigram', ''))
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},
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'hour_gua': {
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**format_gua_data(Gua1Hour),
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**get_piwen_info(format_gua_data(Gua1Hour).get('trigram', ''))
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},
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'luck_gua': {
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**format_gua_data(GuaLuck),
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**get_piwen_info(format_gua_data(GuaLuck).get('trigram', ''))
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},
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'luck_years': [
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{
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'year': row['Year'],
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'trigram': row['trigram'],
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'yaoAll': row['yaoAll'],
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**get_piwen_info(row['trigram'])
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} for _, row in LuckYear.iterrows()
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] if isinstance(LuckYear, pd.DataFrame) else []
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}
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logger.info(f"结果构建完成，耗时: {time.time() - build_start:.2f}秒")
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# 在打印 JSON 前检查内容
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print("=== 要输出的 JSON 内容 ===", file=sys.stderr)
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print(result, file=sys.stderr)
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# 输出 JSON 格式的结果
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# print(json.dumps(result, ensure_ascii=False, indent=4)) # 添加 indent 参数更好查看格式
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# 输出结果
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output_start = time.time()
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print(json.dumps(result, ensure_ascii=False, indent=2))
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logger.info(f"结果输出完成，耗时: {time.time() - output_start:.2f}秒")
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total_time = time.time() - total_start
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logger.info(f"=== API 执行完成，总耗时: {total_time:.2f}秒 ===")
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except Exception as e:
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import traceback
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traceback.print_exc(file=sys.stderr) # 打印错误堆栈，帮助调试
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print(f"计算错误: {str(e)}", file=sys.stderr)
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sys.exit(1) |