Python爬取全国各地区疫情风险等级

2022年11月27日 149点热度 0人点赞 0条评论

Python爬取全国各地区疫情风险等级

 

需求
通过爬虫取得国家官网各地区疫情风险等级,存入电子表格最终如下:

 

数据来源
http://bmfw.www.gov.cn/yqfxdjcx/risk.html

分析网页

页面结构
上部:有截至时间,有三个按键:高\中\低.点击可以切换中部的信息
中部:风险地区信息
下部:翻页

确定请求方式
因为有翻页按钮,猜想应该是用ajax更新数据
打开F12,点<网络>,清除一下之前的内容,刷新一下

 

分析请求信息

url=http://bmfw.www.gov.cn/bjww/interface/interfaceJson

#请求方式为:POST

#请求头
headers={
Accept: application/json, text/plain, */*
Accept-Encoding: gzip, deflate
Accept-Language: zh-CN,zh;q=0.9
Connection: keep-alive
Content-Length: 235
Content-Type: application/json;charset=UTF-8
Cookie: wdcid=57661336733ee69d; _gscu_1088464070=62382713kmnu2p11; __auc=5e75e3b61830dbb29f71ed50e8e; wdses=7e7e0e45f5b9f4e6; _gscbrs_1088464070=1; __asc=578b530b18312ed51c75133a6b5; acw_tc=2760823f16624698875982607ee72639a46b54881093f71cc7ab12b65f0a17; wdlast=1662469913; _gscs_1088464070=62469886ezpysq11|pv:2; SERVERID=edf8bc70025336506334b22603ae1cc6|1662469904|1662469877
Host: bmfw.www.gov.cn
Origin: http://bmfw.www.gov.cn
Referer: http://bmfw.www.gov.cn/yqfxdjcx/risk.html
User-Agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/103.0.0.0 Safari/537.36
x-wif-nonce: QkjjtiLM2dCratiA
x-wif-paasid: smt-application
x-wif-signature: B80277094A20F7C04C735C8413BE2B014332114512BFB51BADD30E21D5C368D9
x-wif-timestamp: 1662469914
}

#POST请求的数据
from_data={
"key":"3C502C97ABDA40D0A60FBEE50FAAD1DA",
"appId":"NcApplication",
"paasHeader":"zdww",
"timestampHeader":"1662469914",
"nonceHeader":"123456789abcdefg",
"signatureHeader":"B0BF67E09448D9A8A6C0538B259E715FD51CB51FCD6822E85000C2196354EB0B"
}
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大多数都是常规项目请求.重点分析:
x-wif-nonce
x-wif-paasid
x-wif-signature
x-wif-timestampy

timestampHeader
signatureHeader

确认请求头参数
先在<源代码 >右边的<XHR/提取断点>里输入接口的后半段地址:
/bjww/interface/interfaceJson,并刷新页面,他会断下来,然后看<作用或>,如果<作用域>里显示有"/bjww/interface/interfaceJson",就可以在里面查看headers等数据

 

上图可见headers只验证
Accept
Content-Type
x-wif-nonce
x-wif-paasid
x-wif-signature
x-wif-timestamp
使用的是POST请求,请求数据是字符串,字符串中是字典.

分析JS
5.1 搜索x-wif-nonce等关键字
在<网络>下按Ctrl+F调出搜索窗口,搜x-wif-nonce

找到2个JS,3个地方
先点第1.2个JS:

这里已经注释丢了,肯定不是.
看第3个JS:
显然就是我们要找的:
javascript function p(t) { if (!t.commonHeaders) return t; var e = o.value , n = CryptoJS.SHA256(e + "fTN2pfuisxTavbTuYVSsNJHetwq5bJvCQkjjtiLM2dCratiA" + e).toString(CryptoJS.enc.Hex).toUpperCase(); return Object.assign(t.headers, { "x-wif-nonce": "QkjjtiLM2dCratiA", "x-wif-paasid": "smt-application", "x-wif-signature": n, "x-wif-timestamp": e }), t }
x-wif-nonce和x-wif-paasid是固定值,分别是:“QkjjtiLM2dCratiA"和"smt-application”
x-wif-signature和x-wif-timestamp是一个对象n,e,可以在这里下一个断点,查看他们:

e是一个时间戳
n是SHA(e+"fTN2pfuisxTavbTuYVSsNJHetwq5bJvCQkjjtiLM2dCratiA" + e)
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这里再进一步验证SHA256是否是标准算法,上图紫框是网页算出来的字串:

可见这里使用的是标准SHA256算法.
5.2搜索timestampHeader
在<网络>里搜索timestampHeader

timestampHeader为时间戳
signatureHeader是SHA(timestampHeader+'23y0ufFl5YxIyGrI8hWRUZmKkvtSjLQA'+'123456789abcdefg'+timestampHeader)
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编写代码
1.爬虫代码

import hashlib
import os
import requests
import time
import sys
import json
import csv

#显示某等级地区的小计
def show_level_count(x_list):
j=0
for i in range(len(x_list)):
j+=len (x_list[i]["communitys"])
print(j)
return j

def writer_to_csv(risk_txt):
risk_json = json.loads(risk_txt)

so_far_time = risk_json["data"]["end_update_time"]

highlist = risk_json["data"]["highlist"]
middlelist = risk_json["data"]["middlelist"]
lowlist = risk_json["data"]["lowlist"]

encoding='utf_8_sig'
f = open('risk_data_' + so_far_time + '.csv','w', encoding=encoding,newline='')
csv_writer = csv.writer(f)

level_dict={}
level_dict["高风险"]=highlist
level_dict["中风险"]=middlelist
level_dict["低风险"]=lowlist

for level in level_dict.keys():
risk_level = level
for i in range(len(level_dict[level])):
province = level_dict[level][i]["province"]
city = level_dict[level][i]["city"]
county = level_dict[level][i]["county"]
for j in range(len(level_dict[level][i]["communitys"])):
csv_writer.writerow(
[risk_level, province, city, county, level_dict[level][i]["communitys"][j]])
# write_to_csv_file(csv_writer, highlist, "高风险")
# write_to_csv_file(csv_writer, middlelist, "中风险")
# write_to_csv_file(csv_writer, lowlist, "低风险")
f.close()

print("写入risk_data.csv完成.")

def get_risk_area_data():
timestamp = str(int(time.time()))
# timestamp = '1662646358'

x_wif_timestamp = timestamp
timestampHeader = timestamp

x_wif_nonce = 'QkjjtiLM2dCratiA'
x_wif_paasid = 'smt-application'

x_wif_signature_str = timestamp + \
'fTN2pfuisxTavbTuYVSsNJHetwq5bJvCQkjjtiLM2dCratiA'+timestamp
x_wif_signature = hashlib.sha256(
x_wif_signature_str.encode('utf-8')).hexdigest().upper()

signatureHeader_str = timestamp + \
'23y0ufFl5YxIyGrI8hWRUZmKkvtSjLQA'+'123456789abcdefg'+timestamp
signatureHeader = hashlib.sha256(
signatureHeader_str.encode('utf-8')).hexdigest().upper()

url = 'http://bmfw.www.gov.cn/bjww/interface/interfaceJson'

headerss = {
'Accept': "application/json, text/plain, */*",
'Content-Type': "application/json;charset=utf-8",
'x-wif-nonce': "QkjjtiLM2dCratiA",
'x-wif-paasid': "smt-application",
'x-wif-signature': x_wif_signature,
'x-wif-timestamp': x_wif_timestamp,
}

From_data = "{\"key\":\"3C502C97ABDA40D0A60FBEE50FAAD1DA\",\
\"appId\":\"NcApplication\",\"paasHeader\":\"zdww\",\
\"timestampHeader\":\"" + timestampHeader + "\",\
\"nonceHeader\":\"123456789abcdefg\",\"signatureHeader\":\"" + signatureHeader + "\"}"
# print(From_data)

response = requests.post(url=url, data=From_data, headers=headerss)
if not response.status_code == 200:
# print(response.status_code)
return "", response.status_code

# print(response.text)
return response.text.replace('\u2022', ''), response.status_code

if __name__ == '__main__':
risk_data=get_risk_area_data()
if risk_data[1]==200:
with open('./risk_data.json', 'w',encoding='utf-8') as f:
f.write(risk_data[0])
print("写入risk_data.log完成.")

f = open('risk_data.json', 'r', encoding='utf-8')
risk_txt = f.read()
f.close()

writer_to_csv(risk_txt)

print('全部程序完成,请勿频繁使用!')
os.system('pause')
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版权声明:本文为CSDN博主「LILI00000」的原创文章,遵循CC 4.0 BY-SA版权协议,转载请附上原文出处链接及本声明。
原文链接:https://blog.csdn.net/LILI00000/article/details/126710407

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