Python tushare 模块，get_today_all() 实例源码

def get_basic():
    hsdq = stock_info.ix['300141']
    print hsdq
    report = ts.get_report_data(2014, 1)
    print report

    #hsdq=stock_info.ix['300141']
    #print hsdq
    #report=ts.get_report_data(2014,1)
    #print report
    print '*' * 20
    df = ts.get_today_all()
    zrkj = df[df['code'] == '300333']
    print type(zrkj)
    print type(zrkj['code'])
    print zrkj['name'].values[0]

def GetAllTodayData(self):
        #???? ????  ?,??????????
        filename=self.today+'_all_.xls'
        #??data????
        filename=os.path.join(self.path,filename)
        if not os.path.exists(filename):
            self.df_today_all=ts.get_today_all()
            #?????
            self.df_today_all.drop(self.df_today_all[self.df_today_all['turnoverratio']==0].index,inplace=True)
            #??????????
            #n1=self.df_today_all[self.df_today_all['turnoverratio']==0]
            #n2=self.df_today_all.drop(n1.index)
            #print n2
            print self.df_today_all
            self.df_today_all.to_excel(filename,sheet_name='All')

        else:
            self.df_today_all=pd.read_excel(filename,sheet_name='All')
            print "File existed"

def main():
    # ?????? ?3????
    history = ts.get_hist_data(id)

    print u"??3????"

    print history.head(10)

    history_all = ts.get_h_data(id, '20015101', '20160101')

    print u'???????'
    print history_all



    # print type(stockInfo)
    # print stockInfo.head()
    # print stockInfo.dtypes
    # df = ts.get_stock_basics()
    #data = df.ix[id]['timeToMarket']
    #print data
    #ts.get_today_all()

def general_info():
    t_all = ts.get_today_all()
    result = []
    t1 = t_all[t_all['changepercent'] <= -9.0].count()['changepercent']
    result.append(t1)
    for i in range(-9, 9, 1):
        temp = t_all[(i * 1.00 < t_all['changepercent']) & (t_all['changepercent'] <= (i + 1) * 1.00)].count()[
            'changepercent']
        result.append(temp)
    t2 = t_all[t_all['changepercent'] > 9.0].count()['changepercent']
    result.append(t2)
    return result

#test in sourcetree
#test in house
#????

def QA_fetch_get_stock_realtime():
    data = QATs.get_today_all()
    data_json = QA_util_to_json_from_pandas(data)
    return data_json

def filter_stock_by_average_pe(min, max):
    path = os.path.join(current_folder, '3????????????%s.csv' % today)
    if not os.path.exists(path):  # ?????3???????
        calcu_all_stocks_3year_average_profit(calcu_average_profit_end_year)

    gplb = pd.read_csv(path, index_col=0, encoding='utf-8')

    # ????????
    price_path = os.path.join(current_folder, today + '????.csv')
    if not os.path.exists(price_path):
        ts.get_today_all().set_index('code').to_csv(price_path, encoding="utf-8")

    current_price = pd.read_csv(price_path, encoding="utf-8", index_col=0)
    current_price = current_price[['trade']]
    current_price.columns = ['??']
    gplb = gplb[
        ['??', '??', '??', '????', '???', '???(?)', '????', '????', '????', '???', '????',
         '????']]

    data = pd.merge(gplb, current_price, left_index=True, right_index=True)
    # ??????????????????????????????
    data['?????'] = data['???'] * data['??'] * 10000 / data['????']
    print('%s:' % today)
    print()
    print('%d???' % data.shape[0])
    print('3???????%.1f' % round(data['?????'].median(), 1))
    print('3???????%.1f' % round(data['???'].median(), 1))
    data = data[data['?????'] < max]
    data = data[data['?????'] > min]
    data['?????'] = data['?????'].round(1)
    data['????'] = data['????'].round()
    data['???'] = data['???'].round(1)
    data['????'] = data['????'].round()
    data['????'] = data['????'].round()
    data['???'] = data['???'].round()
    data['????'] = data['????'].round()
    average_pe_file = os.path.join(current_folder, today + '-3???????%s?%s?????.xlsx' % (min, max))
    data.to_excel(average_pe_file)

