修改数据库连接

hlfx.py

@@ -19,85 +19,96 @@ fre = '1d'
 cursor = db.cursor()
 # cursor.execute("select table_name from information_schema.tables where table_schema='qbh_hlfx_backup' and table_name like {}".format('\'%{}\''.format(fre)))
 cursor.execute('show tables like {}'.format('\'%{}\''.format(fre)))
-table_list = [tuple[0] for tuple in cursor.fetchall()]
+# table_list = [tuple[0] for tuple in cursor.fetchall()]
 
 # print(table_list)
 stk = threading.local()
-engine = locals()
-engine_tosql = locals()
+
 
 
 # 主程序
 # 找顶底（hdx lfx）分型
-def hlfx(table_list, engine, engine_tosql):
+def hlfx(table_list, engine, tosql):
     for table in table_list:
         # stk.fxdf = pd.DataFrame(columns=('date', 'open', 'close', 'high', 'low', 'volume', 'money', 'HL'))
-        stk.df_day = pd.read_sql_query('select date,open,close,high,low,volume,money,HL from %s' % table, engine)
-        for i in stk.df_day.index:
-            m = i - 1
-            if i <= 3:
-                # stk.fxdf = pd.concat([stk.fxdf, stk.df_day.iloc[[i]]], ignore_index=True)
-                stk.df_day.loc[i, 'HL'] = '-'
-            # 底
-            elif ((stk.df_day.loc[i,'high']>stk.df_day.loc[i-1,'high']) and (stk.df_day.loc[i-2,'high']>stk.df_day.loc[i-1,'high'])):
-                # if ((stk.df_day.loc[i-2, 'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-3,'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-1,'date'] != stk.fxdf.iloc[-1,0])):
-                    # stk.fxdf = pd.concat([stk.fxdf, stk.df_day.iloc[[i]]], ignore_index=True)
-                stk.df_day.loc[i, 'HL'] = 'L*'
-                while m:
-                    if m == 1:
-                        stk.df_day.loc[i, 'HL'] = 'l'
-                    elif stk.df_day.loc[m, 'HL'] == 'H' or stk.df_day.loc[m, 'HL'] == 'h':
-                        if(i-m) > 3:
-                            stk.df_day.loc[i, 'HL'] = 'L'
-                        break
-                    elif (stk.df_day.loc[m, 'HL'] == 'L' or stk.df_day.loc[m, 'HL'] == 'l'):
-                        if stk.df_day.loc[i-1, 'low'] < stk.df_day.loc[m-1, 'low']:
-                            # 前一个为顶，且中间存在不包含 or 更低的底
-                            stk.df_day.loc[i, 'HL'] = 'L'
-                            break
-                        else:
-                            break
-                    m = m-1
-
-            # 顶
-            elif ((stk.df_day.loc[i,'high']<stk.df_day.loc[i-1,'high']) and (stk.df_day.loc[i-2,'high']<stk.df_day.loc[i-1,'high'])):
-                # if ((stk.df_day.loc[i-2, 'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-3,'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-1,'date'] != stk.fxdf.iloc[-1,0])):
-                #     stk.fxdf = pd.concat([stk.fxdf, stk.df_day.iloc[[i]]], ignore_index=True)
-                stk.df_day.loc[i, 'HL'] = 'H*'
-                while m:
-                    if m == 1:
-                        stk.df_day.loc[i, 'HL'] = 'h'
-                    elif stk.df_day.loc[m, 'HL'] == 'L' or stk.df_day.loc[m, 'HL'] == 'l':
-                        if i-m > 3:
-                            stk.df_day.loc[i, 'HL'] = 'H'
-                            stk.df_day.loc[i, 9] = stk.df_day.loc[i, 'close'] - stk.df_day.loc[m, 'close']
-                        break
-                    elif (stk.df_day.loc[m, 'HL'] == 'H' or stk.df_day.loc[m, 'HL'] == 'h'):
-                        if stk.df_day.loc[i-1, 'high'] > stk.df_day.loc[m-1, 'high']:
-                            # 前一个为底，且中间存在不包含 or 更高的顶
-                            stk.df_day.loc[i, 'HL'] = 'H'
-                            break
-                        break
-                    m = m-1
-            else:
-                stk.df_day.loc[i, 'HL'] = '-'
+        # stk.df_day = pd.read_sql_query('select date,open,close,high,low,volume,money,HL from %s' % table, engine)
+        print(engine)
+        print(tosql)
+        # stk.df_day.to_sql(name='%s' % table, con=tosql, index=True, if_exists='replace')
+        # with tosql.connect() as con_backup:
+        #     con_backup.execute('ALTER TABLE %s ADD PRIMARY KEY (`date`);' % table)
+        # for i in stk.df_day.index:
+        #     m = i - 1
+        #     if i <= 3:
+        #         # stk.fxdf = pd.concat([stk.fxdf, stk.df_day.iloc[[i]]], ignore_index=True)
+        #         stk.df_day.loc[i, 'HL'] = '-'
+        #     # 底
+        #     elif ((stk.df_day.loc[i,'high']>stk.df_day.loc[i-1,'high']) and (stk.df_day.loc[i-2,'high']>stk.df_day.loc[i-1,'high'])):
