添加mysql执行封装类
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workpc
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@ -2,6 +2,7 @@ import logging
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import os
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import logging.handlers
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import datetime
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from lib.tools import MySQLDB,SQLiteHandler
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# eta 接口token
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@ -21,8 +22,9 @@ edbcodelist = ['CO1 Comdty', 'ovx index', 'C2404194834', 'C2404199738', 'dxy cur
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'DOESCRUD Index', 'WTRBM1 EEGC Index', 'FVHCM1 INDEX', 'doedtprd index', 'CFFDQMMN INDEX',
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'C2403083739', 'C2404167878', 'C2403250571', 'lmcads03 lme comdty', 'GC1 COMB Comdty',
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'C2404171822','C2404167855',
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'W000825','W000826','G.IPE', # 美国汽柴油
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'S5131019','ID00135604','FSGAM1 Index','S5120408','ID00136724'] # 新加坡汽柴油
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# 'W000825','W000826','G.IPE', # 美国汽柴油
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# 'S5131019','ID00135604','FSGAM1 Index','S5120408','ID00136724', # 新加坡汽柴油
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]
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# 临时写死用指定的列,与上面的edbcode对应，后面更改
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edbnamelist = [
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@ -32,8 +34,8 @@ edbnamelist = [
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'C2403128043','C2403150124','FVHCM1 INDEX','doedtprd index','CFFDQMMN INDEX',
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'C2403083739','C2404167878',
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'GC1 COMB Comdty','C2404167855',
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'A汽油价格','W000826','ICE柴油价格',
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'新加坡(含硫0.05%) 柴油现货价','柴油：10ppm：国际市场：FOB中间价：新加坡（日）','Bloomberg Commodity Fair Value Singapore Mogas 92 Swap Month 1','97#汽油FOB新加坡现货价','无铅汽油：97#：国际市场：FOB中间价：新加坡（日）'
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# 'A汽油价格','W000826','ICE柴油价格',
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# '新加坡(含硫0.05%) 柴油现货价','柴油：10ppm：国际市场：FOB中间价：新加坡（日）','Bloomberg Commodity Fair Value Singapore Mogas 92 Swap Month 1','97#汽油FOB新加坡现货价','无铅汽油：97#：国际市场：FOB中间价：新加坡（日）'
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]
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@ -195,7 +197,7 @@ warning_data = {
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### 开关
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is_train = True # 是否训练
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is_debug = False # 是否调试
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is_debug = True # 是否调试
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is_eta = True # 是否使用eta接口
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is_timefurture = True # 是否使用时间特征
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is_fivemodels = False # 是否使用之前保存的最佳的5个模型
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@ -205,10 +207,26 @@ is_update_eta = False # 预测结果上传到eta
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is_update_report = False # 是否上传报告
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is_update_warning_data = False # 是否上传预警数据
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### 北京环境数据库jbsh_test
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# url: jdbc:mysql://192.168.101.27:3306/jingbo_test?autoReconnect=true&useUnicode=true&characterEncoding=utf8&zeroDateTimeBehavior=convertToNull&transformedBitIsBoolean=true&useSSL=false&serverTimezone=GMT%2B8&nullCatalogMeansCurrent=true
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host = '192.168.101.27'
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prot = 3306
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username ='root'
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password = '123456'
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dbname = 'jingbo_test'
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table_name = 'v_tbl_crude_oil_warning'
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db_mysql = MySQLDB(host=host, user=username, password=password, database=dbname)
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# 连接到数据库
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db_mysql.connect()
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# 数据截取日期
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start_year = 2013 # 数据开始年份
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end_time = '' # 数据截取日期
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freq = 'M' # 时间频率，"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日
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freq = 'B' # 时间频率，"D": 天 "W": 周"M": 月"Q": 季度"A": 年 "H": 小时 "T": 分钟 "S": 秒 "B": 工作日
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delweekenday = True if freq == 'B' else False # 是否删除周末数据
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is_corr = False # 特征是否参与滞后领先提升相关系数
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add_kdj = False # 是否添加kdj指标
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@ -239,6 +257,8 @@ dataset = 'yuanyoudataset' # 数据集文件夹
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# 数据库名称
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db_name = os.path.join(dataset,'jbsh_yuanyou.db')
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sqlitedb = SQLiteHandler(db_name)
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sqlitedb.connect()
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settings = f'{input_size}-{horizon}-{train_steps}--{k}-{data_set}-{y}'
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# 获取日期时间
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@ -40,8 +40,8 @@ pdfmetrics.registerFont(TTFont('SimSun', 'SimSun.ttf'))
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plt.rcParams['font.sans-serif'] = ['SimHei'] # 用来正常显示中文标签
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plt.rcParams['axes.unicode_minus'] = False # 用来正常显示负号
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# from config_jingbo import *
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from config_juxiting import *
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from config_jingbo import *
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# from config_juxiting import *
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72
lib/tools.py
72
lib/tools.py
@ -4,7 +4,6 @@ import numpy as np
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import pandas as pd
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import matplotlib.pyplot as plt
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import seaborn as sns
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from config_jingbo import logger
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from sklearn import metrics
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import random, string, base64, hmac, hashlib
