# -*- coding:utf-8 -*- """ Created on 2015/09/30 @author: Jacob He @contact: [email protected] """ from lib.stock.DbCache import DbCache if __name__ == '__main__': #init the fundament data c = DbCache() c.check_db_cache(1989)
import pandas as pd
from lib.stock.DbCache import DbCache
import lib.stock.trading as td
import lib.stock.fundamental as fd
import lib.cons as ct
from pymongo import MongoClient
from lib.util import dateu as du
import json
import numpy as np
from datetime import datetime
from datetime import timedelta
import check_mongo_hist_data
try:
from urllib.request import urlopen, Request
except ImportError:
from urllib2 import urlopen, Request
if __name__ == '__main__':
#更新基本面数据
cur = datetime.now()
curyear = cur.year
c = DbCache()
c.check_db_cache(curyear)
#更新历史数据
check_mongo_hist_data.run()
from pymongo import MongoClient
from lib.util import dateu as du
import json
import numpy as np
from datetime import datetime
from datetime import timedelta
import check_mongo_hist_data
try:
from urllib.request import urlopen, Request
except ImportError:
from urllib2 import urlopen, Request
if __name__ == '__main__':
#更新基本面数据
cur = datetime.now()
curyear = cur.year
c = DbCache()
c.check_db_cache(curyear)
#更新历史数据
check_mongo_hist_data.run()
def get_stock_growth():
"""
获取股票3年的增长率和最近几个季度的增长率
Return
--------
DataFrame
code :股票代码
name :股票名称
1year:最近一年增长率
2year:最近二年增长率
3year:最近三年增长率
4year:最近四年增长率
1quarter:最近一季度增长率
2quarter:最近二季度增长率
3quarter:最近三季度增长率
4quarter:最近四季度增长率
"""
fd = DbCache()
stock_list = fd.get_stock_basics()
df = pd.DataFrame(index=stock_list.index, columns=['name','industry','area','1quarter','2quarter','3quarter','4quarter','1year','2year','3year','4year'])
df['name'] = stock_list['name']
df['industry'] = stock_list['industry']
df['area'] = stock_list['area']
cur = datetime.datetime.now()
curyear = cur.year
fir_year_growth_data = fd.get_growth_data(curyear-1,4)
if fir_year_growth_data.empty:
curyear = curyear - 1
fir_year_growth_data = fd.get_growth_data(curyear-1,4)
sec_year_growth_data = fd.get_growth_data(curyear-2,4)
thir_year_growth_data = fd.get_growth_data(curyear-3,4)
for_year_growth_data = fd.get_growth_data(curyear-4,4)
for i in fir_year_growth_data.index:
df.loc[fir_year_growth_data.loc[i,'code'],'1year'] = fir_year_growth_data.loc[i,'nprg']
for i in sec_year_growth_data.index:
df.loc[sec_year_growth_data.loc[i,'code'],'2year'] = sec_year_growth_data.loc[i,'nprg']
for i in thir_year_growth_data.index:
df.loc[thir_year_growth_data.loc[i,'code'],'3year'] = thir_year_growth_data.loc[i,'nprg']
for i in for_year_growth_data.index:
df.loc[for_year_growth_data.loc[i,'code'],'4year'] = for_year_growth_data.loc[i,'nprg']
curmonth = cur.month
if curmonth in(4,5,6):
curquarter = 1
curyear = cur.year
elif curmonth in (7,8,9):
curquarter = 2
curyear = cur.year
elif curmonth in (10,11,12):
curquarter = 3
curyear = cur.year
elif curmonth in(1,2,3):
curquarter = 4
curyear = cur.year - 1
fir_quarter_growth_data = fd.get_growth_data(curyear,curquarter)
if fir_quarter_growth_data.empty:
curyear,curquarter = _sub_quarter(curyear,curquarter)
fir_quarter_growth_data = fd.get_growth_data(curyear,curquarter)
curyear2,curquarter2 = _sub_quarter(curyear,curquarter)
sec_quarter_growth_data = fd.get_growth_data(curyear2,curquarter2)
curyear3,curquarter3 = _sub_quarter(curyear2,curquarter2)
thir_quarter_growth_data = fd.get_growth_data(curyear3,curquarter3)
curyear4,curquarter4 = _sub_quarter(curyear3,curquarter3)
for_quarter_growth_data = fd.get_growth_data(curyear4,curquarter4)
for i in fir_quarter_growth_data.index:
df.loc[fir_quarter_growth_data.loc[i,'code'],'1quarter'] = fir_quarter_growth_data.loc[i,'nprg']
for i in sec_quarter_growth_data.index:
df.loc[sec_quarter_growth_data.loc[i,'code'],'2quarter'] = sec_quarter_growth_data.loc[i,'nprg']
for i in thir_quarter_growth_data.index:
df.loc[thir_quarter_growth_data.loc[i,'code'],'3quarter'] = thir_quarter_growth_data.loc[i,'nprg']
for i in for_quarter_growth_data.index:
df.loc[for_quarter_growth_data.loc[i,'code'],'4quarter'] = for_quarter_growth_data.loc[i,'nprg']
return df
