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@@ -29,49 +29,57 @@ import threading
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engine2 = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/stocks?charset=utf8')
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stocks = list(get_all_securities(['stock'], date='2021-12-31').index)
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-# stocks =stocks[0:40]
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+stocks =stocks[0:40]
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thd = threading.local()
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-def qbh(stocks , engine):
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+def qbh(stocks, engine, engine_backup):
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for stock in stocks:
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- print(stock)
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- thd.new_df = pd.DataFrame(columns=('date', 'open', 'close', 'high', 'low', 'volume', 'money', 'HL'))
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- # print(new_df.head())
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- thd.df_day = stk['stk' + stock[:6]]
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- for i in thd.df_day.index:
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- if i == 0 or i == 1:
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- thd.new_df = pd.concat([thd.new_df, thd.df_day.iloc[[i]]], ignore_index=True)
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- # 不包含
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- elif (thd.new_df.iloc[-1, 3] > thd.df_day.loc[i, 'high']
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- and thd.new_df.iloc[-1, 4] > thd.df_day.loc[i, 'low']) \
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- or (thd.new_df.iloc[-1, 3] < thd.df_day.loc[i, 'high']
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- and thd.new_df.iloc[-1, 4] < thd.df_day.loc[i, 'low']):
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- thd.new_df = pd.concat([thd.new_df, thd.df_day.iloc[[i]]], ignore_index=True)
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- # 包含
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- else:
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- # (new_df.iloc[-1,3]>=df_day.loc[i,'high'] and new_df.iloc[-1,4]<= df_day.loc[i,'low']):
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- if thd.new_df.iloc[-2, 3] > thd.new_df.iloc[-1, 3]: #左高，下降
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- thd.new_df.iloc[-1, 3] = min(thd.new_df.iloc[-1, 3], thd.df_day.loc[i, 'high'])
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- thd.new_df.iloc[-1, 4] = min(thd.new_df.iloc[-1, 4], thd.df_day.loc[i, 'low'])
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- else:
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- # 右高，上升
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- thd.new_df.iloc[-1, 3] = max(thd.new_df.iloc[-1, 3], thd.df_day.loc[i, 'high'])
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- thd.new_df.iloc[-1, 4] = max(thd.new_df.iloc[-1, 4], thd.df_day.loc[i, 'low'])
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- thd.new_df.to_sql('stk%s_%s' % (stock[:6], u), con=engine, index=True, if_exists='replace')
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- with engine.connect() as con:
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- con.execute('ALTER TABLE stk%s_%s ADD PRIMARY KEY (`date`);'% (stock[:6], u))
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- print(stock)
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- print("**************")
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-
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- # new_df.to_csv('new_df.csv')
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-
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- #return new_df
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+ print(engine)
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+ print(engine_backup)
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+ # thd.new_df = pd.DataFrame(columns=('date', 'open', 'close', 'high', 'low', 'volume', 'money', 'HL'))
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+ # # print(new_df.head())
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+ # thd.df_day = stk['stk' + stock[:6]]
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+ # for i in thd.df_day.index:
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+ # if i == 0 or i == 1:
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+ # thd.new_df = pd.concat([thd.new_df, thd.df_day.iloc[[i]]], ignore_index=True)
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+ # # 不包含
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+ # elif (thd.new_df.iloc[-1, 3] > thd.df_day.loc[i, 'high']
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+ # and thd.new_df.iloc[-1, 4] > thd.df_day.loc[i, 'low']) \
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+ # or (thd.new_df.iloc[-1, 3] < thd.df_day.loc[i, 'high']
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+ # and thd.new_df.iloc[-1, 4] < thd.df_day.loc[i, 'low']):
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+ # thd.new_df = pd.concat([thd.new_df, thd.df_day.iloc[[i]]], ignore_index=True)
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+ # # 包含
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+ # else:
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+ # # (new_df.iloc[-1,3]>=df_day.loc[i,'high'] and new_df.iloc[-1,4]<= df_day.loc[i,'low']):
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+ # # 左高，下降
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+ # if thd.new_df.iloc[-2, 3] > thd.new_df.iloc[-1, 3]:
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+ # thd.new_df.iloc[-1, 3] = min(thd.new_df.iloc[-1, 3], thd.df_day.loc[i, 'high'])
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+ # thd.new_df.iloc[-1, 4] = min(thd.new_df.iloc[-1, 4], thd.df_day.loc[i, 'low'])
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+ # else:
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+ # # 右高，上升
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+ # thd.new_df.iloc[-1, 3] = max(thd.new_df.iloc[-1, 3], thd.df_day.loc[i, 'high'])
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+ # thd.new_df.iloc[-1, 4] = max(thd.new_df.iloc[-1, 4], thd.df_day.loc[i, 'low'])
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+ # thd.new_df.to_sql('stk%s_%s' % (stock[:6], u), con=engine, index=True, if_exists='replace')
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+ # with engine.connect() as con:
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+ # con.execute('ALTER TABLE stk%s_%s ADD PRIMARY KEY (`date`);' % (stock[:6], u))
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+ # thd.new_df.to_sql('stk%s_%s' % (stock[:6], u), con=engine_backup, index=True, if_exists='replace')
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+ # with engine_backup.connect() as con_backup:
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+ # con_backup.execute('ALTER TABLE stk%s_%s ADD PRIMARY KEY (`date`);' % (stock[:6], u))
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+ # thd.new_df.to_csv(
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+ # '/Users/daniel/Library/CloudStorage/OneDrive-个人/个人/python_stocks/20220211qbh/qbh%s.csv' % stock[:6])
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+ # print(stock)
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+ # print("**************")
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+ #
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+ # # new_df.to_csv('new_df.csv')
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+ #
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+ # #return new_df
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stk = locals()
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-engine = locals()
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+engine = []
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+engine_backup = []
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u = '1d'
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# 获取数据存入DataFrame
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@@ -89,7 +97,8 @@ print("#########################################################################
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# 开始去包含
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# qbh(stocks)
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-
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-for m in range(0, len(stocks), 50):
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- engine[m] = create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh_hlfx?charset=utf8', pool_recycle=3600)
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- threading.Thread(target=qbh, args=(stocks[m:m + 50], engine[m])).start()
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+step = 100
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+for m in range(0, len(stocks), step):
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+ engine.append(create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh_hlfx?charset=utf8', pool_recycle= 3600))
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+ engine_backup.append(create_engine('mysql+pymysql://root:r6kEwqWU9!v3@localhost:3307/qbh_hlfx_backup?charset=utf8', pool_recycle= 3600))
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+ threading.Thread(target=qbh, args=(stocks[m:m + step], engine[m], engine_backup[m])).start()
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