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from reportlab.pdfbase import pdfmetrics # 注册字体
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@ -21,10 +20,11 @@ import smtplib
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from email.mime.text import MIMEText
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from email.mime.multipart import MIMEMultipart
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import sqlite3
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import pymysql
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import tkinter as tk
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from tkinter import messagebox
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global logger
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def timeit(func):
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'''计时装饰器'''
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def wrapper(*args, **kwargs):
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@ -446,5 +446,73 @@ class SQLiteHandler:
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else:
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print(f"Column '{column_name}' already exists in table '{table_name}'.")
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import logging
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class MySQLDB:
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def __init__(self, host, user, password, database):
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self.host = host
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self.user = user
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self.password = password
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self.database = database
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self.connection = None
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self.cursor = None
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def connect(self):
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try:
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self.connection = pymysql.connect(
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host=self.host,
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user=self.user,
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password=self.password,
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database=self.database,
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charset='utf8mb4',
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cursorclass=pymysql.cursors.DictCursor
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)
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self.cursor = self.connection.cursor()
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logging.info("Connected to the database successfully.")
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except pymysql.Error as e:
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logging.error(f"Error connecting to the database: {e}")
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def execute_query(self, query):
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try:
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self.cursor.execute(query)
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result = self.cursor.fetchall()
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return result
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except pymysql.Error as e:
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logging.error(f"Error executing query: {e}")
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return None
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def execute_insert(self, query, values):
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try:
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self.cursor.execute(query, values)
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self.connection.commit()
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logging.info("Insert operation successful.")
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except pymysql.Error as e:
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logging.error(f"Error executing insert: {e}")
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self.connection.rollback()
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def execute_update(self, query, values):
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try:
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self.cursor.execute(query, values)
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self.connection.commit()
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logging.info("Update operation successful.")
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except pymysql.Error as e:
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logging.error(f"Error executing update: {e}")
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self.connection.rollback()
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def execute_delete(self, query, values):
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try:
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self.cursor.execute(query, values)
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self.connection.commit()
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logging.info("Delete operation successful.")
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except pymysql.Error as e:
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logging.error(f"Error executing delete: {e}")
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self.connection.rollback()
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def close(self):
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if self.cursor:
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self.cursor.close()
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if self.connection:
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self.connection.close()
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logging.info("Database connection closed.")
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if __name__ == '__main__':
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print('This is a tool, not a script.')
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@ -1,15 +1,13 @@
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# 读取配置
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from config_jingbo import *
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from lib.dataread import *
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from lib.tools import *
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# from lib.tools import *
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from models.nerulforcastmodels import ex_Model,model_losss,model_losss_juxiting,brent_export_pdf,tansuanli_export_pdf,pp_export_pdf,model_losss_juxiting
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import glob
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import torch
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torch.set_float32_matmul_precision("high")
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sqlitedb = SQLiteHandler(db_name)
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sqlitedb.connect()
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def predict_main():
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