数据爬取

直接上代码，这是对全国各个省份市的新冠肺炎各项数据的爬取。

  1 from os import path
  2 import requests
  3 from bs4 import BeautifulSoup
  4 import json
  5 import pymysql
  6 import numpy as np
  7 import time
  8 
  9 url = 'https://ncov.dxy.cn/ncovh5/view/pneumonia?from=timeline&isappinstalled=0'  # 请求地址
 10 headers = {
 11     'user-agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.131 Safari/537.36'}  # 创建头部信息
 12 response = requests.get(url, headers=headers)  # 发送网络请求
 13 # print(response.content.decode('utf-8'))#以字节流形式打印网页源码
 14 content = response.content.decode('utf-8')
 15 # print(content)
 16 soup = BeautifulSoup(content, 'html.parser')
 17 listA = soup.find_all(name='script', attrs={"id": "getAreaStat"})
 18 # 世界确诊
 19 listB = soup.find_all(name='script', attrs={"id": "getListByCountryTypeService2"})
 20 # listA = soup.find_all(name='div',attrs={"class":"c-touchable-feedback c-touchable-feedback-no-default"})
 21 account = str(listA)
 22 # world_messages = str(listB)[87:-21]
 23 messages = account[52:-21]
 24 messages_json = json.loads(messages)
 25 # world_messages_json = json.loads(world_messages)
 26 valuesList = []
 27 cityList = []
 28 
 29 con = len(messages_json)
 30 k = 0
 31 for i in range(len(messages_json)):
 32     # value = messages_json[i]
 33     k = k + 1
 34     value = (
 35     k, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())), messages_json[i].get('provinceShortName'), None,
 36     messages_json[i].get('confirmedCount'), messages_json[i].get('suspectedCount'), messages_json[i].get('curedCount'),
 37     messages_json[i].get('deadCount'), messages_json[i].get('locationId'))
 38     valuesList.append(value)
 39     cityValue = messages_json[i].get('cities')
 40     # print(cityValue)
 41     for j in range(len(cityValue)):
 42         con = con + 1
 43         cityValueList = (
 44         con, time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(time.time())), messages_json[i].get('provinceShortName'),
 45         cityValue[j].get('cityName'), cityValue[j].get('confirmedCount'), cityValue[j].get('suspectedCount'),
 46         cityValue[j].get('curedCount'), cityValue[j].get('deadCount'), cityValue[j].get('locationId'))
 47         # print(cityValueList)
 48         cityList.append(cityValueList)
 49     # cityList.append(cityValue)
 50 db = pymysql.connect("localhost", "root", "******", "yiqing", charset='utf8')
 51 cursor = db.cursor()
 52 array = np.asarray(valuesList[0])
 53 # sql_clean_world = "TRUNCATE TABLE world_map"
 54 # sql_clean_city = "TRUNCATE TABLE city_map"
 55 # sql_clean_json = "TRUNCATE TABLE province_data_from_json"
 56 sql_clean_province = "TRUNCATE TABLE info3"
 57 # sql1 = "INSERT INTO city_map values (%s,%s,%s,%s,%s,%s,%s,%s)"
 58 # sql_world = "INSERT INTO world_map values (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"
 59 # sql = "INSERT INTO province_map values (0,'%s','%s','%s','%s','%s','%s','%s','%s','%s','%s') "
 60 sql = "INSERT INTO info2 values (%s,%s,%s,%s,%s,%s,%s,%s,%s) "
 61 # sql = "INSERT INTO province_map (provinceName,provinceShortName,correntConfirmedCount,confirmedCount,
 62 # suspectedCount,curedCount,deadCount,comment,locationId,statisticsData) values (0,'%s','%s','%s','%s','%s','%s',
 63 # '%s','%s','%s','%s') " sql = """INSERT INTO province_map (provinceName,provinceShortName,correntConfirmedCount,
 64 # confirmedCount,suspectedCount,curedCount,deadCount,comment,locationId,statisticsData) values ('湖北省', '湖北', 43334,
 65 # 64786, 0, 18889, 2563, '', 420000, 'https://file1.dxycdn.com/2020/0223/618/3398299751673487511-135.json')"""
 66 value_tuple = tuple(valuesList)
 67 cityTuple = tuple(cityList)
 68 # worldTuple = tuple(worldList)
 69 # print(cityTuple)
 70 # print(tuple(value_tuple))
 71 try:
 72     # cursor.execute(sql_clean_city)
 73     cursor.execute(sql_clean_province)
 74     # cursor.executemany(sql, value_tuple)
 75     # cursor.executemany(sql1,cityTuple)
 76     db.commit()
 77 except:
 78     print('执行失败，进入回调1')
 79     db.rollback()
 80 
 81 try:
 82     # cursor.execute(sql_clean_city)
 83     # cursor.execute(sql_clean_province)
 84     cursor.executemany(sql, value_tuple)
 85     # cursor.executemany(sql1,cityTuple)
 86     db.commit()
 87 except:
 88     print('执行失败，进入回调3')
 89     db.rollback()
 90 
 91 try:
 92     # cursor.execute(sql_clean_city)
 93     # cursor.execute(sql_clean_province)
 94     # cursor.executemany(sql, value_tuple)
 95     cursor.executemany(sql, cityTuple)
 96     db.commit()
 97 except:
 98     print('执行失败，进入回调4')
 99     db.rollback()
100 
101 # print(messages_json)
102 # print(account[52:-21])
103 # soupDiv = BeautifulSoup(listA,'html.parser')
104 # listB = soupDiv.find_all(name='div',attrs={"class":"c-gap-bottom-zero c-line-clamp2"})
105 # for i in listA:
106 # print(i)
107 # listA[12]
108 # print(listA)
109 
110 
111 db.close()

其中上图便是和数据库的连接