all_stocks = DataAPI.SecTypeRegionRelGet(secID=u"",ticker=u"",typeID=u"",field=u"",pandas="1")

fbl = 



for code in all_stocks['secID']:

    df = DataAPI.MktEqudGet(secID=code,ticker=u"",tradeDate=u"",beginDate=u"20120101",endDate=u"",isOpen="",field=u"",pandas="1")

    df['ztj']=map(lambda x:round(x,2),df['preClosePrice']*1.1)

    df['chgPct']=df['chgPct']*100

    

    # 非一字板

    zt = df[(df['ztj']==df['highestPrice']) & (df['openPrice']!=df['highestPrice'])]

    fz= df[(df['ztj']==df['highestPrice']) & (df['openPrice']!=df['highestPrice'])&(df['closePrice']==df['highestPrice'])]

    try:

        f = len(fz)*1.00/len(zt)*100

        fbl.append((code,f))

    except Exception,e:

        print e

        print code

dx= dict(fbl)

x = np.array(dx.values())

print x.mean()

# -*- coding=utf-8 -*-

import datetime



__author__ = 'Rocky'

'''

http://30daydo.com

Contact: weigesysu@qq.com

'''

# 每天的涨跌停

import urllib2, re, time, xlrd, xlwt, sys, os

import setting

import pandas as pd

import tushare as ts

from setting import LLogger

reload(sys)

sys.setdefaultencoding('gbk')



logger = LLogger('zdt.log')

class GetZDT:

    def __init__(self,current):

        self.user_agent = "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Ubuntu Chromium/64.0.3282.167 Chrome/64.0.3282.167 Safari/537.36"

        # self.today = time.strftime("%Y%m%d")

        self.today=current

        self.path = os.path.join(os.path.dirname(__file__), 'data')

        self.zdt_url = 'http://home.flashdata2.jrj.com.cn/limitStatistic/ztForce/' + self.today + ".js"

        self.zrzt_url = 'http://hqdata.jrj.com.cn/zrztjrbx/limitup.js'



        self.host = "home.flashdata2.jrj.com.cn"

        self.reference = "http://stock.jrj.com.cn/tzzs/z ... ot%3B



        self.header_zdt = {"User-Agent": self.user_agent,

                           "Host": self.host,

                           "Referer": self.reference}



        self.zdt_indexx = [u'代码', u'名称', u'最新价格', u'涨跌幅', u'封成比', u'封流比', u'封单金额', u'最后一次涨停时间', u'第一次涨停时间', u'打开次数',

                           u'振幅',

                           u'涨停强度']



        self.zrzt_indexx = [u'序号', u'代码', u'名称', u'昨日涨停时间', u'最新价格', u'今日涨幅', u'最大涨幅', u'最大跌幅', u'是否连板', u'连续涨停次数',

                            u'昨日涨停强度', u'今日涨停强度', u'是否停牌', u'昨天的日期', u'昨日涨停价', u'今日开盘价格', u'今日开盘涨幅']

        self.header_zrzt = {"User-Agent": self.user_agent,

                            "Host": "hqdata.jrj.com.cn",

                            "Referer": "http://stock.jrj.com.cn/tzzs/zrztjrbx.shtml"

                            }



    def getdata(self, url, headers, retry=5):

        req = urllib2.Request(url=url, headers=headers)

        for i in range(retry):

            try:

                resp = urllib2.urlopen(req,timeout=20)

                content = resp.read()

                md_check = re.findall('summary|lasttradedate',content)

                if content and len(md_check)>0:

                    return content

                else:

                    time.sleep(60)

                    logger.log('failed to get content, retry: {}'.format(i))

                    continue

            except Exception, e:

                logger.log(e)

                time.sleep(60)

                continue

        return None



    def convert_json(self, content):

        p = re.compile(r'"Data":(.*)};', re.S)

        if len(content)<=0:

            logger.log('Content\'s length is 0')

            exit(0)

        result = p.findall(content)

        if result:

            try:

