自循环 30m 1d

.idea/misc.xml

@@ -1,4 +1,4 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <project version="4">
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.8 (jqdata)" project-jdk-type="Python SDK" />
 </project>

.idea/stock.iml

@@ -2,7 +2,7 @@
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
     <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.8" jdkType="Python SDK" />
+    <orderEntry type="jdk" jdkName="Python 3.8 (jqdata)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
     <orderEntry type="module" module-name="stocks_to_sql" />
     <orderEntry type="module" module-name="quantify01" />

updata_qbh_hlfx.py

@@ -9,199 +9,216 @@ import datetime
 auth('18019403367', 'Qwer4321')
 
 stocks = list(get_all_securities(['stock'], date=dt.today().strftime('%Y-%m-%d')).index)
-stocks = stocks[0:1]
+# stocks = stocks[0:1]
 
 start = dt.now()
 # 确定级别
 # 注意修改time delta
-fre = '1d'
-# 连接数据库
-db = pymysql.connect(host='localhost',
-                     user='root',
-                     port=3307,
-                     password='r6kEwqWU9!v3',
-                     database='hlfx')
-engine2 = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/hlfx?charset=utf8')
-engine = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/stocks?charset=utf8')
-cursor = db.cursor()
-cursor.execute("show tables like '%%%s%%' "% fre)
-table_list = [tuple[0] for tuple in cursor.fetchall()]
+# fre = '30m'
+for fre in ['30m', '1d']:
+    # 连接数据库
+    db = pymysql.connect(host='localhost',
+                         user='root',
+                         port=3307,
+                         password='r6kEwqWU9!v3',
+                         database='hlfx')
+    cursor = db.cursor()
+    cursor.execute("show tables like '%%%s%%' " % fre)
+    table_list = [tuple[0] for tuple in cursor.fetchall()]
+    print('取得 table_list %s' % fre)
 
-print(table_list)
-stk = locals()
-thd = threading.local()
+    stk = locals()
+    thd = threading.local()
 
