def run(self, generator_function):
self.generator = generator_function
self.win = Tk()
self.win.grid_columnconfigure(1, weight=1)
self.win.wm_title("Cardcinogen")
self.template = StringVar()
self.deck = StringVar()
self.prefix = StringVar()
Label(self.win, text="Card template:").grid(row=0, column=0, sticky=E)
self.txtTemplate = Entry(self.win, textvariable=self.template).grid(row=0, column=1, sticky=E+W)
self.btnTemplate = Button(self.win, text="...", command=self.setTemplate).grid(row=0, column=2)
Label(self.win, text="Deck data:").grid(row=1, column=0, sticky=E)
self.txtDeck = Entry(self.win, textvariable=self.deck).grid(row=1, column=1, sticky=E+W)
self.btnDeck = Button(self.win, text="...", command=self.setDeck).grid(row=1, column=2)
Label(self.win, text="Output file prefix:").grid(row=2, column=0, sticky=E)
self.txtDeck = Entry(self.win, textvariable=self.prefix).grid(row=2, column=1, sticky=E+W)
self.btnGenerate = Button(self.win, text="Generate!", command=self.invoke).grid(row=3, column=0, columnspan=3, sticky=E+W)
self.log = Text(self.win)
self.log.grid(row=4, column=0, columnspan=3, sticky=N+S+E+W)
self.log.config(state=DISABLED)
log.setlog(self)
return self.win.mainloop()
#!/usr/bin/env python
# -*- coding: utf-8 -*-
"""
calculate indicators
"""
import numpy as np
import pandas as pd
import log
logger = log.setlog("indicator.py")
def typ(df_prices_high, df_prices_low, df_prices_close):
"""
Typical Price = average( high + low + close )
"""
df_typ = (df_prices_high + df_prices_low + df_prices_close) / 3
df_typ.name = 'typ'
return df_typ
def ema(df_prices, i_period, i_start=1):
"""
Exponential Moving Average
S(t) = w*P(t) + (1-w) * S(t-1)
w = 2/(N+1)
"""
i_len = len(df_prices)
assert i_len >= i_period
"""
run several arguments and sort results
"""
import local
import strategy as st
import backtester as bt
import sys,os,itertools
import pandas as pd
import multiprocessing as mp
import log
logger=log.setlog("optimizer.py")
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
def parameters_generator():
arg1 = range(48,51)
arg2 = range(28,31)
return itertools.product(arg1,arg2)
def tryArgList():
"""
run several arguments according to arglist file
"""
logger.info("backtest start.prod=%s",s_prod)
### write backtester file header ###
filepath_backtester =BASE_DIR+ '/backtester/' + s_prod + '.bt'
"""
define operation functions
"""
import pandas as pd
import log
logger = log.setlog("operation.py")
global time
def countif(df_data, i_period):
"""
count the number of True data in the last i_period time
Example: countif([True,False,True,True,False],3)=2
:param df_data: a Series of boolean value, result from conditions such as 'ema27 > ema50 and cci10>100 or typ>ema27'
:param i_period: time length
:return: a number
"""
assert i_period <= len(df_data)
index = df_data.index.get_loc(time)
i_count = len(filter(bool, df_data[index - i_period + 1 : index + 1]))
return i_count
def mro(df_data, i_period, i_index):
"""
Most Recent occur
Example: mro([True,False,True,True,False],3,1)=1
import datetime as dt
import dateutil
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import os, glob
import multiprocessing as mp
import log
logger=log.setlog("pdd.py")
#rights = pd.DataFrame()
def process_pd():
## three types of profit distribution: cash, stock, increase
##Prod ProductCode PlanDate DecisionDate PDD Cash Stock Increase StockSum
##SH SH600000 20000328 20000509 20000706 0.15 0 0 0
##SH SH600000 20020321 20020629 20020822 0.2 0 0.5 0.5
try:
confpath = './configuration/PDData.txt'
global rights
rights = pd.read_csv(confpath, sep ='\t')
# process security simultanously using multiprocess
filepath = './datas/Stock'
seclist = glob.glob(filepath+'/*_nopd')
logger.info("nopdlist:%s",seclist)
po = mp.Pool (mp.cpu_count())
teams = po.map(work, seclist)
po.close()
po.join()
import datetime as dt
import dateutil
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import os, glob
import multiprocessing as mp
import log
logger = log.setlog("ts.py")
freqlist = ['5min','15min','1H','1D']
rights = pd.DataFrame()
def convert_ts():
try:
# process security simultanously using multiprocess
filepath = './datas/Stock'
seclist = glob.glob(filepath+'/*_pd')
logger.info("pd file lists:%s",seclist)
arglist=[]
for f in seclist:
for freq in freqlist:
arglist.append((f,freq))
po = mp.Pool (mp.cpu_count())
teams = po.map(work, arglist)
po.close()
po.join()
import pandas as pd
import multiprocessing as mp
import os
import glob
import dateutil
import fcntl
import log
logger = log.setlog("ts_futures.py")
"""
Input: individual file containing daily tick data
=================== 20140303_IF1403_CFFEX_L1.txt =======================
close high low tlots tvols openint zero1 zero2 time zero3 bid bidvol ask askvol
2165.6 2165.6 2165.6 587 381362160 94019 0 0 09:14:00 0 2165.4 7 2165.6 8
2165.6 2166 2164.4 809 525567540 94045 0 0 09:15:00 0 2165.6 142 2166 7
2165 2166.6 2164.4 1166 757512840 94027 0 0 09:15:00 0 2165 12 2165.4 9
...
