思路: 在腾讯疫情数据网站F12解析网站结构,使用python爬取当日疫情数据和历史疫情数据,分别存储到details和history两个Mysql表。 ①此方法用于爬取每日详细
在腾讯疫情数据网站F12解析网站结构,使用python爬取当日疫情数据和历史疫情数据,分别存储到details和history两个Mysql表。
①此方法用于爬取每日详细疫情数据
import requests
import JSON
import time
def get_details():
url = 'https://view.inews.qq.com/g2/getOnsInfo?name=disease_h5&callback=Jquery34102848205531413024_1584924641755&_=1584924641756'
headers ={
'user-agent': 'Mozilla/5.0 (windows NT 10.0; WOW64) AppleWEBKit/537.36 (Khtml, like Gecko) Chrome/70.0.3538.25 Safari/537.36 Core/1.70.3741.400 QQBrowser/10.5.3863.400'
}
res = requests.get(url,headers=headers)
#输出全部信息
# print(res.text)
response_data = json.loads(res.text.replace('jQuery34102848205531413024_1584924641755(','')[:-1])
#输出这个字典的键值 dict_keys(['ret', 'data'])ret是响应值,0代表请求成功,data里是我们需要的数据
# print(response_data.keys())
"""上面已经转化过一次字典,然后获取里面的data,因为data是字符串,所以需要再次转化字典
print(json.loads(reponse_data['data']).keys())
结果:
dict_keys(['lastUpdateTime', 'chinaTotal', 'chinaAdd', 'isshowAdd', 'showAddSwitch',
'areaTree', 'chinaDayList', 'chinaDayAddList', 'dailyNewAddHistory', 'dailyHistory',
'wuhanDayList', 'articleList'])
lastUpdateTime是最新更新时间,chinaTotal是全国疫情总数,chinaAdd是全国新增数据,
isShowAdd代表是否展示新增数据,showAddSwitch是显示哪些数据,areaTree中有全国疫情数据
"""
areaTree_data = json.loads(response_data['data'])['areaTree']
temp=json.loads(response_data['data'])
# print(temp.keys())
# print(areaTree_data[0].keys())
"""
获取上一级字典里的areaTree
然后查看里面中国键值
print(areaTree_data[0].keys())
dict_keys(['name', 'today', 'total', 'children'])
name代表国家名称,today代表今日数据,total代表总数,children里有全国各地数据,我们需要获取全国各地数据,查看children数据
print(areaTree_data[0]['children'])
这里面是
name是地区名称,today是今日数据,total是总数,children是市级数据,
我们通过这个接口可以获取每个地区的总数据。我们遍历这个列表,取出name,这个是省级的数据,还需要获取市级数据,
需要取出name,children(市级数据)下的name、total(历史总数)下的confirm、heal、dead,today(今日数据)下的confirm(增加数),
这些就是我们需要的数据
"""
# print(areaTree_data[0]['children'])
# for province_data in areaTree_data[0]['children']:
# print(province_data)
ds= temp['lastUpdateTime']
details=[]
for pro_infos in areaTree_data[0]['children']:
province_name = pro_infos['name'] # 省名
for city_infos in pro_infos['children']:
city_name = city_infos['name'] # 市名
confirm = city_infos['total']['confirm']#历史总数
confirm_add = city_infos['today']['confirm']#今日增加数
heal = city_infos['total']['heal']#治愈
dead = city_infos['total']['dead']#死亡
# print(ds,province_name,city_name,confirm,confirm_add,heal,dead)
details.append([ds,province_name,city_name,confirm,confirm_add,heal,dead])
return details
单独测试方法:
# d=get_details()
# print(d)
②此方法用于爬取历史详细数据
import requests
import json
import time
def get_history():
url = 'Https://view.inews.qq.com/g2/getOnsInfo?name=disease_other&callback=jQuery341026745307075030955_1584946267054&_=1584946267055'
headers ={
'user-agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.25 Safari/537.36 Core/1.70.3741.400 QQBrowser/10.5.3863.400'
}
res = requests.get(url,headers=headers)
# print(res.text)
response_data = json.loads(res.text.replace('jQuery341026745307075030955_1584946267054(','')[:-1])
# print(response_data)
data = json.loads(response_data['data'])
# print(data.keys())
chinaDayList = data['chinaDayList']#历史记录
chinaDayAddList = data['chinaDayAddList']#历史新增记录
history = {}
for i in chinaDayList:
ds = '2021.' + i['date']#时间
tup = time.strptime(ds,'%Y.%m.%d')
ds = time.strftime('%Y-%m-%d',tup)#改变时间格式,插入数据库
confirm = i['confirm']
suspect = i['suspect']
heal = i['heal']
dead = i['dead']
history[ds] = {'confirm':confirm,'suspect':suspect,'heal':heal,'dead':dead}
for i in chinaDayAddList:
ds = '2021.' + i['date']#时间
tup = time.strptime(ds,'%Y.%m.%d')
ds = time.strftime('%Y-%m-%d',tup)#改变时间格式,插入数据库
confirm_add = i['confirm']
suspect_add = i['suspect']
heal_add = i['heal']
dead_add = i['dead']
history[ds].update({'confirm_add':confirm_add,'suspect_add':suspect_add,'heal_add':heal_add,'dead_add':dead_add})