-for stock in stocks:
-    print(stock)
-    if ('stk%s_%s' % (stock, fre)) in table_list:
-        # 有历史数据
-        index_len = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine2).iloc[-1, 0]
-        # 注意修改time delta
-        startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine2).iloc[-1, 1]
-        # startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine2).iloc[-1, 1] + datetime.timedelta(minutes= 5)
-        thd.get_price = pd.read_sql_query(
-            'select date,open,close,high,low,volume,money from `stk%s_%s`' % (stock, fre), engine)
-        thd.get_price = thd.get_price.loc[thd.get_price['date'] > startdate]
-        thd.df_day = pd.read_sql_query(
-            'select date,open,close,high,low,volume,money,HL from `stk%s_%s`' % (stock, fre), engine2)
-        # 先处理去包含
-        for i in thd.get_price.index:
-            # 不包含
-            if (thd.df_day.iloc[-1, 3] > thd.get_price.loc[i, 'high']
-                and thd.df_day.iloc[-1, 4] > thd.get_price.loc[i, 'low']) \
-                    or (thd.df_day.iloc[-1, 3] < thd.get_price.loc[i, 'high']
-                        and thd.df_day.iloc[-1, 4] < thd.get_price.loc[i, 'low']):
-                thd.df_day = pd.concat([thd.df_day, thd.get_price.loc[[i]]], ignore_index=True)
-                print(thd.df_day)
-            # 包含
-            else:
-                # (new_df.iloc[-1,3]>=df_day.loc[i,'high'] and new_df.iloc[-1,4]<= df_day.loc[i,'low']):
-                # 左高，下降
-                if thd.df_day.iloc[-2, 3] > thd.df_day.iloc[-1, 3]:
-                    thd.df_day.iloc[-1, 3] = min(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
-                    thd.df_day.iloc[-1, 4] = min(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
-                else:
-                    # 右高，上升
-                    thd.df_day.iloc[-1, 3] = max(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
-                    thd.df_day.iloc[-1, 4] = max(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
+    def hlfx(table_list, engine, engine2):
+        for stock in stocks:
+            print(stock)
+            if ('stk%s_%s' % (stock, fre)) in table_list:
+                # 有历史数据
+                index_len = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine2).iloc[-1, 0]
+                # 注意修改time delta
+                startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine2).iloc[-1, 1]
+                # startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine2).iloc[-1, 1] + datetime.timedelta(minutes= 5)
+                thd.get_price = pd.read_sql_query(
+                    'select date,open,close,high,low,volume,money from `stk%s_%s`' % (stock, fre), engine)
+                thd.get_price = thd.get_price.loc[thd.get_price['date'] > startdate]
+                thd.df_day = pd.read_sql_query(
+                    'select date,open,close,high,low,volume,money,HL from `stk%s_%s`' % (stock, fre), engine2)
+                # 先处理去包含
+                for i in thd.get_price.index:
+                    # 不包含
+                    if (thd.df_day.iloc[-1, 3] > thd.get_price.loc[i, 'high']
+                        and thd.df_day.iloc[-1, 4] > thd.get_price.loc[i, 'low']) \
+                            or (thd.df_day.iloc[-1, 3] < thd.get_price.loc[i, 'high']
+                                and thd.df_day.iloc[-1, 4] < thd.get_price.loc[i, 'low']):
+                        thd.df_day = pd.concat([thd.df_day, thd.get_price.loc[[i]]], ignore_index=True)
+                        print(thd.df_day)
+                    # 包含
+                    else:
+                        # (new_df.iloc[-1,3]>=df_day.loc[i,'high'] and new_df.iloc[-1,4]<= df_day.loc[i,'low']):
+                        # 左高，下降
+                        if thd.df_day.iloc[-2, 3] > thd.df_day.iloc[-1, 3]:
+                            thd.df_day.iloc[-1, 3] = min(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
+                            thd.df_day.iloc[-1, 4] = min(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
+                        else:
+                            # 右高，上升
+                            thd.df_day.iloc[-1, 3] = max(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
+                            thd.df_day.iloc[-1, 4] = max(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
+                            # 寻找顶底分型
+                if len(thd.df_day.index) > 2:
                     # 寻找顶底分型
-        if len(thd.df_day.index) > 2:
-            # 寻找顶底分型
-            for x in range(index_len, len(thd.df_day.index)):
-                m = x - 1
-                # 底
-                if ((thd.df_day.loc[x, 'high'] > thd.df_day.loc[x - 1, 'high']) and (
-                        thd.df_day.loc[x - 2, 'high'] > thd.df_day.loc[x - 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)
-                    thd.df_day.loc[x, 'HL'] = 'L*'
-                    while m:
-                        if thd.df_day.loc[m, 'HL'] == 'H':
-                            if (x - m) > 3:
-                                thd.df_day.loc[x, 'HL'] = 'L'
-                                if x == len(thd.df_day.index) - 1:
-                                    print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '买买买买买！！')
-                            break
-                        elif (thd.df_day.loc[m, 'HL'] == 'L'):
