def back_test(df,
start_date='0',
date_delta=60,
norm_type='character',
quota_index=0,
lost=1.0):
if start_date:
end_date = date_add(start_date, date_delta)
else:
end_date = '9'
if end_date > today():
return []
df_dif = get_quota(df)[quota_index]
df_dif_norm = get_normlized(df_dif)
df = pd.concat([df.set_index('date')['close'], df_dif_norm['sar']],
axis=1).dropna(how='any')
close = df['close']
r = get_trade_chance(df_dif, close, norm_type, start_date, end_date, lost)
if r:
rate, date_this, buy_price, buy_date, sell_price, sell_date, start_date_open, end_date_open = r
else:
return []
for s_type in sell_price:
rate[s_type] = {}
rate[s_type]['profit'] = {}
rate[s_type]['profit']['total'] = 1.0
rate[s_type]['trade'] = {}
for i in range(len(buy_price[s_type])):
try:
#rate[s_type]['profit']['total'] = rate[s_type]['profit']['total'] * (sell_price[s_type][i] * (1 - 0.002) / buy_price[s_type][i])
rate[s_type]['profit']['total'] = rate[s_type]['profit'][
'total'] * (sell_price[s_type][i] *
(1 - 0.002) / buy_price[s_type][i]) * (
(sell_price[s_type][i]) *
(1 - 0.002) / buy_price[s_type][i + 1])
rate[s_type]['profit'][buy_date[s_type]
[i]] = rate[s_type]['profit']['total']
rate[s_type]['trade'][buy_date[s_type][i]] = [
buy_date[s_type][i], buy_price[s_type][i],
sell_date[s_type][i], sell_price[s_type][i]
]
except Exception, e:
if len(buy_price[s_type]) == len(sell_price[s_type]):
rate[s_type]['profit']['total'] = rate[s_type]['profit'][
'total'] * (end_date_open *
(1 - 0.002) / sell_price[s_type][i])
else:
rate[s_type]['profit']['total'] = rate[s_type]['profit'][
'total'] * (end_date_open *
(1 - 0.002) / buy_price[s_type][i])
rate[s_type]['profit'][date_this] = rate[s_type]['profit'][
'total']
rate[s_type]['trade'][date_this] = [
buy_date[s_type][i], buy_price[s_type][i], 'lastday',
end_date_open
]
#coding:utf-8
import pandas as pd
from commfunction import today, date_add
df = pd.read_csv('./cluedetail.csv')
td = today()
td = date_add(td, -2)
thisweek_start = date_add(td, -8)
thisweek_end = date_add(td, -2)
lastweek_start = date_add(thisweek_start, -7)
lastweek_end = date_add(thisweek_end, -7)
lastmonth_start = date_add(thisweek_start, -31)
lastmonth_end = date_add(thisweek_end, -31)
df_thisweek = df[(df['date'] >= thisweek_start)
& (df['date'] <= thisweek_end)].groupby(['city']).count()
df_thisweek['date'] = thisweek_start + '~' + thisweek_end
df_lastweek = df[(df['date'] >= lastweek_start)
& (df['date'] <= lastweek_end)].groupby(['city']).count()
df_lastweek['date'] = lastweek_start + '~' + lastweek_end
df_lastmonth = df[(df['date'] >= lastmonth_start)
& (df['date'] <= lastmonth_end)].groupby(['city']).count()
df_lastmonth['date'] = lastmonth_start + '~' + lastmonth_end
df_thismonth = df[(df['date'] >= lastmonth_start)
& (df['date'] <= lastmonth_end)].groupby(['city']).count()
df_thismonth['date'] = lastmonth_start + '~' + lastmonth_end
df_all = pd.concat([df_thisweek, df_lastweek, df_lastmonth],
axis=0,
join='inner')
#coding:utf-8
from sqlalchemy import create_engine
import requests
from sqlalchemy.orm import sessionmaker
import time, datetime, commfunction
from random import random
import pandas as pd
import numpy as np
#exit()
stocks = open('stocks.txt', 'r').readlines()
stocks = [code.replace('\n', '').replace('\r', '') for code in stocks]