            # print result

                t1 = result[0]

                t2 = list(eval(t1))

                return t2

            except Exception,e:

                logger.log(e)

                return None

        else:

            return None





    def save_to_dataframe(self, data, indexx, choice, post_fix):

        engine = setting.get_engine('db_zdt')

        if not data:

            exit()

        data_len = len(data)

        if choice == 1:

            for i in range(data_len):

                data[i][choice] = data[i][choice].decode('gbk')



        df = pd.DataFrame(data, columns=indexx)



        filename = os.path.join(self.path, self.today + "_" + post_fix + ".xls")

        if choice == 1:

            df[u'今天的日期']=self.today

            df.to_excel(filename, encoding='gbk')

            try:

                df.to_sql(self.today + post_fix, engine, if_exists='fail')

            except Exception,e:

                logger.log(e)





    def storedata(self):

        zdt_content = self.getdata(self.zdt_url, headers=self.header_zdt)

        logger.log('zdt Content'+zdt_content)

        zdt_js = self.convert_json(zdt_content)

        self.save_to_dataframe(zdt_js, self.zdt_indexx, 1, 'zdt')

        time.sleep(5)



if __name__ == '__main__':

    date_list = [datetime.datetime.strftime(i,'%Y%m%d') for i in list(pd.date_range('20170401','20171231'))]

    for today in date_list:



        if not ts.is_holiday(datetime.datetime.strptime(today,'%Y%m%d').strftime('%Y-%m-%d')):

            print today

            obj = GetZDT(today)

            obj.storedata()

        else:

            logger.log('Holiday')

[/i][/i]

#-*-coding=utf-8

'''

可转债监控

'''

import tushare as ts

from setting import get_engine

engine = get_engine('db_bond')

import pandas as pd

import datetime

class ConvertBond():



    def __init__(self):

        self.conn=ts.get_apis()

        self.allBonds=ts.new_cbonds(pause=2)

        self.onSellBond=self.allBonds.dropna(subset=['marketprice'])

        self.today=datetime.datetime.now().strftime('%Y-%m-%d %H:%M')



    def stockPrice(self,code):

        stock_df = ts.get_realtime_quotes(code)

        price = float(stock_df['price'].values[0])

        return price



    def dataframe(self):

        price_list=[]

        for code in self.onSellBond['scode']:

            price_list.append(self.stockPrice(code))

        self.onSellBond['stock_price']=price_list

        self.onSellBond['ratio'] = (

self.onSellBond['marketprice']

/(self.onSellBond['stock_price'] / self.onSellBond['convprice'])-1)*100

        self.onSellBond['Updated']=self.today

        self.onSellBond.to_sql('tb_bond',engine,if_exists='replace')



    def closed(self):

        ts.close_apis(self.conn)



def main():

    bond=ConvertBond()

    bond.dataframe()

    bond.closed()

if __name__=='__main__':

    main()

import os

import MySQLdb

MYSQL_USER = *********

MYSQL_PASSWORD = ********

MYSQL_HOST = *********

MYSQL_PORT = *****



def get_engine(db):

    engine = create_engine('mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8'.format(MYSQL_USER, MYSQL_PASSWORD, MYSQL_HOST, MYSQL_PORT, db))

    return engine

import tushare as ts

#获取2017年第3季度的盈利能力数据

ts.get_profit_data(2017,3)

def profit(code,start,end):

    try:

        df=ts.get_k_data(code,start=start,end=end)

    except Exception,e:

        print e

        return None

    try:

        p=(df['close'].iloc[-1]-df['close'].iloc[0])/df['close'].iloc[0]*100.00

    except Exception,e:

        print e

        return None 

    return round(p,2)

profit('300678','2016-12-31','2017-12-31')

def price_change():

    basic=ts.get_stock_basics()

    pro=



    for code in basic.index.values:

        print code

        p=profit(code,'2016-12-31','2017-12-31')

        pro.append(p)

    basic['price_change']=pro

    basic.to_csv('2017_all_price_change.xls',encoding='gbk')

    df=pd.read_csv('2017_all_price_change.xls',encoding='gbk')

    df.to_excel('2017_all_price_change.xls',encoding='gbk')

def analysis():

    df=pd.read_excel('2017_all_price_change.xls',encoding='gbk')

    df=df.sort_values(by='price_change',ascending=False)

    df.to_excel('2017-year.xls',encoding='gbk')

engine=get_engine('stock')

df.to_sql('2017years',engine)