def get_real_time():
    df = ts.get_today_all()
    print df

def save_excel():
    df = ts.get_today_all()
    df.to_excel('1.xls', sheet_name='all_stock')
    df2 = ts.get_hist_data('300333')
    df2.to_excel('1.xls', sheet_name='basic_info')
    df.ExcelWriter
    out = pd.ExcelWriter("2.xls")
    df.to_excel()

def gsz():
    hq = ts.get_today_all()
    hq['trade'] = hq.apply(lambda x: x.settlement if x.trade == 0 else x.trade, axis=1)
    basedata = stock_info[['outstanding', 'totals', 'reservedPerShare', 'esp']]
    hqdata = hq[['code', 'name', 'trade', 'mktcap', 'nmc']]
    hqdata = hqdata.set_index('code')
    data = basedata.merge(hqdata, left_index=True, right_index=True)
    print data.head(10)

def basic_usage():
    df = ts.get_today_all()
    print df[df['code'] == '000006']
    # print df.to_excel('tets.xls')
    #print df[df['code']=='000006']

def get_today_all():
    print "[%s] get_today_all" %(datetime.now().strftime("%H:%M:%S.%f"))
    df = ts.get_today_all()
    filename = PREFIX + '/' + 'today_all.csv'
    os.remove(filename)
    return save_to_file(filename, df)

def get_target(self):
        # lc = ts.get_today_all()
        # lc.to_csv('a.txt',encoding="utf-8")
        lc = pd.read_csv('a.txt',encoding='utf-8')
        lc_amount = lc.query('amount>10000000')
        lc_amount_except_ST = lc_amount[(lc_amount['name'].str.contains(stRegex, regex=True))]
        res = lc_amount_except_ST.sort_values(by="mktcap").head(self.__cnt)
        # print(res)
        # res = res[['code','name','trade','amount']]
        self.__target = res[['code','name','trade']]
        self.__target['share'] = 0
        self.__target['action'] = ''

def daily_market():
        df = ts.get_today_all()
        try:
            df.to_sql(SaveData.today,daily_engine,if_exists='replace')
        except Exception,e:
            print e
        print "Save {} data to MySQL".format(SaveData.today)

def __init__(self):
        self.today_stock=ts.get_today_all()
        now=datetime.datetime.now()
        self.today=now.strftime("%Y-%m-%d")
        #weekday=now+datetime.timedelta(days=-2)
        #weekday=weekday.strftime("%Y-%m-%d")
        #print weekday
        #today=now.strftime('%Y-%m-%d')
        self.path=os.path.join(os.getcwd(),'data')
        self.filename=os.path.join(self.path,'recordMyChoice.xls')

def daily_market(self):
        '''
        ????????????
        :return:
        '''
        df = ts.get_today_all()
        print df
        try:
            df.to_sql(self.today, daily_engine, if_exists='replace')
        except Exception, e:
            print e
        print "Save {} data to MySQL".format(self.today)

def base_function(self, id):
        if id == None:
            print "Input stock id please "
            return

        stockInfo = ts.get_hist_data(id)
        # print type(stockInfo)
        # print stockInfo.head()
        # print stockInfo.dtypes
        df = ts.get_stock_basics()
        data = df.ix[id]['timeToMarket']
        print data
        all_data = ts.get_today_all()
        print all_data.ix[id]['name']

def realtime(self, id):
        # all_stock=ts.get_today_all()
        # print all_stock
        df = ts.get_realtime_quotes(id)
        # print df[['time','name','price','bid','ask','volume']]
        # print df.head()
        # price_change = ts.get_today_ticks(id)
        # print price_change[['time','change','type','volume']]
        big_share = ts.get_sina_dd(id, date=self.date)
        print big_share[['time', 'code', 'price', 'preprice', 'volume', 'type']]
        print big_share.sort(columns='volume')

