Esempio n. 1
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def get_day_cinema(day=None):
    if day == None:
        try:
            result = ts.day_cinema().to_json()
        except Exception as e:
            result = json.dumps({"error":True,"message":str(e)})
    else:
        try:
            result = ts.day_cinema(day).to_json()
        except Exception as e:
            result = json.dumps({"error":True,
            "message":"can not get the data, format date as YYYY-M-D,error:{error}".format(error=e.message)})
    return result
Esempio n. 2
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def job_9():
    try:
        print("I'm working......电影票房")
        # 实时票房
        realtime_boxoffice = ts.realtime_boxoffice()
        data = pd.DataFrame(realtime_boxoffice)
        data.to_sql('realtime_boxoffice',engine,index=True,if_exists='replace')
        print("实时票房......done")

        # 每日票房
        day_boxoffice = ts.day_boxoffice()
        data = pd.DataFrame(day_boxoffice)
        data.to_sql('day_boxoffice',engine,index=True,if_exists='replace')
        print("每日票房......done")

        # 月度票房
        month_boxoffice = ts.month_boxoffice()
        data = pd.DataFrame(month_boxoffice)
        data.to_sql('month_boxoffice',engine,index=True,if_exists='replace')
        print("月度票房......done")

        # 影院日度票房
        day_cinema = ts.day_cinema()
        data = pd.DataFrame(day_cinema)
        data.to_sql('day_cinema',engine,index=True,if_exists='replace')
        print("影院日度票房......done")
    except Exception as e:
        print(e)
Esempio n. 3
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def get_movie():
    # mov = ts.realtime_boxoffice()
    # print(mov.to_json())
    df = ts.day_cinema()  # 取上一日全国影院票房排行数据
    # df = ts.day_cinema('2015-12-24') #取指定日期的数据
    df.head(10)
    print(df.to_json())
Esempio n. 4
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def cinema():
    dd = tu.day_cinema()
    dd_data = nu.array(dd)
    dd_list = dd_data.tolist()
    send_dd_list = []
    for i in dd_list[:10]:
        send_dd_list.append('-'.join(i))
    send_dd_list.insert(0, u"上座率-场均人次-影院名称-排名-今日观众-今日票房-今日场次-场均票价")
    str_send_dd_list = '\n'.join(send_dd_list)
    return str_send_dd_list
Esempio n. 5
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def get_day_cinema(day=None):
    df = ts.day_cinema(day)
    if df is not None:
        if day is None:
            day = get_yesterday()
        df.insert(0, 'date', day)
        res = df.to_sql(fun_day_cinema, engine, if_exists='replace')
        msg = 'ok' if res is None else res
        print('获取全国影院指定单日:{0}票房排行数据: {1} '.format(day, msg) + '\n')
    else:
        print('获取全国影院指定单日:{0}票房排行数据: {1} '.format(day, 'None') + '\n')
Esempio n. 6
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def updateDayCinema(con, date: datetime):
    import share.model.dao.boxoffice.DayCinema as Model
    dateString = date.strftime("%Y-%m-%d")
    logging.debug("Updating day cinema of {}".format(dateString))
    df = ts.day_cinema(date=dateString,retry_count=16)
    res = []
    for _, row in df.iterrows():
        obj = Model.rowToORM(row, date=date)
        if obj is not None:
            res.append(obj)
    Base.metadata.create_all(con.engine)
    con.save_all(res)
    return
Esempio n. 7
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def cinema_office((start_date,end_date)):
    startdate = datetime .datetime .strptime(start_date ,'%Y-%m-%d').date()
    enddate = datetime .datetime .strptime(end_date ,'%Y-%m-%d').date()
    date_list = date_loop .date_loop_all(start_date= startdate ,end_date= enddate )
    DTS = []

    for date in date_list:
        preDTS = ts.day_cinema(date=date)
        preDTS['date'] = date
        DTS.append(preDTS)

