石油焦日度预测，调试完成

lib/dataread.py

@@ -2223,16 +2223,17 @@ def addtimecharacteristics(df, dataset):
 # 从数据库获取百川数据，接收一个百川id列表，返回df格式的数据
 def get_baichuan_data(baichuanidnamedict):
     baichuanidlist = [str(k) for k in baichuanidnamedict.keys()]
+    baichuanidlist= [f"'{id}'" for id in baichuanidlist]
     # 连接数据库
     db = config.db_mysql
+    if db is None:
         db.connect()
     # 执行SQL查询 select BAICHUAN_ID,DATA_DATE,DATA_VALUE from V_TBL_BAICHUAN_YINGFU_VALUE where BAICHUAN_ID in ('1588348470396475286','1666');
     sql = f"SELECT  BAICHUAN_ID,DATA_DATE,DATA_VALUE  FROM {global_config['baichuan_table_name']} WHERE BAICHUAN_ID in ({','.join(baichuanidlist)})"
 
     # 获取查询结果
     results = db.execute_query(sql)
-    formatted_results = [tuple(item) for item in results]
+    df = pd.DataFrame(results, columns=[
-    df = pd.DataFrame(formatted_results, columns=[
                       'BAICHUAN_ID', 'DATA_DATE', 'DATA_VALUE'])
     df['BAICHUAN_ID'] = df['BAICHUAN_ID'].astype('string')
     df.to_csv('百川数据test.csv', index=False)

main_shiyoujiao_lvyong.py

@@ -32,6 +32,7 @@ global_config.update({
     'modelsindex': modelsindex,
     'rote': rote,
     'bdwd_items': bdwd_items,
+    'baichuanidnamedict': baichuanidnamedict,
 
     # 特征工程开关
     'is_del_corr': is_del_corr,
@@ -429,16 +430,8 @@ def predict_main():
     logger.info('制作报告end')
     logger.info('模型训练完成')
 
-    # push_market_value()
+    push_market_value()
 
-    # # LSTM 单变量模型
-    # ex_Lstm(df,input_seq_len=input_size,output_seq_len=horizon,is_debug=is_debug,dataset=dataset)
-
-    # # lstm 多变量模型
-    # ex_Lstm_M(df,n_days=input_size,out_days=horizon,is_debug=is_debug,datasetpath=dataset)
-
-    # # GRU 模型
-    # # ex_GRU(df)
 
     # 发送邮件
     # m = SendMail(