Python crawler implements an example of querying the national list of dishonest persons subject to execution-Python Tutorial-php.cn

这篇文章主要介绍了Python爬虫实现全国失信被执行人名单查询功能,涉及Python爬虫相关网络接口调用及json数据转换等相关操作技巧,需要的朋友可以参考下

本文实例讲述了Python爬虫实现全国失信被执行人名单查询功能。分享给大家供大家参考，具体如下：

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 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'

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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 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'

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