    DTS = pd.concat(DTS)

    return DTS
Esempio n. 8
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def get_day_cinema(day=None):
    print(day)
    if day == None:
        try:
            total = ts.day_cinema().to_csv().split()
            head = [TRANS.get(i) for i in total[0].split(",")]
            body = [line.split(",") for line in total[1:]]
            result = {"head": head, "body": body}
        except Exception as e:
            result = {"error": "true", "message": str(e)}
    else:
        try:
            total = ts.day_cinema(day).to_csv().split()
            head = [TRANS.get(i) for i in total[0].split(",")]
            body = [line.split(",") for line in total[1:]]
            result = {"head": head, "body": body}
        except Exception as e:
            result = {
                "error": "true",
                "message": "can not get the data, format date as YYYY-M-D"
            }
    print("result")
    print(result)
    return result
Esempio n. 9
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import tushare as ts

# 实时票房
ts.realtime_boxoffice()

# 每日票房
ts.day_boxoffice()  #取上一日的数据
ts.day_boxoffice('2010-01-01')  #取指定日期的数据

# 月度票房
ts.month_boxoffice()  #取上一月票房数据
ts.month_boxoffice('2019-02')  #此月数据

# 影院日度票房
ts.day_cinema()  #取上一日全国影院票房排行数据
df = ts.day_cinema('2019-02-05')  # 指定日期的数据 2019年春节
df.to_excel('movie.xlsx')  # pip install openpyxl
Esempio n. 10
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import tushare as ts
from sqlalchemy import create_engine
token = ts.set_token(
    'c723069dd4a25402d05ea6afad36da2937111adf012f8258abb5f7e05936e575')
#engine = create_engine('mysql+pymysql://root:[email protected]/packageing?charset=utf8')
engine = create_engine(
    'mysql+pymysql://root:[email protected]/gupiao?charset=utf8')

realtime = ts.realtime_boxoffice()
#realtime.to_sql('realtime_boxoffice',engine)
realtime.to_sql('realtime_boxoffice', engine, if_exists='append')

day = ts.day_boxoffice()
#day.to_sql('day_boxoffice',engine)
day.to_sql('day_boxoffice', engine, if_exists='append')

month = ts.month_boxoffice()
#month.to_sql('month_boxoffice',engine)
month.to_sql('month_boxoffice', engine, if_exists='append')

cinema = ts.day_cinema()
#cinema.to_sql('day_cinema',engine)
cinema.to_sql('day_cinema', engine, if_exists='append')
Esempio n. 11
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import tushare as ts

# 实时票房
# 获取实时电影票房数据,30分钟更新一次票房数据,可随时调用。
df = ts.realtime_boxoffice()
print(df)

# 每日票房
# 获取单日电影票房数据,默认为上一日的电影票房,可输入参数获取指定日期的票房。
# 似乎只能显示前一日的
df = ts.day_boxoffice("2015-01-01")
print(df)

# 月度票房
# 获取单月电影票房数据,默认为上一月,可输入月份参数获取指定月度的数据。
df = ts.month_boxoffice('2016-12')
print(df)

# 影院日度票房
# 获取全国影院单日票房排行数据,默认为上一日,可输入日期参数获取指定日期的数据。
df = ts.day_cinema('2015-12-24')
print(df)
Esempio n. 12
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g_p.index=g_p.month;g_p
g_p.plot();
#工业品价格指数
g_p1=g_p[['ppiip','ppi','qm','rmi','pi']].dropna()
g_p1.plot();
#生活价格指数
g_p2=g_p[['cg','food','clothing','roeu','dcg']].dropna();g_p2
g_p2.plot(grid=True)

###10.4 电影票房数据的实时分析
#实时票房
#获取实时电影票房数据,30分钟更新一次票房数据,可随时调用。
r_b = ts.realtime_boxoffice()
r_b.info()
r_b

plt.barh(r_b.MovieName,r_b.BoxOffice.astype(float));
plt.pie(r_b.boxPer,labels=r_b.MovieName);

