爬虫_1

import urllib.request
import time,re
import pandas as pd
from datetime import datetime, timedelta
# from tqdm import tqdm

# def get_data(base_url,tt):
#     html=urllib.request.urlopen(base_url).read().decode('utf-8')
#     html = str(html)
#     key_names =re.compile('.*?"NAME_":"(.*?)",')
#     key_aqi =re.compile('.*?,"AQI_":(.*?),')
#     PRIMARY_POLLUTANTS_ =re.compile('.*?"PRIMARY_POLLUTANTS_":"(.*?)",')
#     names = re.findall( key_names, html)
#     aqi = re.findall( key_aqi, html)
#     PRIMARY_POLLUTANTS_=re.findall(PRIMARY_POLLUTANTS_,html)
#     data = pd.DataFrame()
#     data['市/区/县'] = names
#     data['AQI_'+str(tt)] = aqi
#     data['首污_'+str(tt)]=PRIMARY_POLLUTANTS_
#     return data

def get_data_chengdu(base_url,tt):
    html=urllib.request.urlopen(base_url).read().decode('utf-8')
    html = str(html)
    key_names =re.compile('.*?{"CITY_":"(.*?)",')
    key_aqi =re.compile('.*?"AQI_":"(.*?)",')
    PRIMARY_POLLUTANTS_ =re.compile('.*?,"PRIMARY_POLLUTANTS_":"(.*?)"}')
    names = re.findall( key_names, html)
    aqi = re.findall( key_aqi, html)
    PRIMARY_POLLUTANTS_=re.findall(PRIMARY_POLLUTANTS_,html)
    data = pd.DataFrame()
    data['市/区/县'] = names
    data['AQI_'+str(tt)] = aqi
    data['首污_'+str(tt)]=PRIMARY_POLLUTANTS_
    return data


# def day_chengdu_area(days_2018,data_days):
#     for day_index in range(days_2018-3):
#         tt = datetime.strptime('20180102', "%Y%m%d") + timedelta(days=day_index)
#         tt = tt.strftime("%Y%m%d")
#         base_url = r'http://weixin.cdepb.gov.cn:20005/data/w/%E5%8C%BA%E5%8E%BF%E6%97%A5%E6%8E%92%E5%90%8D?' 
#                        r'token=78C579FA28C9B1E6C156A806C392458C&date={}&rows=1000&page=1'.format(tt)
#         # print(base_url)
#         data=get_data(base_url,tt)
#         data.index=data['市/区/县']
#         # data.sort_values(by=['市/区/县'])
#         # data.sort(['市/区/县'])
#         # print(data)
#         # data_days=data_days.set_index('市/区/县').join(data.set_index('市/区/县'))
#         data_days=pd.merge(data_days,data,on='市/区/县')
#
#         # data_days.join(data, lsuffix='_caller', rsuffix='_other')
#         print(data_days)
#         # time.sleep(60)
#         break
#     # data_days.to_excel(r'data_days.xlsx')



def day_chengdu(days_2018,data_days):
    for day_index in range(days_2018-3):
        tt = datetime.strptime('20180102', "%Y%m%d") + timedelta(days=day_index)
        tt = tt.strftime("%Y%m%d")
        base_url = r'http://weixin.cdepb.gov.cn:20005/data/w/%E5%9B%9B%E5%B7%9D%E7%9C%81%E5%90%84%E5%9F%8E%E5%B8%82%E7%A9%' 
                   r'BA%E6%B0%94%E8%B4%A8%E9%87%8F%E6%97%A5%E6%95%B0%E6%8D%AE?token=78C579FA28C9B1E6C156A806C392458C&date={}&rows=1000&page=1'.format(tt)
        # print(base_url)
        data=get_data_chengdu(base_url,tt)
        data.index=data['市/区/县']
        # data.sort_values(by=['市/区/县'])
        # data.sort(['市/区/县'])
        # print(data)
        # data_days=data_days.set_index('市/区/县').join(data.set_index('市/区/县'))
        data_days=pd.merge(data_days,data,on='市/区/县')

        # data_days.join(data, lsuffix='_caller', rsuffix='_other')
        # print(data_days)
        # time.sleep(60)
        # break
    print(data_days)
    data_days.to_excel(r'data_days.xlsx')

if __name__ == '__main__':

    # 获取并保存 每天 排名 区县   AQI    首要污染物
    # days_2018=time.localtime(time.time()).tm_yday
    # days_2017=365
    # days_2016=366
    # day_sum=days_2018+days_2017+days_2016
    # # print(day_sum)
    # tt = datetime.strptime('20180101', "%Y%m%d") + timedelta(days=0)
    # tt = tt.strftime("%Y%m%d")
    #
    # base_url = r'http://weixin.cdepb.gov.cn:20005/data/w/%E5%8C%BA%E5%8E%BF%E6%97%A5%E6%8E%92%E5%90%8D?' 
    #            r'token=78C579FA28C9B1E6C156A806C392458C&date={}&rows=1000&page=1'.format(tt)
    # data_days=get_data(base_url,tt)
    # day_chengdu_area(days_2018, data_days)

    # 获取成都总体的AQI
    days_2018 = time.localtime(time.time()).tm_yday
    tt = datetime.strptime('20180101', "%Y%m%d") + timedelta(days=0)
    tt = tt.strftime("%Y%m%d")
    chengdu_url=r'http://weixin.cdepb.gov.cn:20005/data/w/%E5%9B%9B%E5%B7%9D%E7%9C%81%E5%90%84%E5%9F%8E%E5%B8%82%E7%A9%BA' 
                r'%E6%B0%94%E8%B4%A8%E9%87%8F%E6%97%A5%E6%95%B0%E6%8D%AE?token=78C579FA28C9B1E6C156A806C392458C&date={}&rows=1000&page=1'.format(tt)
    data_chengdu=get_data_chengdu(chengdu_url,tt)
    # print(data_chengdu)
    day_chengdu(days_2018, data_chengdu)