-                            if thd.df_day.loc[x - 1, 'low'] < thd.df_day.loc[m - 1, 'low']:
-                                # 前一个为底，且中间存在不包含 or 更低的底
-                                thd.df_day.loc[x, 'HL'] = 'L'
-                                if x == len(thd.df_day.index) - 1:
-                                    # pass
-                                    print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '中继后的底————买吗？！')
-                                break
-                            else:
-                                break
-                        m = m - 1
-                # 顶
-                elif ((thd.df_day.loc[x, 'high'] < thd.df_day.loc[x - 1, 'high']) and (
-                        thd.df_day.loc[x - 2, 'high'] < thd.df_day.loc[x - 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)
-                    thd.df_day.loc[x, 'HL'] = 'H*'
-                    while m:
-                        if thd.df_day.loc[m, 'HL'] == 'L':
-                            if x - m > 3:
-                                thd.df_day.loc[x, 'HL'] = 'H'
-                                if x == len(thd.df_day.index) - 1:
-                                    # print(stock, '!!!!!!!', '\n', '卖卖卖卖卖卖卖!')
-                                    pass
-                                thd.df_day.loc[x, 9] = thd.df_day.loc[x, 'close'] - thd.df_day.loc[m, 'close']
-                            break
-                        elif (thd.df_day.loc[m, 'HL'] == 'H'):
-                            if thd.df_day.loc[x - 1, 'high'] > thd.df_day.loc[m - 1, 'high']:
-                                # 前一个为顶，且中间存在不包含 or 更高的顶
-                                thd.df_day.loc[x, 'HL'] = 'H'
-                                if x == len(thd.df_day.index) - 1:
-                                    pass
-                                    # print(stock, '/\/\/\/\/\/\/', '一顶更有一顶高！')
-                                break
-                            break
-                        m = m - 1
-                else:
-                    thd.df_day.loc[x, 'HL'] = '-'
+                    for x in range(index_len, len(thd.df_day.index)):
+                        m = x - 1
+                        # 底
+                        if ((thd.df_day.loc[x, 'high'] > thd.df_day.loc[x - 1, 'high']) and (
+                                thd.df_day.loc[x - 2, 'high'] > thd.df_day.loc[x - 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)
+                            thd.df_day.loc[x, 'HL'] = 'L*'
+                            while m:
+                                if thd.df_day.loc[m, 'HL'] == 'H':
+                                    if (x - m) > 3:
+                                        thd.df_day.loc[x, 'HL'] = 'L'
+                                        if x == len(thd.df_day.index) - 1:
+                                            print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '买买买买买！！')
+                                    break
+                                elif (thd.df_day.loc[m, 'HL'] == 'L'):
+                                    if thd.df_day.loc[x - 1, 'low'] < thd.df_day.loc[m - 1, 'low']:
+                                        # 前一个为底，且中间存在不包含 or 更低的底
+                                        thd.df_day.loc[x, 'HL'] = 'L'
+                                        if x == len(thd.df_day.index) - 1:
+                                            # pass
+                                            print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '中继后的底————买吗？！')
+                                        break
+                                    else:
+                                        break
+                                m = m - 1
+                        # 顶
+                        elif ((thd.df_day.loc[x, 'high'] < thd.df_day.loc[x - 1, 'high']) and (
+                                thd.df_day.loc[x - 2, 'high'] < thd.df_day.loc[x - 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)
+                            thd.df_day.loc[x, 'HL'] = 'H*'
+                            while m:
+                                if thd.df_day.loc[m, 'HL'] == 'L':
+                                    if x - m > 3:
+                                        thd.df_day.loc[x, 'HL'] = 'H'
+                                        if x == len(thd.df_day.index) - 1:
+                                            # print(stock, '!!!!!!!', '\n', '卖卖卖卖卖卖卖!')
+                                            pass
+                                        thd.df_day.loc[x, 9] = thd.df_day.loc[x, 'close'] - thd.df_day.loc[m, 'close']
+                                    break
+                                elif (thd.df_day.loc[m, 'HL'] == 'H'):
+                                    if thd.df_day.loc[x - 1, 'high'] > thd.df_day.loc[m - 1, 'high']:
+                                        # 前一个为顶，且中间存在不包含 or 更高的顶
+                                        thd.df_day.loc[x, 'HL'] = 'H'
+                                        if x == len(thd.df_day.index) - 1:
+                                            pass
+                                            # print(stock, '/\/\/\/\/\/\/', '一顶更有一顶高！')
+                                        break
+                                    break
+                                m = m - 1
+                        else:
+                            thd.df_day.loc[x, 'HL'] = '-'
 
