def update_fund_nav():
db_config = setting.DATABASES['fund_stat']
conn, cr = create_db_connection(db_config['HOST'], db_config['DB'],
db_config['PORT'], db_config['USER'],
db_config['PASSWD'])
fd = ts.Fund()
cnt = 0
for line in open("fundcode"):
tc = line.strip()
print cnt, "code:", tc
cnt += 1
#Get fund info
f1 = fd.FundNav(
ticker=tc,
field="secID,secShortName,endDate,NAV,ACCUM_NAV,ADJUST_NAV")
if not f1.empty:
f1['code'] = tc
pd.io.sql.to_sql(f1,
"fund_nav",
conn,
flavor='mysql',
if_exists='append',
index=False)
conn.commit()
db_close(conn, cr)
def preprocess():
db_config = setting.DATABASES['fund_stat']
conn,cr = create_db_connection(db_config['HOST'],db_config['DB'],db_config['PORT'],db_config['USER'],db_config['PASSWD'])
fd = ts.Fund()
cnt = 0
for line in open("fundcode"):
tc = line.strip()
print cnt,"code:",tc
cnt += 1
f1 = fd.FundNav(ticker = tc, field = "secID,secShortName,endDate,NAV,ACCUM_NAV,ADJUST_NAV")
if not f1.empty:
secID = f1.ix[0, "secID"]
# print secID
sql = "update fund_nav set code= %s where secID=%s"
cr.execute(sql, (tc, secID))
if cnt % 50 == 0:
print "commit"
conn.commit()
# for rz in cr.fetchall():
# print rz
conn.commit()
db_close(conn,cr)
def fund(self):
fd = ts.Fund()
df = fd.FundDiv(
ticker='184688',
adjustedType='D',
beginDate='20000101',
field=
'secShortName,effectDate,publishDate,dividendAfTax,dividendBfTax')
print(df)
dd = ts.fund_holdings(2015, 4)
print(dd[['name', 'nums', 'clast', 'amount']])
import tushare as ts
import sys
import os
import marshal
import numpy as np
import pandas as pd
from pandas.compat import StringIO
from sklearn.linear_model import LinearRegression as lr
import warnings
import MySQLdb
mysql = MySQLdb.connect(host='localhost', port=3306, user='******', passwd='', db='fund_stat')
ts.set_token('eaf6b3ffd2808fee8221dbbc2ab223c1ffa4e64c29ce508d7fcdaefd09c264ba')
fd = ts.Fund()
cnt = 0
for line in open("fundcode"):
tc = line.strip()
print cnt,"code:",tc
cnt += 1
#Get fund info
f1 = fd.FundNav(ticker = tc, field = "secID,secShortName,endDate,NAV,ACCUM_NAV,ADJUST_NAV")
if not f1.empty:
pd.io.sql.to_sql(f1, "fund_nav", mysql, flavor='mysql', if_exists='append', index=False)
def get_fund_data(fund_code):
fd = ts.Fund()
return fd.FundNav(
ticker=fund_code,
beginDate='20150101',
field='ticker,endDate,NAV,publishDate,ACCUM_NAV,ADJUST_NAV')