+        #         # if ((stk.df_day.loc[i-2, 'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-3,'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-1,'date'] != stk.fxdf.iloc[-1,0])):
+        #             # stk.fxdf = pd.concat([stk.fxdf, stk.df_day.iloc[[i]]], ignore_index=True)
+        #         stk.df_day.loc[i, 'HL'] = 'L*'
+        #         while m:
+        #             if m == 1:
+        #                 stk.df_day.loc[i, 'HL'] = 'l'
+        #             elif stk.df_day.loc[m, 'HL'] == 'H' or stk.df_day.loc[m, 'HL'] == 'h':
+        #                 if(i-m) > 3:
+        #                     stk.df_day.loc[i, 'HL'] = 'L'
+        #                 break
+        #             elif (stk.df_day.loc[m, 'HL'] == 'L' or stk.df_day.loc[m, 'HL'] == 'l'):
+        #                 if stk.df_day.loc[i-1, 'low'] < stk.df_day.loc[m-1, 'low']:
+        #                     # 前一个为顶，且中间存在不包含 or 更低的底
+        #                     stk.df_day.loc[i, 'HL'] = 'L'
+        #                     break
+        #                 else:
+        #                     break
+        #             m = m-1
+        #
+        #     # 顶
+        #     elif ((stk.df_day.loc[i,'high']<stk.df_day.loc[i-1,'high']) and (stk.df_day.loc[i-2,'high']<stk.df_day.loc[i-1,'high'])):
+        #         # if ((stk.df_day.loc[i-2, 'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-3,'date'] != stk.fxdf.iloc[-1,0]) and (stk.df_day.loc[i-1,'date'] != stk.fxdf.iloc[-1,0])):
+        #         #     stk.fxdf = pd.concat([stk.fxdf, stk.df_day.iloc[[i]]], ignore_index=True)
+        #         stk.df_day.loc[i, 'HL'] = 'H*'
+        #         while m:
+        #             if m == 1:
+        #                 stk.df_day.loc[i, 'HL'] = 'h'
+        #             elif stk.df_day.loc[m, 'HL'] == 'L' or stk.df_day.loc[m, 'HL'] == 'l':
+        #                 if i-m > 3:
+        #                     stk.df_day.loc[i, 'HL'] = 'H'
+        #                     stk.df_day.loc[i, 9] = stk.df_day.loc[i, 'close'] - stk.df_day.loc[m, 'close']
+        #                 break
+        #             elif (stk.df_day.loc[m, 'HL'] == 'H' or stk.df_day.loc[m, 'HL'] == 'h'):
+        #                 if stk.df_day.loc[i-1, 'high'] > stk.df_day.loc[m-1, 'high']:
+        #                     # 前一个为底，且中间存在不包含 or 更高的顶
+        #                     stk.df_day.loc[i, 'HL'] = 'H'
+        #                     break
+        #                 break
+        #             m = m-1
+        #     else:
+        #         stk.df_day.loc[i, 'HL'] = '-'
         # stk.df_day.to_sql('%s' % table, con=engine, index=True, if_exists='replace', chunksize=20000)
         # print(table, '\n', stk.df_day)
-        stk.df_day.to_csv('/Users/daniel/Library/CloudStorage/OneDrive-个人/个人/python_stocks/20220212hlfx2/hlfx%s.csv' % table)
-        stk.df_day.to_sql('%s' % table, con=engine_tosql, index=True, if_exists='replace')
-        with engine_tosql.connect() as con_backup:
-            con_backup.execute('ALTER TABLE %s ADD PRIMARY KEY (`date`);' % table)
+        # stk.df_day.to_csv('/Users/daniel/Library/CloudStorage/OneDrive-个人/个人/python_stocks/20220212hlfx2/hlfx%s.csv' % table)
+        # stk.df_day.to_sql(name='%s' % table, con=tosql, index=True, if_exists='replace')
+        # with tosql.connect() as con_backup:
+        #     con_backup.execute('ALTER TABLE %s ADD PRIMARY KEY (`date`);' % table)
 
-# table_list = ['stk002237_1d','stk000002_1d']
+table_list = ['stk002237_1d','stk000004_1d']
 # engine = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh_hlfx_backup?charset=utf8')
-# hlfx(table_list, engine)
+# tosql = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/bb22?charset=utf8')
+# hlfx(table_list, engine, tosql)
 
 step = 50
 thread_list = []
+engine = []
+tosql = []
 for i in range(0, len(table_list), step):
-    engine_tosql[i] = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/hlfx_backup?charset=utf8')
-    engine[i] = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh_hlfx_backup?charset=utf8')
-    threading.Thread(target=hlfx, args=(table_list[i:i + step], engine[i], engine_tosql[i])).start()
+    engine.append(create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh_hlfx_backup?charset=utf8'))
+    tosql.append(create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/bb22?charset=utf8'))
+    threading.Thread(target=hlfx, args=(table_list[i:i + step], engine[i], tosql[i],)).start()
+
+
+
+