-        # 更新数据库
-        thd.df_day[index_len + 1:].to_sql('stk%s_%s' % (stock, fre), con=engine2, index=True, if_exists='append')
-    else:
-        # 没有历史数据表
-        thd.df_day = pd.DataFrame(columns=('date', 'open', 'close', 'high', 'low', 'volume', 'money', 'HL'))
-        thd.get_price = pd.read_sql_query(
-            'select date,open,close,high,low,volume,money from `stk%s_%s`' % (stock, fre), engine)
-        # 先处理去包含
-        for i in thd.get_price.index:
-            if i == 0 or i == 1:
-                thd.df_day = pd.concat([thd.df_day, thd.get_price.iloc[[i]]], ignore_index=True)
-            # 不包含
-            elif (thd.df_day.iloc[-1, 3] > thd.get_price.loc[i, 'high']
-                  and thd.df_day.iloc[-1, 4] > thd.get_price.loc[i, 'low']) \
-                    or (thd.df_day.iloc[-1, 3] < thd.get_price.loc[i, 'high']
-                        and thd.df_day.iloc[-1, 4] < thd.get_price.loc[i, 'low']):
-                thd.df_day = pd.concat([thd.df_day, thd.get_price.loc[[i]]], ignore_index=True)
-            # 包含
+                # 更新数据库
+                thd.df_day[index_len + 1:].to_sql('stk%s_%s' % (stock, fre), con=engine2, index=True, if_exists='append')
             else:
-                # 左高，下降
-                if thd.df_day.iloc[-2, 3] > thd.df_day.iloc[-1, 3]:
-                    thd.df_day.iloc[-1, 3] = min(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
-                    thd.df_day.iloc[-1, 4] = min(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
-                else:
-                    # 右高，上升
-                    thd.df_day.iloc[-1, 3] = max(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
-                    thd.df_day.iloc[-1, 4] = max(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
-        if len(thd.df_day.index) > 2:
-            # 寻找顶底分型
-            for x in range(index_len, len(thd.df_day.index)):
-                m = x - 1
-                # 底
-                if ((thd.df_day.loc[x, 'high'] > thd.df_day.loc[x - 1, 'high']) and (
-                        thd.df_day.loc[x - 2, 'high'] > thd.df_day.loc[x - 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)
-                    thd.df_day.loc[x, 'HL'] = 'L*'
-                    while m:
-                        if thd.df_day.loc[m, 'HL'] == 'H':
-                            if (x - m) > 3:
-                                thd.df_day.loc[x, 'HL'] = 'L'
-                                if x == len(thd.df_day.index) - 1:
-                                    print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '买买买买买！！')
-                            break
-                        elif (thd.df_day.loc[m, 'HL'] == 'L'):
-                            if thd.df_day.loc[x - 1, 'low'] < thd.df_day.loc[m - 1, 'low']:
-                                # 前一个为底，且中间存在不包含 or 更低的底
-                                thd.df_day.loc[x, 'HL'] = 'L'
-                                if x == len(thd.df_day.index) - 1:
-                                    # pass
-                                    print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '中继后的底————买吗？！')
-                                break
-                            else:
-                                break
-                        m = m - 1
-                # 顶
-                elif ((thd.df_day.loc[x, 'high'] < thd.df_day.loc[x - 1, 'high']) and (
-                        thd.df_day.loc[x - 2, 'high'] < thd.df_day.loc[x - 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)
-                    thd.df_day.loc[x, 'HL'] = 'H*'
-                    while m:
-                        if thd.df_day.loc[m, 'HL'] == 'L':
-                            if x - m > 3:
-                                thd.df_day.loc[x, 'HL'] = 'H'
-                                if x == len(thd.df_day.index) - 1:
-                                    # print(stock, '!!!!!!!', '\n', '卖卖卖卖卖卖卖!')
-                                    pass
-                                thd.df_day.loc[x, 9] = thd.df_day.loc[x, 'close'] - thd.df_day.loc[m, 'close']
-                            break
-                        elif (thd.df_day.loc[m, 'HL'] == 'H'):
-                            if thd.df_day.loc[x - 1, 'high'] > thd.df_day.loc[m - 1, 'high']:
-                                # 前一个为顶，且中间存在不包含 or 更高的顶
-                                thd.df_day.loc[x, 'HL'] = 'H'
-                                if x == len(thd.df_day.index) - 1:
-                                    pass
-                                    # print(stock, '/\/\/\/\/\/\/', '一顶更有一顶高！')
-                                break
-                            break
-                        m = m - 1
-                else:
-                    thd.df_day.loc[x, 'HL'] = '-'
-        # 更新数据库
-        thd.df_day.to_sql('stk%s_%s' % (stock, fre), con=engine2, index=True, if_exists='append')
+                # 没有历史数据表
+                thd.df_day = pd.DataFrame(columns=('date', 'open', 'close', 'high', 'low', 'volume', 'money', 'HL'))
+                thd.get_price = pd.read_sql_query(
+                    'select date,open,close,high,low,volume,money from `stk%s_%s`' % (stock, fre), engine)
+                # 先处理去包含
+                for i in thd.get_price.index:
+                    if i == 0 or i == 1:
+                        thd.df_day = pd.concat([thd.df_day, thd.get_price.iloc[[i]]], ignore_index=True)