return history
单独测试此方法:
# h=get_history()
# print(h)
③此方法用于数据库的连接与关闭:
import time
import pymysql
import traceback
def get_conn():
"""
:return: 连接,游标
"""
# 创建连接
conn = pymysql.connect(host="127.0.0.1",
user="root",
passWord="000429",
db="mydb",
charset="utf8")
# 创建游标
cursor = conn.cursor() # 执行完毕返回的结果集默认以元组显示
return conn, cursor
def close_conn(conn, cursor):
if cursor:
cursor.close()
if conn:
conn.close()
④此方法用于更新并插入每日详细数据到数据库表:
def update_details():
"""
更新 details 表
:return:
"""
cursor = None
conn = None
try:
li = get_details()
conn, cursor = get_conn()
sql = "insert into details(update_time,province,city,confirm,confirm_add,heal,dead) values(%s,%s,%s,%s,%s,%s,%s)"
sql_query = 'select %s=(select update_time from details order by id desc limit 1)' #对比当前最大时间戳
cursor.execute(sql_query,li[0][0])
if not cursor.fetchone()[0]:
print(f"{time.asctime()}开始更新最新数据")
for item in li:
cursor.execute(sql, item)
conn.commit() # 提交事务 update delete insert操作
print(f"{time.asctime()}更新最新数据完毕")
else:
print(f"{time.asctime()}已是最新数据!")
except:
traceback.print_exc()
finally:
close_conn(conn, cursor)
单独测试能否插入数据到details表:
update_details()
⑤此方法用于插入历史数据到history表
def insert_history():
"""
插入历史数据
:return:
"""
cursor = None
conn = None
try:
dic = get_history()
print(f"{time.asctime()}开始插入历史数据")
conn, cursor = get_conn()
sql = "insert into history values(%s,%s,%s,%s,%s,%s,%s,%s,%s)"
for k, v in dic.items():
# item 格式 {'2021-01-13': {'confirm': 41, 'suspect': 0, 'heal': 0, 'dead': 1}
cursor.execute(sql, [k, v.get("confirm"), v.get("confirm_add"), v.get("suspect"),
v.get("suspect_add"), v.get("heal"), v.get("heal_add"),
v.get("dead"), v.get("dead_add")])
conn.commit() # 提交事务 update delete insert操作
print(f"{time.asctime()}插入历史数据完毕")
except:
traceback.print_exc()
finally:
close_conn(conn, cursor)
单独测试能否插入数据到history表:
# insert_history()
⑥此方法用于根据时间来更新历史数据表的内容:
def update_history():
"""
更新历史数据
:return:
"""
cursor = None
conn = None
try:
dic = get_history()
print(f"{time.asctime()}开始更新历史数据")
conn, cursor = get_conn()
sql = "insert into history values(%s,%s,%s,%s,%s,%s,%s,%s,%s)"
sql_query = "select confirm from history where ds=%s"
for k, v in dic.items():
# item 格式 {'2020-01-13': {'confirm': 41, 'suspect': 0, 'heal': 0, 'dead': 1}
if not cursor.execute(sql_query, k):
cursor.execute(sql, [k, v.get("confirm"), v.get("confirm_add"), v.get("suspect"),
v.get("suspect_add"), v.get("heal"), v.get("heal_add"),
v.get("dead"), v.get("dead_add")])
conn.commit() # 提交事务 update delete insert操作
print(f"{time.asctime()}历史数据更新完毕")
except:
traceback.print_exc()
finally:
close_conn(conn, cursor)
单独测试更新历史数据表的方法:
# update_history()
最后是两个数据表的详细建立代码(也可以使用mysql可视化工具直接建立):
create table history(
ds datetime not null comment '日期',
confirm int(11) default null comment '累计确诊',
confirm_add int(11) default null comment '当日新增确诊',
suspect int(11) default null comment '剩余疑似',
suspect_add int(11) default null comment '当日新增疑似',
heal int(11) default null comment '累计治愈',
heal_add int(11) default null comment '当日新增治愈',
dead int(11) default null comment '累计死亡',
dead_add int(11) default null comment '当日新增死亡',
primary key(ds) using btree
)engine=InnoDB DEFAULT charset=utf8mb4;
create table details(
id int(11) not null auto_increment,
update_time datetime default null comment '数据最后更新时间',
province varchar(50) default null comment '省',
city varchar(50) default null comment '市',
confirm int(11) default null comment '累计确诊',
confirm_add int(11) default null comment '新增确诊',
heal int(11) default null comment '累计治愈',
dead int(11) default null comment '累计死亡',
primary key(id)
)engine=InnoDB default charset=utf8mb4;
Tomorrowthe birds will singing.
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本文标题: Python爬取腾讯疫情实时数据并存储到mysql数据库的示例代码
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