(知乎也有我的文章)
在这里,先表明,此爬虫是否失效,视时间而定,解析网页内容方法较为原始,
本人并非爬虫大神,开始爬虫只是因为数学建模需要自己爬取数据(坑爹),整个队伍就我一个计算机专业,责任在我,只好硬着头皮去搞,没想到还挺有成就感。
好,话不多说,直接上代码
# -*- coding: utf-8 -*- """ Created on Thu Feb 8 18:09:44 2018 @author: 白马非马 """ #!/usr/bin/env python # -*- coding:utf-8 -*- #需要事先安装selenium和plantom.js,不适合大量爬虫,速度太慢,这里只爬取所有行业的第一页20个公司 #注意需要少量人工值守,当代理IP意外在4个行业以内超时崩掉时。需要手动关闭,可能不关闭代理IP会自动好转,但基本不可能 from selenium import webdriver import time import pymysql from bs4 import BeautifulSoup #网页代码解析器 from selenium.webdriver.common.desired_capabilities import DesiredCapabilities from selenium.webdriver.common.proxy import Proxy from selenium.webdriver.common.proxy import ProxyType import json import urllib.request ipurl = "http://piping.mogumiao.com/proxy/api/get_ip_al?appKey=6d22aed70f7d0479cbce55dff726a8d8a&count=1&expiryDate=5&format=1" #代理IP获取API connect = pymysql.Connect( host='localhost', port=3306, user='root', passwd='1234', db='user', charset='utf8' ) #mysql数据库驱动信息 #获取代理IP def getip_port(): req = urllib.request.Request(ipurl) data = urllib.request.urlopen(req).read() #loads:把json转换为dict s1 = json.loads(data) #print (s1["msg"][0]["ip"] ) #print (s1["msg"][0]["port"] ) ipstrs=s1["msg"][0]["ip"]+":"+s1["msg"][0]["port"] print("代理IP:"+ipstrs) return ipstrs #创建浏览器驱动 def driver_open(): #dcap = dict(DesiredCapabilities.PHANTOMJS) # dcap["phantomjs.page.settings.userAgent"] = ( #"Mozilla/5.0 (Windows NT 6.1; WOW64; rv:50.0) Gecko/20100101 Firefox/50.0" #) #driver = webdriver.PhantomJS(executable_path='phantomjs.exe', desired_capabilities=dcap) proxy = Proxy( { 'proxyType': ProxyType.MANUAL, 'httpProxy': getip_port() # 代理ip和端口 } ) desired_capabilities = DesiredCapabilities.PHANTOMJS.copy() desired_capabilities = dict(DesiredCapabilities.PHANTOMJS) desired_capabilities["phantomjs.page.settings.userAgent"] = ( "Mozilla/5.0 (Windows NT 6.1; WOW64; rv:50.0) Gecko/20100101 Firefox/50.0" ) # 把代理ip加入到技能中 proxy.add_to_capabilities(desired_capabilities) driver = webdriver.PhantomJS( executable_path='phantomjs.exe', desired_capabilities=desired_capabilities ) return driver #获取网页内容 def get_content(driver,url): driver.get(url) #等待5秒,更据动态网页加载耗时自定义 #sleeptime=random.randint(2,3) time.sleep(1) content = driver.page_source.encode('utf-8') #driver.close() soup = BeautifulSoup(content, 'lxml') #print(soup) return soup #解析网页内容,爬虫筛选不完善,不匹配所有网页, #天眼查4分之三的网页可正常解析,时间为2018-2-27 #有爬虫大神可对此进行改进,期待谢谢 def get_basic_info(soup,instr): #com=soup.find_all("span") #print(com[6]) company = soup.find(attrs={'class':'f18 in-block vertival-middle sec-c2'}).text fddbr = soup.find(attrs={'class':'f18 overflow-width sec-c3'}).text #fddbr=soup.find_all("a") baseinfo = soup.find_all(attrs={'class':'baseinfo-module-content-value'}) zczb =baseinfo[0].text zt = baseinfo[2].text zcrq =baseinfo[1].text foundAllTd = soup.find_all("td"); #print len(basics) #jyfw = soup.find(attrs={'class':'js-full-container hidden'}).text print (u'公司名称:'+company) print( u'法定代表人:'+fddbr) print (u'注册资本:'+zczb) print (u'公司状态:'+zt) print (u'注册日期:'+zcrq) #根据网页td标签粗略识别网页类型, #有两种,一种大公司,报表内容较为多,td标签数大致为800到1000 #小公司基本在500以下 #少量公司td标签数在中间,无法很好识别,数量不多,影响不大,时间:2018-2-26 if len(foundAllTd) > 600: """ print (u'员工人数:'+foundAllTd[50].text) print (u'行业:'+foundAllTd[527].text) print (u'企业类型:'+foundAllTd[523].text) #print (u'工商注册号:'+foundAllTd[517].text) print( u'组织机构代码:'+foundAllTd[519].text) print (u'营业期限:'+foundAllTd[529].text) print( u'登记机构:'+foundAllTd[533].text) print (u'核准日期:'+foundAllTd[531].text) print( u'统一社会信用代码:'+foundAllTd[521].text) print (u'注册地址:'+foundAllTd[537].text) print (u'经营范围:'+foundAllTd[539].text) """ sql = "INSERT INTO company (instr,company_name,industry,business_scope,type_enterprise,regist_capital,legal_represent,regist_date,company_status,operat_period,registrat_body,approval_date,address,people_num) VALUES ( '%s','%s','%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s' )" data = (instr,company, foundAllTd[527].text, foundAllTd[539].text,foundAllTd[523].text ,zczb , fddbr,zcrq ,zt,foundAllTd[529].text ,foundAllTd[533].text ,foundAllTd[531].text ,foundAllTd[537].text,foundAllTd[49].text) else: """ print (u'行业:'+foundAllTd[18].text) #print (u'工商注册号:'+foundAllTd[8].text) print (u'企业类型:'+foundAllTd[14].text) print( u'组织机构代码:'+foundAllTd[10].text) print (u'营业期限:'+foundAllTd[20].text) print( u'登记机构:'+foundAllTd[24].text) print (u'核准日期:'+foundAllTd[22].text) print( u'统一社会信用代码:'+foundAllTd[16].text) print (u'注册地址:'+foundAllTd[28].text) print (u'经营范围:'+foundAllTd[30].text) """ sql = "INSERT INTO company (instr,company_name,industry,business_scope,type_enterprise,regist_capital,legal_represent,regist_date,company_status,operat_period,registrat_body,approval_date,address) VALUES ( '%s','%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s', '%s' )" data = (instr,company, foundAllTd[18].text, foundAllTd[30].text,foundAllTd[14].text ,zczb , fddbr,zcrq ,zt,foundAllTd[20].text ,foundAllTd[24].text ,foundAllTd[22].text ,foundAllTd[28].text) # 插入数据 cursor.execute(sql % data) connect.commit() #print('成功插入', cursor.rowcount, '条数据') #获取高管信息,已失效,对代码运行没有影响 def get_gg_info(soup): ggpersons = soup.find_all(attrs={"event-name": "company-detail-staff"}) ggnames = soup.select('table.staff-table > tbody > tr > td.ng-scope > span.ng-binding') # print(len(gg)) for i in range(len(ggpersons)): ggperson = ggpersons[i].text ggname = ggnames[i].text print (ggperson+" "+ggname) #获取信息,已失效,对代码运行没有影响 def get_gd_info(soup): tzfs = soup.find_all(attrs={"event-name": "company-detail-investment"}) for i in range(len(tzfs)): tzf_split = tzfs[i].text.replace("\n","").split() tzf = ' '.join(tzf_split) print (tzf) #获取信息,已失效,对代码运行没有影响 def get_tz_info(soup): btzs = soup.select('a.query_name') for i in range(len(btzs)): btz_name = btzs[i].select('span')[0].text print (btz_name) #在首页获取行业链接 def get_industry(soup): # print(soup.find(attrs={'class':'industry_container js-industry-container'})) #hangye = soup.find(attrs={'class':'industry_container js-industry-container'}).find_all("a") x=[] buyao=70 #开始爬数据时删掉 hangye = soup.find_all('a') for item in hangye: if 'https://www.tianyancha.com/search/oc' in str(item.get("href")): print (item.get("href")) if buyao>0: buyao-=1 else: x.append(str(item.get("href"))) print("行业数") print(len(x)) return x; #获取行业下公司链接 def get_industry_company(soup): y=[] companylist = soup.find_all('a') for item in companylist: if 'https://www.tianyancha.com/company/' in str(item.get("href")): print (item.get("href")) y.append(str(item.get("href"))) return y if __name__=='__main__': cursor = connect.cursor() #连接数据库 companycount=0 #爬取的公司数 instrcount=0 #爬取的行业数,每4个行业换一个代理IP,每个行业爬取第一页20个 theinscount=0 #需要爬取的行业标签数,每4个行业换一个代理IP,每个行业爬取第一页20个 driver = driver_open() url = "https://www.tianyancha.com/" soup = get_content(driver, url) instrlist=get_industry(soup) theinscount=len(instrlist) print for instr in instrlist: #遍历行业链接 instrcount+=1 print(instrcount) print(instr) compsoup = get_content(driver, instr) complist =get_industry_company(compsoup) for comp in complist: #遍历行业下公司链接 print(comp) companycount+=1 #print(num) print("行业数爬了"+str(instrcount)) try: infosoup = get_content(driver, comp) print ('----获取基础信息----') get_basic_info(infosoup,instr) except: print('异常跳过', end=' ') if instrcount%4 == 0 : #每3个行业链接换一个代理IP,防止网页封禁代理IP, #有时会出问题,代理IP超时之类,遇到此类情况关掉程序,或者关掉plantomjs print("换IP") #driver.close()#关闭驱动 ,可能会有多个plantomjs窗口,需要常关 driver = driver_open() #try: # get_basic_info(soup,instr) #except: # print('异常跳过', end=' ') # print() cursor.close() connect.close() #关闭数据库链接
代码注释已经打的比较详细,可以直接看。
上面的代码爬取结果还需要数据预处理,尤其是天眼查煞笔的数据加密,
上面加密的数据有,注册资本,注册时间,营业期限,加密方法贼原始,
我遇到的加密是,
数字加密方式 密文 明文 7 4 5 8 4 . 3 9 0 1 . 5 9 2 6 0 1 3 8 6 2 7
就这么简单,哈哈哈,发现这个时没笑死我。这个解码的操作较为简单,小伙伴自己去操练去吧。
有人说,为啥不去爬国家企业信用信息公示系统,原因只有一个,我实在懒得去搞什么滑动验证码,文字点击验证码,看着就烦,(注定无法成为爬虫工程师)需要的伙伴可以看这位老兄的博客,他的说已经失效了,可以借鉴点经验,【爬虫】关于企业信用信息公示系统-加速乐最新反爬虫机制
还好天眼查没有验证码,不然建模小伙伴要被我这个辣鸡气死。
另外,如果有小伙伴实在不想自己爬数据的,只想要数据的,可以私信找我要,没错我还真的想过去买点数据应付一下建模,不过看到价格,基本就放弃了,看图
代理IP是找的蘑菇代理,就花了6块钱,1000个高匿IP,上面的API好像还剩700个,给你们用吧,,反正我是不想搞爬虫了,有大神搞了个爬取代理IP的点击打开链接。
,感觉一句话,做技术只是累,学技术不仅累还难。
坑,爬虫坑,填了土。