+                    # 不包含
+                    elif (thd.df_day.iloc[-1, 3] > thd.get_price.loc[i, 'high']
+                          and thd.df_day.iloc[-1, 4] > thd.get_price.loc[i, 'low']) \
+                            or (thd.df_day.iloc[-1, 3] < thd.get_price.loc[i, 'high']
+                                and thd.df_day.iloc[-1, 4] < thd.get_price.loc[i, 'low']):
+                        thd.df_day = pd.concat([thd.df_day, thd.get_price.loc[[i]]], ignore_index=True)
+                    # 包含
+                    else:
+                        # 左高，下降
+                        if thd.df_day.iloc[-2, 3] > thd.df_day.iloc[-1, 3]:
+                            thd.df_day.iloc[-1, 3] = min(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
+                            thd.df_day.iloc[-1, 4] = min(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
+                        else:
+                            # 右高，上升
+                            thd.df_day.iloc[-1, 3] = max(thd.df_day.iloc[-1, 3], thd.get_price.loc[i, 'high'])
+                            thd.df_day.iloc[-1, 4] = max(thd.df_day.iloc[-1, 4], thd.get_price.loc[i, 'low'])
+                if len(thd.df_day.index) > 2:
+                    # 寻找顶底分型
+                    for x in range(2, len(thd.df_day.index)):
+                        m = x - 1
+                        # 底
+                        if ((thd.df_day.loc[x, 'high'] > thd.df_day.loc[x - 1, 'high']) and (
+                                thd.df_day.loc[x - 2, 'high'] > thd.df_day.loc[x - 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)
+                            thd.df_day.loc[x, 'HL'] = 'L*'
+                            while m:
+                                if thd.df_day.loc[m, 'HL'] == 'H':
+                                    if (x - m) > 3:
+                                        thd.df_day.loc[x, 'HL'] = 'L'
+                                        if x == len(thd.df_day.index) - 1:
+                                            print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '买买买买买！！')
+                                    break
+                                elif (thd.df_day.loc[m, 'HL'] == 'L'):
+                                    if thd.df_day.loc[x - 1, 'low'] < thd.df_day.loc[m - 1, 'low']:
+                                        # 前一个为底，且中间存在不包含 or 更低的底
+                                        thd.df_day.loc[x, 'HL'] = 'L'
+                                        if x == len(thd.df_day.index) - 1:
+                                            # pass
+                                            print(stock, '$$$$$$$', '\n', thd.df_day.loc[x, 'date'], '中继后的底————买吗？！')
+                                        break
+                                    else:
+                                        break
+                                m = m - 1
+                        # 顶
+                        elif ((thd.df_day.loc[x, 'high'] < thd.df_day.loc[x - 1, 'high']) and (
+                                thd.df_day.loc[x - 2, 'high'] < thd.df_day.loc[x - 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)
+                            thd.df_day.loc[x, 'HL'] = 'H*'
+                            while m:
+                                if thd.df_day.loc[m, 'HL'] == 'L':
+                                    if x - m > 3:
+                                        thd.df_day.loc[x, 'HL'] = 'H'
+                                        if x == len(thd.df_day.index) - 1:
+                                            # print(stock, '!!!!!!!', '\n', '卖卖卖卖卖卖卖!')
+                                            pass
+                                        thd.df_day.loc[x, 9] = thd.df_day.loc[x, 'close'] - thd.df_day.loc[m, 'close']
+                                    break
+                                elif (thd.df_day.loc[m, 'HL'] == 'H'):
+                                    if thd.df_day.loc[x - 1, 'high'] > thd.df_day.loc[m - 1, 'high']:
+                                        # 前一个为顶，且中间存在不包含 or 更高的顶
+                                        thd.df_day.loc[x, 'HL'] = 'H'
+                                        if x == len(thd.df_day.index) - 1:
+                                            pass
+                                            # print(stock, '/\/\/\/\/\/\/', '一顶更有一顶高！')
+                                        break
+                                    break
+                                m = m - 1
+                        else:
+                            thd.df_day.loc[x, 'HL'] = '-'
+                # 更新数据库
+                thd.df_day.to_sql('stk%s_%s' % (stock, fre), con=engine2, index=True, if_exists='append')
+
+    step = 100
+    thread_list = []
+    engine = []
+    engine2 = []
+    times_engine = 0
+    for i in range(0, len(table_list), step):
+        engine.append(create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh?charset=utf8'))
+        engine2.append(create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/hlfx?charset=utf8'))
+        thread = threading.Thread(target=hlfx, args=(table_list[i:i + step], engine[times_engine], engine2[times_engine]))
+        times_engine = times_engine + 1
+        thread.start()
+        thread_list.append(thread)
+
+    for thread in thread_list:
+        thread.join()
+    db.close()