def get_engine(db):

    engine = create_engine('mysql+pymysql://{}:{}@{}:{}/{}?charset=utf8'.format(MYSQL_USER, MYSQL_PASSWORD, MYSQL_HOST, MYSQL_PORT, db))

    return engine

• 2017-year.zip

    df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [10, 20, 30, 40, 50]})

    df2 = pd.DataFrame({'A': [6], 'B': [60]})

    print 'df\n', df

    print 'df2\n', df2



    df_x = [df, df2]

    result = pd.concat(df_x)

    print 'first result\n', result

result2= result.reset_index()

result2 = result.reset_index(drop=True)

result3 = result.reindex(columns=['A','C'])

    df = pd.DataFrame({'A': [1, 2, 3, 4, 5], 'B': [10, 20, 30, 40, 50]})

    df2 = pd.DataFrame({'A': [6], 'B': [60]})

    print 'df\n', df

    print 'df2\n', df2

    df_x = [df, df2]

    result = pd.concat(df_x)

    print 'first result\n', result

    basic=ts.get_stock_basics()

    

    print basic.info()

    print basic.head(10)



    basic.to_excel('basic2017.xls',encoding='gbk')

    basic.to_csv('2017_all_price_change.xls',encoding='gbk')

    df=pd.read_csv('2017_all_price_change.xls',encoding='gbk')

    df.to_excel('2017_all_price_change.xls',encoding='gbk')

	df=pd.read_excel('600050.xls',dtype={'datetime':np.datetime64})

	df=df.set_index('datetime')

	df['close'].plot(use_index=True,grid=True)

	plt.show()

这个策略是我做虚拟货币以来的主要策略，后面经过不断完善和修改，复杂了很多，但主要思想并没有改变，分享的这个版本是无明显bug的 最初版本，最为简单清晰，没有仓位管理，每次交易都是满仓，没有卡死后重启等等，但也足够说明问题。

function GetPrice(Type) {

   //_C()是平台的容错函数

    var depth=_C(exchange.GetDepth);

    var amountBids=0;

    var amountAsks=0;

    //计算买价，获取累计深度达到预设的价格

    if(Type=="Buy"){

       for(var i=0;i<20;i++){

           amountBids+=depth.Bids[i].Amount;

           //参数floatamountbuy是预设的累计深度

           if (amountBids>floatamountbuy){

               //稍微加0.01，使得订单排在前面

              return depth.Bids[i].Price+0.01;}

        }

    }

    //同理计算卖价

    if(Type=="Sell"){

       for(var j=0; j<20; j++){

    	   amountAsks+=depth.Asks[j].Amount;

            if (amountAsks>floatamountsell){

            return depth.Asks[j].Price-0.01;}

        }

    }

    //遍历了全部深度仍未满足需求，就返回一个价格，以免出现bug

    return depth.Asks[0].Price

}



// 每个循环的主函数onTick(),这里定的循环时间3.5s，每次循环都会把原来的单子撤销，重新挂单，越简单越不会遇到bug.



function onTick() {

    var buyPrice = GetPrice("Buy");

    var sellPrice= GetPrice("Sell");

    //diffprice是预设差价，买卖价差如果小于预设差价，就会挂一个相对更深的价格

    if ((sellPrice - buyPrice) <= diffprice){

            buyPrice-=10;

            sellPrice+=10;}

    //把原有的单子全部撤销，实际上经常出现新的价格和已挂单价格相同的情况，此时不需要撤销

    CancelPendingOrders() 

    //获取账户信息，确定目前账户存在多少钱和多少币

    var account=_C(exchange.GetAccount);

    //可买的比特币量，_N()是平台的精度函数

    var amountBuy = _N((account.Balance / buyPrice-0.1),2); 

    //可卖的比特币量，注意到没有仓位的限制，有多少就买卖多少，因为我当时的钱很少

    var amountSell = _N((account.Stocks),2); 

    if (amountSell > 0.02) {

        exchange.Sell(sellPrice,amountSell);}

    if (amountBuy > 0.02) {

        exchange.Buy(buyPrice, amountBuy);}

    //休眠，进入下一轮循环

    Sleep(sleeptime);

