Python爬虫怎么实现全国失信被执行人名单查询功能

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一、需求说明

利用百度的接口，实现一个全国失信被执行人名单查询功能。输入姓名，查询是否在全国失信被执行人名单中。

二、python实现

版本1：

# -*- coding:utf-8*-import sysreload(sys)sys.setdefaultencoding('utf-8')import timeimport requeststime1=time.time()import pandas as pdimport jsoniname=[]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:      passif __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'

三、效果展示

"D:\Program Files\Python27\python.exe" D:/PycharmProjects/learn2017/全国失信被执行人查询.py
郭** 34122319790****5119
郭** 32032119881****2419
郭** 32032119881****2419
3
IDCard name
0 34122319790****5119 郭**
1 32032119881****2419 郭**
2
ok,爬虫结束!
总共耗时：7.72000002861s
Process finished with exit code 0

版本2：

# -*- coding:utf-8*-import sysreload(sys)sys.setdefaultencoding('utf-8')import timeimport requeststime1=time.time()import pandas as pdimport jsoniname=[]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:      passif __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'

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