today = commfunction.today('%Y_%m_%d').replace('_0', '_')
DB_CONNECT_STRING = 'sqlite:///stock_US_data.db'
engine = create_engine(DB_CONNECT_STRING, echo=False)
DB_Session = sessionmaker(bind=engine)
session = DB_Session()
def get_origin_ustock_datas(code, today):
time.sleep(random() * 20)
code = code.lower()
url = 'http://stock.finance.sina.com.cn/usstock/api/jsonp_v2.php/var%20_' + code + today + '=/US_MinKService.getDailyK?symbol=' + code + '&_=' + today + '&___qn=3'
contents = requests.get(url).text[:-2].split('=(')[1]
try:
df = pd.DataFrame(eval(contents))
df.rename(columns={
'o': 'open',
'c': 'close',
'h': 'high',
'l': 'low',
#coding:utf-8
from sqlalchemy import create_engine
import tushare as ts
from sqlalchemy.orm import sessionmaker
import time, datetime
from commfunction import today, date_add
fw = open('stock_date.txt', 'w')
today_date = date_add(str(today()), -1)
DB_CONNECT_STRING = 'sqlite:///stock_CN_data.db'
engine = create_engine(DB_CONNECT_STRING, echo=False)
DB_Session = sessionmaker(bind=engine)
session = DB_Session()
codeDatas = session.execute(
'select * from publish_date where code="002230";').fetchall()
for data in codeDatas[:1]:
code, time_to_market = data
print code, time_to_market
try:
lastdate = session.execute('select date from day_k_data where code="' +
code +
'" order by date desc limit 1;').first()[0]
except Exception, e:
#print e
try:
lastdate = date_add(str(time_to_market), 0, '%Y%m%d')
except:
lastdate = date_add(str(today_date), -1095, '%Y-%m-%d')
#!/usr/bin/python
#coding:utf-8
import requests, time
import BeautifulSoup
import sys
import datetime
from random import random
import pandas as pd
from commfunction import today, date_add, date_today_delta
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
import matplotlib.pyplot as plt
date_today = today()
record = 'greeks\t' + date_today + '\n'
stocks = open('stocks.txt', 'r').readlines()
stocks = [code.replace('\n', '').replace('\r', '') for code in stocks]
DB_CONNECT_STRING = 'sqlite:///stock_option_data.db'
engine = create_engine(DB_CONNECT_STRING, echo=False)
DB_Session = sessionmaker(bind=engine)
session = DB_Session()
def get_origin_option_datas(url, datasAll=[]):
time.sleep(random() * 20)
content = BeautifulSoup.BeautifulSoup(requests.get(url).text)
nextpage = content.findAll('a', {'id': 'quotes_content_left_lb_NextPage'})
datasAll.append(
content.findAll('div',
def downloadFenshi(stockNum):
imageUrl = 'http://image.sinajs.cn/newchart/v5/usstock/wap/min_daily/226/' + stockNum + '.gif'
print imageUrl
return requests.get(imageUrl, 'fenshi/' + stockNum + today() + '.gif')
#!/usr/bin/python
#coding:utf-8
import requests,time
import BeautifulSoup
import sys
import datetime
from random import random
import pandas as pd
from commfunction import today,date_add,date_today_delta
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
date_today = date_add(today(),-1)
record = 'option_price\t'+date_today+'\n'
try:
t = open('t.txt','r').readlines()
if record in t:
exit()
except Exception,e:
pass
t = open('t.txt','a')
t.write(record)
t.close()
DB_CONNECT_STRING = 'sqlite:///stock_option_data.db'
engine = create_engine(DB_CONNECT_STRING,echo=False)
DB_Session = sessionmaker(bind=engine)
session = DB_Session()
stocks = open('stocks.txt','r').readlines()