#每日票房
d_b = ts.day_boxoffice() #取上一日的数据
d_b

#影院日度票房
#获取全国影院单日票房排行数据,默认为上一日,可输入日期参数获取指定日期的数据。
d_c=ts.day_cinema() #取上一日全国影院票房排行数据
d_c.info()

d_c[:10]
plt.barh(d_c.CinemaName[:10],d_c.Attendance.astype(float)[:10]);
Esempio n. 13
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def capture_stock_data():
    capture_date = datetime.datetime.now().strftime("%Y%m%d")
    save_dir = "/home/dandelion/stock_data/" + capture_date

    if not os.path.exists(save_dir):
        os.mkdir(save_dir)
        print("The save directory is created successfully!\n", save_dir)
    print("The save directory is already exist!\n", save_dir)
    # ======================Daily Command================================================================
    # get the boxoffcie data of the last day and save as csvfile named as the capture command
    ts.day_boxoffice().to_csv(
        save_dir + "/" + capture_date + "_day_boxoffice.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("day_boxoffice data capture completed!")

    # get the cinema data of the last day and save as csvfile named as the capture command
    ts.day_cinema().to_csv(
        save_dir + "/" + capture_date + "_day_cinema.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("day_cinema data capture completed!")

    ts.month_boxoffice().to_csv(
        save_dir + "/" + capture_date + "_month_boxoffice.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("month_boxoffice data capture completed!")

    ts.realtime_boxoffice().to_csv(
        save_dir + "/" + capture_date + "_realtime_boxoffice.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("realtime_boxoffice data capture completed!")

    # get the stock data index of the last day and save as csvfile named as the capture command
    ts.get_index().to_csv(
        save_dir + "/" + capture_date + "_get_index.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_index data capture completed!")

    # get the history cpi data and save as csvfile named as the capture command
    ts.get_cpi().to_csv(
        save_dir + "/" + capture_date + "_get_cpi.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_cpi data capture completed!")

    # get the history gdp data  by month and save as csvfile named as the capture command
    ts.get_gdp_year().to_csv(
        save_dir + "/" + capture_date + "_get_gdp_year.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_gdp_year data capture completed!")

    # get today all stock data and save as csvfile named as the capture command
    # ts.get_today_all().to_csv(save_dir+'/'+capture_date+'_get_today_all.csv',header=True,sep=',',index=False)

    # get detail information of the top brokers today and save as csvfile named as the capture command
    ts.broker_tops().to_csv(
        save_dir + "/" + capture_date + "_broker_tops.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("broker_tops data capture completed!")

    # get detail information of the top brokers today and save as csvfile named as the capture command
    ts.cap_tops().to_csv(
        save_dir + "/" + capture_date + "_cap_tops.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("cap_tops data capture completed!")

    ts.get_area_classified().to_csv(
        save_dir + "/" + capture_date + "_get_area_classified.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_area_classified data capture completed!")

    # ts.get_balance_sheet(code='').to_csv(save_dir+'/'+capture_date+'_get_balance_sheet.csv',header=True,sep=',',index=False)
    # print('get_balance_sheet data capture completed!')

    # ts.get_cash_flow(code='').to_csv(save_dir+'/'+capture_date+'_get_cash_flow.csv',header=True,sep=',',index=False)
    # print('get_cash_flow data capture completed!')

    ts.get_day_all().to_csv(
        save_dir + "/" + capture_date + "_get_day_all.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_day_all data capture completed!")
    ts.get_cashflow_data(2018, 3).to_csv(
        save_dir + "/" + capture_date + "_get_cashflow_data.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_cashflow_data data capture completed!")
    ts.get_concept_classified().to_csv(
        save_dir + "/" + capture_date + "_get_concept_classified.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_concept_classified data capture completed!")
    ts.get_debtpaying_data(2018, 3).to_csv(
        save_dir + "/" + capture_date + "_get_debtpaying_data.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_debtpaying_data data capture completed!")
    ts.get_deposit_rate().to_csv(
        save_dir + "/" + capture_date + "_get_deposit_rate.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_deposit_rate data capture completed!")