def main():
    now = time.strftime("%Y-%m-%d")
    # print now
    token = '60517739976b768e07823056c6f9cb0fee33ed55a1709b3eaa14a76c6a1b7a56'
    sb = StockBox()
    # sb.looper(id)
    id = '300333'
    # sb.realtime(id)
    sb.base_function("300333")
    # pandas_test=Pandas_test()
    # pandas_test.test_function()
    # sb.longhuban('2016-04-05')
    # sb.getNews()
    # sb.fund()
    #sb.get_stock_chengfeng()
    #sb.date_store()
    #sb.profit_test()
    #sb.daily_longhu()


    # ?????? ?3????
    history = ts.get_hist_data(id)

    print u"??3????"

    print history.head(10)

    history_all = ts.get_h_data(id, '20015101', '20160101')

    print u'???????'
    print history_all



    # print type(stockInfo)
    # print stockInfo.head()
    # print stockInfo.dtypes
    #df = ts.get_stock_basics()
    #data = df.ix[id]['timeToMarket']
    #print data
    #ts.get_today_all()

def realtime(self, id):
    # all_stock=ts.get_today_all()
    # print all_stock
    df = ts.get_realtime_quotes(id)
    # print df[['time','name','price','bid','ask','volume']]
    # print df.head()

    price_change = ts.get_today_ticks(id)
    print price_change[['time', 'change', 'type', 'volume']]
    big_share = ts.get_sina_dd(id, date='2016-04-01')
    print big_share[['time', 'code', 'price', 'preprice', 'volume', 'type']]

def stat_today_all(tmp_datetime):
    datetime_str = (tmp_datetime).strftime("%Y-%m-%d")
    datetime_int = (tmp_datetime).strftime("%Y%m%d")
    print("datetime_str:", datetime_str)
    print("datetime_int:", datetime_int)
    data = ts.get_today_all()
    # ?????????????????????????concat????
    if not data is None and len(data) > 0:
        # ??????
        # del data["reason"]
        data["date"] = datetime_int  # ??????int???
        data = data.drop_duplicates(subset="code", keep="last")
        data.head(n=1)
        common.insert_db(data, "ts_today_all", False, "`date`,`code`")
    else:
        print("no data .")

    time.sleep(5)  # ??5?

    data = ts.get_index()
    # ?????????????????????????concat????
    if not data is None and len(data) > 0:
        # ??????
        # del data["reason"]
        data["date"] = datetime_int  # ??????int???
        data = data.drop_duplicates(subset="code", keep="last")
        data.head(n=1)
        common.insert_db(data, "ts_index_all", False, "`date`,`code`")
    else:
        print("no data .")

    print(datetime_str)


# main????

def QA_fetch_get_stock_realtime():
    data = QATs.get_today_all()
    data_json = json.loads(data.to_json(orient='records'))
    return data_json

def plot_days():
    if request.method == 'GET' :
        today = ts.get_today_all()
        code_info = ts.get_industry_classified()

        today['code'] = today['code'].astype(unicode)
        one_day = gd.get_data_real_time(code_info, today)
        body = heatmap.get_heatmap('Today', one_day)
        return render_template('heatmap.html', body=body)

def update_market():
    df = ts.get_today_all()
    engine = create_engine('mysql://root:@127.0.0.1/stock_1.0?charset=utf8')
    #?????
    df.to_sql('current_market',engine,if_exists='replace')
    print("Done")

def update_market():
    df = ts.get_today_all()
    engine = create_engine('mysql://root:@127.0.0.1/stock_1.0?charset=utf8')
    #?????
    df.to_sql('current_market',engine,if_exists='replace')
    print("Done")

def get_today_codes():
    stock_basics = ts.get_today_all()
    return stock_basics.code.values