}

date = date + '-01-01'

        cmd = 'select * from `{}` where datetime > \'{}\''.format(code, date)



        try:

            df = pd.read_sql(cmd, history_engine,index_col='index')

        except Exception,e:

            print e

            return None

        

        # 不知道为啥，这里的类型发生改变

        idx= df['low'].idxmin()

datetime    datetime64[ns]

code                object

name                object

open                object

close               object

high                object

low                 object

vol                float64

amount             float64

dtype: object

df['low']=df['low'].astype('float64')

# -*-coding=utf-8-*-

__author__ = 'Rocky'

'''

http://30daydo.com

Contact: weigesysu@qq.com

'''

import random

import hashlib

import hmac,time

import smtplib

from email.mime.text import MIMEText

from email import Utils

import threading

import requests,datetime,itchat



from toolkit import Toolkit





class Jubi_web():

    def __init__(self, send=None):

        cfg = Toolkit.getUserData('data.cfg')

        self.public_key = cfg['public_key']

        self.private_key = cfg['private_key']

        self.send=send

        from_mail = cfg['from_mail']

        password = cfg['password']

        to_mail = cfg['to_mail']

        smtp_server = 'smtp.qq.com'



        self.server = smtp_server

        self.username = from_mail.split("@")[0]

        self.from_mail = from_mail

        self.password = password

        self.to_mail = to_mail

        self.coin_list=['IFC','DOGE','EAC','DNC','MET','ZET','SKT','YTC','PLC','LKC',

                        'JBC','MRYC','GOOC','QEC','PEB','XRP','NXT','WDC','MAX','ZCC',

                        'HLB','RSS','PGC','RIO','XAS','TFC','BLK','FZ','ANS','XPM','VTC',

                        'KTC','VRC','XSGS','LSK','PPC','ETC','GAME','LTC','ETH','BTC']

        # 初始化邮箱设置读取需要股票信息

        # 这样子只登陆一次

        if self.send == 'msn':



            try:

                self.smtp = smtplib.SMTP_SSL(port=465)

                self.smtp.connect(self.server)

                self.smtp.login(self.username, self.password)

            except smtplib.SMTPException, e:

                print e

                return 0



        if send=='wechat':

            self.w_name=u'xxxxx'

            

            itchat.auto_login(hotReload=True)

            account=itchat.get_friends(self.w_name)





    def send_wechat(self,name,content):

        w_content=name+' '+content

        itchat.send(w_content,toUserName=self.toName)

        time.sleep(1)

        itchat.send(w_content,toUserName='filehelper')





    def send_text(self, name, content):



        subject = '%s' % name

        self.msg = MIMEText(content, 'plain', 'utf-8')

        self.msg['to'] = self.to_mail

        self.msg['from'] = self.from_mail

        self.msg['Subject'] = subject

        self.msg['Date'] = Utils.formatdate(localtime=1)

        try:

            self.smtp.sendmail(self.msg['from'], self.msg['to'], self.msg.as_string())

            self.smtp.quit()

            print "sent"

        except smtplib.SMTPException, e:

            print e

            return 0



    def warming(self, coin, up_price, down_price):

        url = 'https://www.jubi.com/api/v1/ticker/'

        while 1:

            time.sleep(5)

            try:

                data = requests.post(url, data={'coin': coin}).json()

            except Exception,e:

                print e

                print "time out. Retry"

                time.sleep(15)

                continue



            current = float(data['last'])

            if current >= up_price:

                print "Up to ", up_price

                print "current price ",current



                if self.send=='msn':

                    self.send_text(coin,str(current))

                if self.send=='wechat':

                    self.send_wechat(coin,str(current))



                time.sleep(1200)

            if current <= down_price:

                print "Down to ", down_price

                print "current price ",current

                if self.send=='msn':

                    self.send_text(coin,str(current))

                if self.send=='wechat':

                    self.send_wechat(coin,str(current))

                time.sleep(1200)

    #上面的内容尽量不用修改。





    def getContent(self):

        url = 'https://www.jubi.com/api/v1/trade_list'

        params_data = {'key': 'x', 'signature': 'x'}

        s = requests.get(url=url, params=params_data)



    def getHash(self, s):

        m = hashlib.md5()

        m.update(s)

        return m.hexdigest()



    def sha_convert(self, s):

        return hashlib.sha256(self.getHash(s)).hexdigest()



    def get_nonce(self):

        lens = 12

        return ''.join([str(random.randint(0, 9)) for i in range(lens)])



    def get_signiture(self):

        url = 'xxxxxxxxx'

        coin = 'zet'

        nonce = self.get_nonce()



