#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat May 5 12:43:52 2018@author: luogan """# -*- coding: utf-8 -*- """ Created on Thu Dec 14 15:26:31 2017@author: 量化之王 """import pymongo import pandasimport pandas as pd import matplotlib.pyplot as plt import numpy as np import pylab as pl import datetime import matplotlib.pyplot as plt from matplotlib.dates import DateFormatter, WeekdayLocator, DayLocator, MONDAY,YEARLY from matplotlib.finance import quotes_historical_yahoo_ohlc, candlestick_ohlcfrom matplotlib.pylab import date2numimport talib from dateutil.parser import parse import tushare as tsclient1 = pymongo.MongoClient('192.168.10.182',27017) db1 = client1.stock.low_closedef before_month_lastday(ti,k):from dateutil.parser import parsetoday=parse(str(ti))#first = datetime.date(day=1, month=today.month, year=today.year)lastMonth = today - datetime.timedelta(days=k)def plus(k):if k<10:return '0'+str(k)else:return str(k)y=lastMonth.yearm=lastMonth.monthd=lastMonth.day#day=calendar.monthrange(y,m)[1]cc=str(y)+plus(m)+plus(d)#bb=parse(cc)#pacific = pytz.timezone('Asia/Shanghai')#return pacific.localize(bb) return int(cc) def polyfit(c,k):#print(close)xlist=list(range(len(c)))bbz1 = np.polyfit(xlist, c,k)# 生成多項式對象{#bbp1 = np.poly1d(bbz1)#f5=bbp1(pl-1)#f6=bbp1(pl)return bbz1[0]def potential_index(tl):#df=ts.get_hist_data(name,start=bf,end=now)df=ts.get_hist_data(tl[0],start=tl[1],end=tl[2])if str(type(df))!="<class 'NoneType'>":if df.shape[0]>250:date=df.indexdate1=list(map(parse,date))df['date']=date1df=df.sort_values(by='date')#print('df=',df)#df=ts.get_k_data('002230',start='2015-01-12',end='2018-04-30')#提取收盤價closed=df['close'].valuesopend=df['open'].valueslow=df['low'].values#獲取均線的數據，通過timeperiod參數來分別獲取 5,10,20 日均線的數據。#ma5=talib.SMA(closed,timeperiod=30)#ma10=talib.SMA(closed,timeperiod=60)#ma250=talib.SMA(closed,timeperiod=250)p=closed[-1]o=opend[-1]opp=min(p,o)n=low[-1]#print('p=',p)#print('n=',n)ra=(opp-n)/opp#print('kk=',kk)#print('ra=',ra)if ra>=0.05:#print('kk=',kk)print('ra=',ra)print('name',tl[0])#db1.insert_one({'name':tl[0],'ratio':ra})#db1.save({'name':tl[0]})tt=before_month_lastday(tl[2],0)#db1.save({'name':tl[0],'potential':vv})#return vv*1.0db1.replace_one({"name":tl[0],"date":tt},{ "name":tl[0],"date":tt,'ratio':round(ra,2)},True)print('$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$$')#return vv*1.0#mm=potential_index(code[100])ak=ts.get_stock_basics()code=list(ak.index)def front_step_time(day):now = datetime.datetime.now()front = now - datetime.timedelta(days=day)d1 = front.strftime('%Y-%m-%d')#return int(d1)return d1now=front_step_time(0)bf=front_step_time(720)sheet=pd.DataFrame() sheet['code']=codesheet['bf']=bf sheet['sta']=now #name='600354' #b1=potential_vocanol(name,'2017-11-14','2018-02-14') #b2=potential_vocanol(name,'2018-02-14','2018-04-13')import time from multiprocessing import Pool import numpy as npte =sheet.values''' for name in te:mm=potential_index(name)#print(name,mm)''' if __name__ == "__main__" :startTime = time.time()testFL =sheet.values#ll=codepool = Pool(20)#可以同時跑10個進程pool.map(potential_index,testFL)pool.close()pool.join() endTime = time.time()print ("time :", endTime - startTime) { "_id" : ObjectId("5aed3d531815c4ffea37f824"), "name" : "300519", "date" : NumberInt(20180505), "ratio" : 0.06 } { "_id" : ObjectId("5aed3d571815c4ffea37f835"), "name" : "002806", "date" : NumberInt(20180505), "ratio" : 0.06 } { "_id" : ObjectId("5aed3d5e1815c4ffea37f850"), "name" : "600753", "date" : NumberInt(20180505), "ratio" : 0.08 } { "_id" : ObjectId("5aed3d5e1815c4ffea37f854"), "name" : "002047", "date" : NumberInt(20180505), "ratio" : 0.06 } { "_id" : ObjectId("5aed3d621815c4ffea37f865"), "name" : "002726", "date" : NumberInt(20180505), "ratio" : 0.08 } { "_id" : ObjectId("5aed3d661815c4ffea37f878"), "name" : "002592", "date" : NumberInt(20180505), "ratio" : 0.08 } { "_id" : ObjectId("5aed3d661815c4ffea37f87a"), "name" : "002584", "date" : NumberInt(20180505), "ratio" : 0.1 } { "_id" : ObjectId("5aed3d671815c4ffea37f87e"), "name" : "002161", "date" : NumberInt(20180505), "ratio" : 0.06 } { "_id" : ObjectId("5aed3d801815c4ffea37f8e1"), "name" : "002691", "date" : NumberInt(20180505), "ratio" : 0.09 }

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