获取资金流信息

change_pct	涨跌幅(%)	---
net_amount_main	主力净额(万)	主力净额 = 超大单净额 + 大单净额
net_pct_main	主力净占比(%)	主力净占比 = 主力净额 / 成交额
net_amount_xl	超大单净额(万)	超大单：大于等于50万股或者100万元的成交单
net_pct_xl	超大单净占比(%)	超大单净占比 = 超大单净额 / 成交额
net_amount_l	大单净额(万)	大单：大于等于10万股或者20万元且小于50万股或者100万元的成交单
net_pct_l	大单净占比(%)	大单净占比 = 大单净额 / 成交额
net_amount_m	中单净额(万)	中单：大于等于2万股或者4万元且小于10万股或者20万元的成交单
net_pct_m	中单净占比(%)	中单净占比 = 中单净额 / 成交额
net_amount_s	小单净额(万)	小单：小于2万股或者4万元的成交单
net_pct_s	小单净占比(%)	小单净占比 = 小单净额 / 成交额

his_money_flow.py

@@ -0,0 +1,53 @@
+from jqdatasdk import *
+from datetime import datetime as dt
+import pandas as pd
+import pymysql
+from sqlalchemy import create_engine
+
+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')
+engine_data = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/stocks_data?charset=utf8')
+# stocks_List = ','.join(set(stocks))
+
+# db_stocks_list = pymysql.connect(host='localhost',
+#                           user='root',
+#                           port=3307,
+#                           password='r6kEwqWU9!v3',
+#                           database='hlfx_pool')
+# cursor_stock_list = db_stocks_list.cursor()
+# sql = "INSERT INTO stocks_list (date,securities) VALUES('%s','%s')" % (dt.today().strftime('%Y-%m-%d'),  stocks_List)
+# cursor_stock_list.execute(sql)
+# db_stocks_list.commit()
+# db_stocks_list.close()
+
+fre = '1d'
+print('ready to write to mysql %s' % fre)
+for stock in stocks:
+    print(stock, fre)
+    starttime ='2010-01-04'
+    # endtime = pd.read_sql_table('stk%s_%s' % (stock, fre), con=engine).iloc[-1, 1]
+    df_stock = get_price(stock, start_date=starttime, 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.index.name = 'date'
+
+    # print(df_stock)
+    # print(starttime,endtime)
+
+    df_money = get_money_flow(stock, start_date=starttime, end_date=dt.today().strftime('%Y-%m-%d %H:%M:%S'),
+                              fields=None, count=None)
+    df_money = df_money.drop(columns=['sec_code'])
+    # df_money.to_csv('/Users/daniel/Downloads/000002.csv')
+    # print(df_money)
+
+    df_stock = pd.merge(df_stock, df_money, how='outer', left_index=False , on='date')
+    # df_stock.to_csv('D:\001_QuantTrade\Result.csv')
+    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_data, index=True, if_exists='replace')
+    # with engine.connect() as con:
+    #     con.execute("ALTER TABLE `stk%s_%s` ADD PRIMARY KEY (`date`);" % (stock, fre))
+    print(df_stock)