


Writing a crawler is a complex, noisy, and repetitive task. Issues to consider include collection efficiency, link exception handling, data quality (which has a lot to do with site coding specifications), etc. Organize and write a crawler program yourself. A single server can enable 1 to 8 instances to collect at the same time, and then store the data in the database.
#-*- coding:utf-8 -*- #!/usr/local/bin/python import sys, time, os,string import mechanize import urlparse from BeautifulSoup import BeautifulSoup import re import MySQLdb import logging import cgi from optparse import OptionParser #----------------------------------------------------------------------------# # Name: TySpider.py # # Purpose: WebSite Spider Module # # Author: 刘天斯 # # Email: liutiansi@gamil.com # # Created: 2010/02/16 # # Copyright: (c) 2010 # #----------------------------------------------------------------------------# """ |-------------------------------------------------------------------------- | 定义 loging class; |-------------------------------------------------------------------------- | | 功能:记录系统相关日志信息。 | | """ class Pubclilog(): def __init__(self): self.logfile = 'website_log.txt' def iniLog(self): logger = logging.getLogger() filehandler = logging.FileHandler(self.logfile) streamhandler = logging.StreamHandler() fmt = logging.Formatter('%(asctime)s, %(funcName)s, %(message)s') logger.setLevel(logging.DEBUG) logger.addHandler(filehandler) logger.addHandler(streamhandler) return [logger,filehandler] """ |-------------------------------------------------------------------------- | 定义 tySpider class; |-------------------------------------------------------------------------- | | 功能:抓取分类、标题等信息 | | """ class BaseTySpider: #初始化相关成员方法 def __init__(self,X,log_switch): #数据库连接 self.conn = MySQLdb.connect(db='dbname',host='192.168.0.10', user='dbuser',passwd='SDFlkj934y5jsdgfjh435',charset='utf8') #分类及标题页面Community self.CLASS_URL = 'http://test.abc.com/aa/CommTopicsPage?' #发表回复页 self.Content_URL = 'http://test.bac.com/aa/CommMsgsPage?' #开始comm值 self.X=X #当前comm id取模,方面平均到表 self.mod=self.X%5 #Community文件下载页 self.body="" #self.bodySoup对象 self.soup=None #发表回复页下载内容变量 self.Contentbody="" #发表回复页内容self.ContentbodySoup对象 self.Contentsoup=None #日志开关 self.log_switch=log_switch #======================获取名称及分类方法========================== def _SpiderClass(self,nextpage=None): if nextpage==None: FIXED_QUERY = 'cmm='+str(self.X) else: FIXED_QUERY = nextpage[1:] try: rd = mechanize.Browser() rd.addheaders = [("User-agent", "Tianya/2010 (compatible; MSIE 6.0;Windows NT 5.1)")] rd.open(self.CLASS_URL + FIXED_QUERY) self.body=rd.response().read() #rd=mechanize.Request(self.CLASS_URL + FIXED_QUERY) #response = mechanize.urlopen(rd) #self.body=response.read() except Exception,e: if self.log_switch=="on": logapp=Pubclilog() logger,hdlr = logapp.iniLog() logger.info(self.CLASS_URL + FIXED_QUERY+str(e)) hdlr.flush() logger.removeHandler(hdlr) return self.soup = BeautifulSoup(self.body) NextPageObj= self.soup("a", {'class' : re.compile("fs-paging-item fs-paging-next")}) self.cursor = self.conn.cursor() if nextpage==None: try: Ttag=str(self.soup.table) #print Ttag """ ------------------分析结构体----------------- <table cellspacing="0" cellpadding="0"> <tr> <td> <h1 id="Dunhill">Dunhill</h1> </td> <td valign="middle"> <p class="fs-comm-cat"> <span class="fs-icons fs-icon-cat"> </span> <a href="TopByCategoryPage?cid=211&ref=commnav-cat">中国</a> » <a href="TopByCategoryPage?cid=211&subcid=273&ref=commnav-cat">人民</a> </p> </td> </tr> </table> """ soupTable=BeautifulSoup(Ttag) #定位到第一个h1标签 tableh1 = soupTable("h1") #print self.X #print "Name:"+tableh1[0].string.strip().encode('utf-8') #处理无类型的 try: #定位到表格中符合规则“^TopByCategory”A链接块,tablea[0]为第一个符合条件的连接文字,tablea[1]... tablea = soupTable("a", {'href' : re.compile("^TopByCategory")}) if tablea[0].string.strip()=="": pass #print "BigCLass:"+tablea[0].string.strip().encode('utf-8') #print "SubClass:"+tablea[1].string.strip().encode('utf-8') except Exception,e: if self.log_switch=="on": logapp=Pubclilog() logger,hdlr = logapp.iniLog() logger.info("[noClassInfo]"+str(self.X)+str(e)) hdlr.flush() logger.removeHandler(hdlr) self.cursor.execute("insert into baname"+str(self.mod)+" values('%d','%d','%s')" %(self.X,-1,tableh1[0].string.strip().encode('utf-8'))) self.conn.commit() self._SpiderTitle() if NextPageObj: NextPageURL=NextPageObj[0]['href'] self._SpiderClass(NextPageURL) return else: return #获取链接二对象的href值 classlink=tablea[1]['href'] par_dict=cgi.parse_qs(urlparse.urlparse(classlink).query) #print "CID:"+par_dict["cid"][0] #print "SubCID:"+par_dict["subcid"][0] #print "---------------------------------------" #插入数据库 self.cursor.execute("insert into class values('%d','%s')" %(int(par_dict["cid"][0]),tablea[0].string.strip().encode('utf-8'))) self.cursor.execute("insert into subclass values('%d','%d','%s')" %(int(par_dict["subcid"][0]),int(par_dict["cid"][0]),tablea[1].string.strip().encode('utf-8'))) self.cursor.execute("insert into baname"+str(self.mod)+" values('%d','%d','%s')" %(self.X,int(par_dict["subcid"][0]),tableh1[0].string.strip().encode('utf-8'))) self.conn.commit() self._SpiderTitle() if NextPageObj: NextPageURL=NextPageObj[0]['href'] self._SpiderClass(NextPageURL) self.body=None self.soup=None Ttag=None soupTable=None table=None table1=None classlink=None par_dict=None except Exception,e: if self.log_switch=="on": logapp=Pubclilog() logger,hdlr = logapp.iniLog() logger.info("[ClassInfo]"+str(self.X)+str(e)) hdlr.flush() logger.removeHandler(hdlr) else: self._SpiderTitle() if NextPageObj: NextPageURL=NextPageObj[0]['href'] self._SpiderClass(NextPageURL) #====================获取标题方法========================= def _SpiderTitle(self): #查找标题表格对象(table) soupTitleTable=self.soup("table", {'class' : "fs-topic-list"}) #查找标题行对象(tr) TitleTr = soupTitleTable[0]("tr", {'onmouseover' : re.compile("^this\.className='fs-row-hover'")}) """ -----------分析结构体-------------- <tr class="fs-alt-row" onmouseover="this.className='fs-row-hover'" onmouseout="this.className='fs-alt-row'"> <td valign="middle" class="fs-hot-topic-dots-ctn"> <p class="fs-hot-topic-dots" style="background-position:0 -0px" title="点击量:12"></p> </td> <td valign="middle" class="fs-topic-name"> <a href="CommMsgsPage?cmm=16081&tid=2718969307756232842&ref=regulartopics" id="a53" title="【新人报到】欢迎美国人民加入" target="_blank">【新人报到】欢迎美国人民加入</a> <span class="fs-meta"> <span class="fs-icons fs-icon-mini-reply"> </span>0 / <span class="fs-icons fs-icon-pageview"> </span>12</span> </td> <td valign="middle"> <a class="fs-tiny-user-avatar umhook " href="ProfilePage?uid=8765915421039908242" title="中国人"><img src="/static/imghwm/default1.png" data-src="http://img1.sohu.com.cn/aa/images/138/0/P/1/s.jpg" class="lazy" / alt="Sharing the source code of a crawler program written in python" ></a> </td> <td valign="middle" style="padding-left:4px"> <a href="Profile?uid=8765915421039908242" id="b53" title="中国人" class="umhook">中国人</a> </td> <td valign="middle" class="fs-topic-last-mdfy fs-meta">2-14</td> </tr> """ for CurrTr in TitleTr: try: #初始化置顶及精华状态 Title_starred='N' Title_sticky='N' #获取当前记录的BeautifulSoup对象 soupCurrTr=BeautifulSoup(str(CurrTr)) #BeautifulSoup分析HTML有误,只能通过span的标志数来获取贴子状态,会存在一定误差 #如只有精华时也会当成置顶来处理。 TitleStatus=soupCurrTr("span", {'title' : ""}) TitlePhotoViewer=soupCurrTr("a", {'href' : re.compile("^PhotoViewer")}) if TitlePhotoViewer.__len__()==1: TitlePhotoViewerBool=0 else: TitlePhotoViewerBool=1 if TitleStatus.__len__()==3-TitlePhotoViewerBool: Title_starred='Y' Title_sticky='Y' elif TitleStatus.