Python クローラーは、処刑対象となる不正行為者の全国リストをクエリする例を実装します。

# -*- coding:utf-8*-
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import time
import requests
time1=time.time()
import pandas as pd
import json
iname=[]
icard=[]
def person_executed(name):
  for i in range(0,30):
    try:
      url="https://sp0.baidu.com/8aQDcjqpAAV3otqbppnN2DJv/api.php?resource_id=6899" \
      "&query=%E5%A4%B1%E4%BF%A1%E8%A2%AB%E6%89%A7%E8%A1%8C%E4%BA%BA%E5%90%8D%E5%8D%95" \
      "&cardNum=&" \
      "iname="+str(name)+ \
      "&areaName=" \
      "&pn="+str(i*10)+ \
      "&rn=10" \
      "&ie=utf-8&oe=utf-8&format=json"
      html=requests.get(url).content
      html_json=json.loads(html)
      html_data=html_json['data']
      for each in html_data:
        k=each['result']
        for each in k:
          print each['iname'],each['cardNum']
          iname.append(each['iname'])
          icard.append(each['cardNum'])
    except:
      pass
if __name__ == '__main__':
  name="郭**"
  person_executed(name)
  print len(iname)
  #####################将数据组织成数据框###########################
  data=pd.DataFrame({"name":iname,"IDCard":icard})
  #################数据框去重####################################
  data1=data.drop_duplicates()
  print data1
  print len(data1)
  #########################写出数据到excel#########################################
  pd.DataFrame.to_excel(data1,"F:\\iname_icard_query.xlsx",header=True,encoding='gbk',index=False)
  time2=time.time()
  print u'ok,爬虫结束!'
  print u'总共耗时：'+str(time2-time1)+'s'

# -*- coding:utf-8*-
import sys
reload(sys)
sys.setdefaultencoding('utf-8')
import time
import requests
time1=time.time()
import pandas as pd
import json
iname=[]
icard=[]
courtName=[]
areaName=[]
caseCode=[]
duty=[]
performance=[]
disruptTypeName=[]
publishDate=[]
def person_executed(name):
  for i in range(0,30):
    try:
      url="https://sp0.baidu.com/8aQDcjqpAAV3otqbppnN2DJv/api.php?resource_id=6899" \
      "&query=%E5%A4%B1%E4%BF%A1%E8%A2%AB%E6%89%A7%E8%A1%8C%E4%BA%BA%E5%90%8D%E5%8D%95" \
      "&cardNum=&" \
      "iname="+str(name)+ \
      "&areaName=" \
      "&pn="+str(i*10)+ \
      "&rn=10" \
      "&ie=utf-8&oe=utf-8&format=json"
      html=requests.get(url).content
      html_json=json.loads(html)
      html_data=html_json['data']
      for each in html_data:
        k=each['result']
        for each in k:
          print each['iname'],each['cardNum'],each['courtName'],each['areaName'],each['caseCode'],each['duty'],each['performance'],each['disruptTypeName'],each['publishDate']
          iname.append(each['iname'])
          icard.append(each['cardNum'])
          courtName.append(each['courtName'])
          areaName.append(each['areaName'])
          caseCode.append(each['caseCode'])
          duty.append(each['duty'])
          performance.append(each['performance'])
          disruptTypeName.append(each['disruptTypeName'])
          publishDate.append(each['publishDate'])
    except:
      pass
if __name__ == '__main__':
  name="郭**"
  person_executed(name)
  print len(iname)
  #####################将数据组织成数据框###########################
  # data=pd.DataFrame({"name":iname,"IDCard":icard})
  detail_data=pd.DataFrame({"name":iname,"IDCard":icard,"courtName":courtName,"areaName":areaName,"caseCode":caseCode,"duty":duty,"performance":performance,\
               "disruptTypeName":disruptTypeName,"publishDate":publishDate})
  #################数据框去重####################################
  # data1=data.drop_duplicates()
  # print data1
  # print len(data1)
  detail_data1=detail_data.drop_duplicates()
  # print detail_data1
  # print len(detail_data1)
  #########################写出数据到excel#########################################
  pd.DataFrame.to_excel(detail_data1,"F:\\iname_icard_query.xlsx",header=True,encoding='gbk',index=False)
  time2=time.time()
  print u'ok,爬虫结束!'
  print u'总共耗时：'+str(time2-time1)+'s'