update_data_tosql.py

@@ -7,36 +7,41 @@ import datetime
 auth('18616891214', 'Ea?*7f68nD.dafcW34d!')
 stocks = list(get_all_securities(['stock'], date=dt.today().strftime('%Y-%m-%d')).index)
 engine = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/stocks?charset=utf8')
-fre = '30m'
-
-print('ready to write to mysql')
-for stock in stocks:
-    print(stock)
-    try:
-        index_len = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine).iloc[-1, 0]
-        # 注意修改time delta
-        startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine).iloc[-1, 1] + datetime.timedelta(days=1)
-        print(startdate)
-        df_stock = get_price(stock, start_date=startdate, end_date=dt.today().strftime('%Y-%m-%d %H:%M:%S'),
-                             frequency=fre, fields=['open', 'close', 'high', 'low', 'volume', 'money'],
-                             skip_paused=False,
-                             fq='pre', count=None, panel=False)
-        df_stock = df_stock.dropna(axis=0)
-        df_stock.reset_index(inplace=True)
-        df_stock.rename(columns={'index': 'date'}, inplace=True)
-        df_stock.index = df_stock.index + index_len + 1
-        df_stock.to_sql('stk%s_%s' % (stock, fre), con=engine, index=True, if_exists='append')
-    except BaseException:
-        df_stock = get_price(stock, start_date='2022-01-01 00:00:00', end_date=dt.today().strftime('%Y-%m-%d %H:%M:%S'),
-                             frequency=fre, fields=['open', 'close', 'high', 'low', 'volume', 'money'],
-                             skip_paused=False,
-                             fq='pre', count=None, panel=False)
-        df_stock = df_stock.dropna(axis=0)
-        df_stock.reset_index(inplace=True)
-        df_stock.rename(columns={'index': 'date'}, inplace=True)
-        df_stock.to_sql('stk%s_%s' % (stock, fre), con=engine, index=True, if_exists='append')
-        with engine.connect() as con:
-            con.execute("ALTER TABLE `stk%s_%s` ADD PRIMARY KEY (`date`);" % (stock, fre))
+
+for fre in ['30m', '1d']:
+    print('ready to write to mysql %s' % fre)
+    for stock in stocks:
+        print(stock)
+        try:
+            index_len = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine).iloc[-1, 0]
+            # 注意修改time delta
+            if fre == '1d':
+                startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine).iloc[-1, 1] + datetime.timedelta(
+                    days=1)
+            elif fre == '30m':
+                startdate = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine).iloc[-1, 1] + datetime.timedelta(
+                    minutes=5)
+            print(startdate)
+            df_stock = get_price(stock, start_date=startdate, end_date=dt.today().strftime('%Y-%m-%d %H:%M:%S'),
+                                 frequency=fre, fields=['open', 'close', 'high', 'low', 'volume', 'money'],
+                                 skip_paused=False,
+                                 fq='pre', count=None, panel=False)
+            df_stock = df_stock.dropna(axis=0)
+            df_stock.reset_index(inplace=True)
+            df_stock.rename(columns={'index': 'date'}, inplace=True)
+            df_stock.index = df_stock.index + index_len + 1
+            df_stock.to_sql('stk%s_%s' % (stock, fre), con=engine, index=True, if_exists='append')
+        except BaseException:
+            df_stock = get_price(stock, start_date='2022-01-01 00:00:00', end_date=dt.today().strftime('%Y-%m-%d %H:%M:%S'),
+                                 frequency=fre, fields=['open', 'close', 'high', 'low', 'volume', 'money'],
+                                 skip_paused=False,
+                                 fq='pre', count=None, panel=False)
+            df_stock = df_stock.dropna(axis=0)
+            df_stock.reset_index(inplace=True)
+            df_stock.rename(columns={'index': 'date'}, inplace=True)
+            df_stock.to_sql('stk%s_%s' % (stock, fre), con=engine, index=True, if_exists='append')
+            with engine.connect() as con:
+                con.execute("ALTER TABLE `stk%s_%s` ADD PRIMARY KEY (`date`);" % (stock, fre))