========================================================================
OutPut: combine all daily files into one big tick file
"""
############## global configuration ############
prod = 'IF'
s_starttime = '09:15:00'
s_breakmor = '11:30:00'
s_breakrep = '11:29:59'
s_endtime = '15:15:00'
import datetime as dt
import matplotlib.pyplot as plt
import pandas as pd
import numpy as np
import os, glob
import multiprocessing as mp
import log
logger=log.setlog("processdata.py")
def list_securities ():
try:
## get all the securities to be processed
## loop through to process
filepath_rawdata='../share/stocks_data/'
#filepath_rawdata='./datas_raw/Stock/'
seclist = glob.glob(filepath_rawdata+'*')
logger.info("rawdata list:%s",seclist)
po = mp.Pool (mp.cpu_count())
po.map(work, seclist)
po.close()
po.join()
except Exception,ex:
logger.error( "{0}: {1}".format(Exception,ex) )
def work (s):
logger.info("work(%s) start",s)
secname, result =process_one_stock(s)
## formated print
'''
# datestimes, typ, ema50, ema27, rsi14, cci10, tr, kpi
# 2014-11-12 09:15:00, 2557.9333, 2557.4000, 2557.4000, 0.5000, 0.0000, 2.8000, 2557.4000
#
# #########################################################################
# Output filepath_blotter ='./blotter/Future/IF/IF_50_30.bl'
# datestimes, direction, lot, product, price, refprice, PNL, maxPNL, minPNL
# 2014-11-17 09:38:15, B, 1, IF, 2587.0000, 2586.1100
# 2014-11-17 09:40:15, S, 1, IF, 2581.8000, 2582.5770, -5.2000, 1.4000, -5.2000
import os
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
import operation as op
import pandas as pd
import sys
import log
logger=log.setlog("strategy.py")
i_lot=1
class Strategy(object):
def __init__(self, s_prod, s_prodtype):
if not (s_prodtype in ["Future","Stock"]):
logger.error(r'prodtype not in ["Future","Stock"]. incorrect product type. ')
self.prod = s_prod
self.prodtype = s_prodtype
self.freq = None
self.freq2 =None
self.freq3 =None
def preparedata(self):
import pandas as pd
import glob,os,sys
import multiprocessing as mp
import indicator as ic
import log
logger = log.setlog("gencator.py")
stock_freq = ['5min','15min','1H','1D']
future_freq = ['4s','15s','1min']
def generate_all():
try:
if s_prodtype not in ["Future","Stock"]:
logger.error("incorrect product type")
return
## grab all prods under ts directory
prodlist = glob.glob('./ts/'+s_prodtype+'/*')
prodnamelist = []
for prod in prodlist:
prodname = prod.split('/')[-1]
prodnamelist.append(prodname)
if len(prodnamelist)==0:
logger.warning("no prod to generate")
return
else:
logger.info("{} prods to generate indicator (.ics)".format(len(prodnamelist)))
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import urllib
import urllib2
import cookielib
import base64
import re
import json
import rsa
import binascii
import redis
#logger
import log
logger=log.setlog("backtester.py")
#global variable
userMap={}
#redis-server
r = redis.Redis(host='localhost',port=6379,db=0)
class weiboLogin:
cj = cookielib.LWPCookieJar()
cookie_support = urllib2.HTTPCookieProcessor(cj)
opener = urllib2.build_opener(cookie_support, urllib2.HTTPHandler)
urllib2.install_opener(opener)
postdata = {
'entry': 'weibo',
'gateway': '1',