    ts.get_gdp_contrib().to_csv(
        save_dir + "/" + capture_date + "_get_gdp_contrib.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_gdp_for().to_csv(
        save_dir + "/" + capture_date + "_get_gdp_for.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_gdp_pull().to_csv(
        save_dir + "/" + capture_date + "_get_gdp_pull.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_gdp_quarter().to_csv(
        save_dir + "/" + capture_date + "_get_gdp_quarter.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("get_gdp_ data capture completed!")
    # ts.get_gdp_year().to_csv(save_dir+'/'+capture_date+'_get_gdp_year.csv',header=True,sep=',',index=False)
    ts.get_gem_classified().to_csv(
        save_dir + "/" + capture_date + "_get_gem_classified.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_gold_and_foreign_reserves().to_csv(
        save_dir + "/" + capture_date + "_get_gold_and_foreign_reserves.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_growth_data(2018, 3).to_csv(
        save_dir + "/" + capture_date + "_get_growth_data.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_industry_classified().to_csv(
        save_dir + "/" + capture_date + "_get_industry_classified.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_hs300s().to_csv(
        save_dir + "/" + capture_date + "_get_hs300s.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_sz50s().to_csv(
        save_dir + "/" + capture_date + "_get_sz50s.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_zz500s().to_csv(
        save_dir + "/" + capture_date + "_get_zz500s.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_operation_data(2018, 3).to_csv(
        save_dir + "/" + capture_date + "_get_operation_data.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_stock_basics().to_csv(
        save_dir + "/" + capture_date + "_get_stock_basics.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.get_report_data(2018, 3).to_csv(
        save_dir + "/" + capture_date + "_get_report_data.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.inst_detail().to_csv(
        save_dir + "/" + capture_date + "_inst_detail.csv",
        header=True,
        sep=",",
        index=False,
    )
    ts.inst_tops().to_csv(
        save_dir + "/" + capture_date + "_inst_tops.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("inst_tops data capture completed!")
    ts.new_stocks().to_csv(
        save_dir + "/" + capture_date + "_new_stocks.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("new_stocks data capture completed!")
    ts.top_list().to_csv(
        save_dir + "/" + capture_date + "_top_list.csv",
        header=True,
        sep=",",
        index=False,
    )
    print("top_list data capture completed!")
Esempio n. 14
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def GetDayCinema():
    df = ts.day_cinema()
    df = df.head(10)
    df = df.to_json(force_ascii=False)
    print(df)
    return df
Esempio n. 15
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for i in range(aaa.shape[0]):
    print(aaa.iloc[i,1])
    print("aaa result={result}".format(result=aaa[i,1]))

df=pd.DataFrame(columns=['month','cpi'])
for i in range(aaa.shape[0]):
    gap=pd.DataFrame({"month":aaa.iloc[i,0],"cpi":(aaa.iloc[i,1].astype(float)-bbb.astype(float))})
    df=df.append(gap)



#票房数据
piaofang=ts.day_cinema('2017-10-02')

pd.set_option

pd.set_option('display.max_columns', 200)
pd.set_option('display.width', 1000)


piaofang[piaofang['price'].max()]

rl_piaofang=ts.realtime_boxoffice()

last_m_pf=ts.month_boxoffice('2017-07')

piaofang_df=pd.DataFrame()
Esempio n. 16
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ticker = '000547'

# 获取历史行情数据
# finace=ts.get_hist_data(ticker)
# print("获取历史行情数据")
# print(finace)
#
# # 获取实时行情数据
# datato = ts.get_today_all(ticker)
# print("获取实时行情数据")
# print(datato)

# # 获取实时分笔数据
# data=ts.get_realtime_quotes(ticker)
# print("获取实时分笔数据")
# print(data)

# 获取当日历史分笔数据
data_today = ts.get_today_ticks(ticker)
print("获取当日历史分笔数据")
print(data_today)
data_today.to_csv('000547.csv')
# data_today.to_excel('000547.xlsx')

df = ts.realtime_boxoffice()
print(df)

dd = ts.day_cinema()
print(dd)