def import_stock_pledged() :
db=cx_Oracle.connect('c##stock','didierg160','myoracle') #创建连接
cr=db.cursor()
sql = "delete tb_stock_pledged"
cr.execute(sql)
df = ts.stock_pledged()
for row in df.itertuples():
sql = "insert into tb_stock_pledged values ("
sql += "'" + str(getattr(row,"code" )) + "',"
sql += "'" + str(getattr(row,"name" )) + "',"
sql += "'" + str(getattr(row,"deals" )) + "',"
sql += "'" + str(getattr(row,"unrest_pledged" )) + "',"
sql += "'" + str(getattr(row,"rest_pledged" )) + "',"
sql += "'" + str(getattr(row,"totals" )) + "',"
sql += "'" + str(getattr(row,"p_ratio" )) + "',"
sql += "sysdate"
sql += ")"
cr.execute(sql)
db.commit()
cr.close ()
db.close ()
print("stock_pledged done")
def pledge_info():
df=ts.stock_pledged()
df.to_sql('tb_pledged_base',engine,if_exists='replace')
df_list=[]
for stock in stocks:
df_list.append(df[df['code']==stock])
df=pd.concat(df_list)
# print(df)
df=df.reset_index(drop=True)
# print(df)
df= df.sort_values('p_ratio',ascending=False)
df['code']=df['code'].astype('str')
df['rest_ratio']=df['rest_pledged']/df['totals']*100
df['rest_ratio']=map(lambda x:round(x,2),df['rest_ratio'])
df['unrest_ratio']=df['unrest_pledged']/df['totals']*100
df['unrest_ratio']=map(lambda x:round(x,2),df['unrest_ratio'])
def baseAPI():
# df=ts.get_hist_data('002524',start='2017-01-01',end='2017-04-24')
# 这个函数只能获取近3年的数据
# 目前这个版本是从最新开始 【0】
# print(df)
# print(df['close'].sum())
# stock_info=ts.get_stock_basics()
# print(stock_info)
# stock_info.to_csv('2.csv',encoding='gbk')
# n_df=pd.read_csv('2.csv',encoding='gbk')
# n_df.to_excel('2.xls',encoding='gbk')
# print(n_df)
# 这样子居然搞定了。
# dx_1=ts.get_hist_data('603111',start='2017-01-28',end='2017-04-22')
# print(dx_1)
# print(len(dx_1))
# ts.get_sz50s()
# print(dx_1['close'][0])
'''
print(stock_info.dtypes)
cols=stock_info.columns
for col in cols:
if stock_info[col].dtype == 'O':
print("O in " ,col)
del stock_info[col]
print(stock_info)
stock_info.to_excel('new.xls')
'''
# 编码出错
# stock_info.to_excel('base.xls',encoding='gb2312')
'''
data=stock_info.ix['300141']['timeToMarket']
print(data)
print(type(data))
data=str(data)
print(type(data))
print(data[1:4])
print(data[4:6])
print(data)
date_format=data[0:4]+'-'+data[4:6]+'-'+data[6:8]
print(date_format)
delta=60*7/5
day0=datetime.date(datetime.date.today().year,datetime.date.today().month,datetime.date.today().day)
day30=day0-datetime.timedelta(delta)
print(day30)
day30=day30.strftime("%Y-%m-%d")
day0=day0.strftime("%Y-%m-%d")
'''
# df1=ts.new_stocks()
# print(df1)
# df2=ts.new_stocks(2)
# print(df2)
# df3=ts.new_stocks(3)
# print(df3)
# sz_index=ts.get_k_data('399001',index=True,start='2017-01-10',end='2017-04-28')
'''
sz_index=ts.get_k_data('300141')
print(sz_index)
print(sz_index.ix[sz_index['date']=='2014-05-06','high'].values[0])
'''
'''
df = ts.get_realtime_quotes(['600848', '000980', '000981']) #一次过返回3个数据
print(df)
'''
# bar 函数
# conn = ts.get_apis()
# df =ts.bar('000022',conn,start_date='2000-01-01',adj='qfq')
# print(df)
# print(df.dtypes)
df = ts.get_today_all()
print(df)
exit()
filename = datetime.datetime.now().strftime('%Y-%m-%d') + '.xls'
df.to_excel(filename)
forecast_filename = '2017-12.xls'
forecast_df = ts.forecast_data(2017, 4)
print(forecast_df)
forecast_df.to_excel(forecast_filename)
ts.stock_pledged()
'''
Created on 2018年2月8日
@author: moonlit
'''
import tushare as ts
if __name__ == '__main__':
df = ts.stock_pledged()
print(df.columns)
print(len(df))
df = ts.pledged_detail()
print(df.columns)
print(len(df))
def baseAPI():
# df=ts.get_hist_data('002524',start='2017-01-01',end='2017-04-24')
# 这个函数只能获取近3年的数据
# 目前这个版本是从最新开始 【0】
# print(df)
# print(df['close'].sum())
# stock_info=ts.get_stock_basics()
# print(stock_info)
# stock_info.to_csv('2.csv',encoding='gbk')
# n_df=pd.read_csv('2.csv',encoding='gbk')
# n_df.to_excel('2.xls',encoding='gbk')
# print(n_df)
# 这样子居然搞定了。
# dx_1=ts.get_hist_data('603111',start='2017-01-28',end='2017-04-22')
# print(dx_1)
# print(len(dx_1))
# ts.get_sz50s()
# print(dx_1['close'][0])
'''
print(stock_info.dtypes)
cols=stock_info.columns
for col in cols:
if stock_info[col].dtype == 'O':
print("O in " ,col)
del stock_info[col]
print(stock_info)
stock_info.to_excel('new.xls')
'''
# 编码出错
# stock_info.to_excel('base.xls',encoding='gb2312')
'''
data=stock_info.ix['300141']['timeToMarket']
print(data)
print(type(data))
data=str(data)
print(type(data))
print(data[1:4])
print(data[4:6])
print(data)
date_format=data[0:4]+'-'+data[4:6]+'-'+data[6:8]
print(date_format)
delta=60*7/5
day0=datetime.date(datetime.date.today().year,datetime.date.today().month,datetime.date.today().day)
day30=day0-datetime.timedelta(delta)
print(day30)
day30=day30.strftime("%Y-%m-%d")
day0=day0.strftime("%Y-%m-%d")
'''
# df1=ts.new_stocks()
# print(df1)
# df2=ts.new_stocks(2)
# print(df2)
# df3=ts.new_stocks(3)
# print(df3)
# sz_index=ts.get_k_data('399001',index=True,start='2017-01-10',end='2017-04-28')
'''
sz_index=ts.get_k_data('300141')
print(sz_index)
print(sz_index.ix[sz_index['date']=='2014-05-06','high'].values[0])
'''
'''
df = ts.get_realtime_quotes(['600848', '000980', '000981']) #一次过返回3个数据
print(df)
'''
# bar 函数
# conn = ts.get_apis()
# df =ts.bar('000022',conn,start_date='2000-01-01',adj='qfq')
# print(df)
# print(df.dtypes)
df = ts.get_today_all()
print(df)
exit()
filename = datetime.datetime.now().strftime('%Y-%m-%d') + '.xls'
df.to_excel(filename)
forecast_filename = '2017-12.xls'
forecast_df = ts.forecast_data(2017, 4)
print(forecast_df)
forecast_df.to_excel(forecast_filename)
ts.stock_pledged()
def get_all_stock_pledged(self):
return tu.stock_pledged().sort_values(['p_ratio'], ascending=False)