        # sha=self.sha_convert(private_key)

        md5 = self.getHash(self.private_key)

        message = 'nonce=' + nonce + '&' + 'key=' + self.public_key

        # print message

        signature = hmac.new(md5, message, digestmod=hashlib.sha256).digest()

        # print signature



        # req=requests.post(url,data={'signature':signature,'key':public_key,'nonce':nonce,'coin':'zet'})

        req = requests.post(url, data={'coin': coin})

        print req.status_code

        print req.text



    def real_time_ticker(self, coin):

        url = 'xxxxxxxx'

        try:

            data = requests.post(url, data={'coin': coin}).json()

            #print data

        except Exception ,e:

            print e

        return data





    def real_time_depth(self, coin):

        url = 'xxxxxxxxx'

        data = requests.post(url, data={'coin': coin}).json()

        print data

        data_bids = data['bids']

        data_asks = data['asks']

        print "bids"

        for i in data_bids:

            print i[0],

            print ' ',

            print i[1]

        print "asks"

        for j in data_asks:

            print j[0],

            print ' ',

            print j[1]



    def list_all_price(self):

        for i in self.coin_list:

            print i,

            print " price: ",

            p=self.real_time_ticker(i.lower())

            if p is not None:

                print p[u'last']



    def getOrder(self,coin):

        url='https://www.jubi.com/api/v1/orders/'

        try:

            req=requests.get(url,params={'coin':coin})

        except Exception,e:

            print e



        data=req.json()

        return data

    # recent 100 trade turn over

    def turnover(self,coin):

        i=coin.lower()

        coins=Toolkit.getUserData('coins.csv')

        total=long(coins[i])

[i]        [/i]p=self.getOrder(i)

        print p

        amount=0.00

        for j in p:

            t= j[u'amount']

            amount=float(t)+amount

        #current=float(self.real_time_ticker(i)[u'last'])

        turn_over=amount*1.00/total*100

        print turn_over



    def multi_thread(self,coin_list,price_list):

        thread_num=len(coin_list)

        thread_list=

        for i in range(thread_num):

            t=threading.Thread(target=self.warming, args=(coin_list,price_list[0],price_list[1]),)

            thread_list.append(t)

        for j in thread_list:

            j.start()

        for k in thread_list:

            k.join()



if __name__ == '__main__':



    obj = Jubi_web(send='wechat')

    coin_list=['zet','doge']

    price_list=[[0.2,0.13],[0.03,0.024]]

    obj.multi_thread(coin_list,price_list)



[/i]

    #通过tushare获取股票信息

    df=ts.get_k_data('300580',start='2017-01-12',end='2017-05-26')

    #提取收盘价

    closed=df['close'].values

    

    upper,middle,lower=talib.BBANDS(closed,matype=talib.MA_Type.T3)

    

    print upper,middle,lower

    plt.plot(upper)

    plt.plot(middle)

    plt.plot(lower)

    plt.grid()

    plt.show()

    diff1=upper-middle

    diff2=middle-lower

    print diff1

    print diff2

    #通过tushare获取股票信息

    df=ts.get_k_data('300580',start='2017-01-12',end='2017-05-26')

    #提取收盘价

    closed=df['close'].values

    #获取均线的数据，通过timeperiod参数来分别获取 5,10,20 日均线的数据。

    ma5=talib.SMA(closed,timeperiod=5)

    ma10=talib.SMA(closed,timeperiod=10)

    ma20=talib.SMA(closed,timeperiod=20)



    #打印出来每一个数据

    print closed

    print ma5

    print ma10

    print ma20



    #通过plog函数可以很方便的绘制出每一条均线

    plt.plot(closed)

    plt.plot(ma5)

    plt.plot(ma10)

    plt.plot(ma20)

    #添加网格，可有可无，只是让图像好看点

    plt.grid()

    #记得加这一句，不然不会显示图像

    plt.show()