__len__()==2-TitlePhotoViewerBool: Title_sticky='Y' #获取贴子标题 Title=soupCurrTr.a.next.strip() #获取贴子ID par_dict=cgi.parse_qs(urlparse.urlparse(soupCurrTr.a['href']).query) #获取回复数及浏览器 TitleNum=soupCurrTr("td", {'class' : "fs-topic-name"}) TitleArray=string.split(str(TitleNum[0]),'\n') Title_ReplyNum=string.split(TitleArray[len(TitleArray)-4],'>')[2] Title_ViewNum=string.split(TitleArray[len(TitleArray)-2],'>')[2][:-6] #获取贴子作者 TitleAuthorObj=soupCurrTr("td", {'style' : "padding-left:4px"}) Title_Author=TitleAuthorObj[0].next.next.next.string.strip().encode('utf-8') #获取回复时间 TitleTime=soupCurrTr("td", {'class' : re.compile("^fs-topic-last-mdfy fs-meta")}) """ print "X:"+str(self.X) print "Title_starred:"+Title_starred print "Title_sticky:"+Title_sticky print "Title:"+Title #获取贴子内容连接URL print "Title_link:"+soupCurrTr.a['href'] print "CID:"+par_dict["tid"][0] print "Title_ReplyNum:"+Title_ReplyNum print "Title_ViewNum:"+Title_ViewNum print "Title_Author:"+Title_Author print "TitleTime:"+TitleTime[0].string.strip().encode('utf-8') """ #入库 self.cursor.execute("insert into Title"+str(self.mod)+" values('%s','%d','%s','%d','%d','%s','%s','%s','%s')" %(par_dict["tid"][0], \ self.X,Title,int(Title_ReplyNum),int(Title_ViewNum),Title_starred,Title_sticky, \ Title_Author.decode('utf-8'),TitleTime[0].string.strip().encode('utf-8'))) self.conn.commit() self._SpiderContent(par_dict["tid"][0]) except Exception,e: if self.log_switch=="on": logapp=Pubclilog() logger,hdlr = logapp.iniLog() logger.info("[Title]"+str(self.X)+'-'+par_dict["tid"][0]+'-'+str(e)) hdlr.flush() logger.removeHandler(hdlr) #======================获取发表及回复方法======================= def _SpiderContent(self,ID,nextpage=None): if nextpage==None: FIXED_QUERY = 'cmm='+str(self.X)+'&tid='+ID+'&ref=regulartopics' else: FIXED_QUERY = nextpage[9:] rd = mechanize.Browser() rd.addheaders = [("User-agent", "Tianya/2010 (compatible; MSIE 6.0;Windows NT 5.1)")] rd.open(self.Content_URL + FIXED_QUERY) self.Contentbody=rd.response().read() #rd=mechanize.Request(self.Content_URL + FIXED_QUERY) #response = mechanize.urlopen(rd) #self.Contentbody=response.read() self.Contentsoup = BeautifulSoup(self.Contentbody) NextPageObj= self.Contentsoup("a", {'class' : re.compile("fs-paging-item fs-paging-next")}) try: Tp=self.Contentsoup("p", {'class' : "fs-user-action"}) i=0 for Currp in Tp: if i==0: Ctype='Y' else: Ctype='N' #发表时间 soupCurrp=BeautifulSoup(str(Currp)) PosttimeObj=soupCurrp("span", {'class' : "fs-meta"}) Posttime=PosttimeObj[0].next[1:] Posttime=Posttime[0:-3] #IP地址 IPObj=soupCurrp("a", {'href' : re.compile("CommMsgAddress")}) if IPObj: IP=IPObj[0].next.strip() else: IP='' #发表/回复内容 ContentObj=soupCurrp("p", {'class' :"fs-user-action-body"}) Content=ContentObj[0].renderContents().strip() """ print "ID:"+str(self.X) print "ID:"+ID print "Ctype:"+Ctype print "POSTTIME:"+Posttime print "IP:"+IP print "Content:"+Content """ self.cursor.execute("insert into Content"+str(self.mod)+" values('%s','%d','%s','%s','%s','%s')" %(ID,self.X,Ctype,Posttime,IP,Content.decode('utf-8'))) self.conn.commit() i+=1 except Exception,e: if self.log_switch=="on": logapp=Pubclilog() logger,hdlr = logapp.iniLog() logger.info("[Content]"+str(self.X)+'-'+ID+'-'+str(e)) hdlr.flush() logger.removeHandler(hdlr) #如“下一页”有链接刚继续遍历 if NextPageObj: NextPageURL=NextPageObj[0]['href'] self._SpiderContent(ID,NextPageURL) def __del__(self): try: self.cursor.close() self.conn.close() except Exception,e: pass #遍历comm范围 def initapp(StartValue,EndValue,log_switch): for x in range(StartValue,EndValue): app=BaseTySpider(x,log_switch) app._SpiderClass() app=None if __name__ == "__main__": #定义命令行参数 MSG_USAGE = "TySpider.py [ -s StartNumber EndNumber ] -l [on|off] [-v][-h]" parser = OptionParser(MSG_USAGE) parser.add_option("-s", "--set", nargs=2,action="store", dest="comm_value", type="int", default=False, help="配置名称ID值范围。".decode('utf-8')) parser.add_option("-l", "--log", action="store", dest="log_switch", type="string", default="on", help="错误日志开关".decode('utf-8')) parser.add_option("-v","--version", action="store_true", dest="verbose", help="显示版本信息".decode('utf-8')) opts, args = parser.parse_args() if opts.comm_value: if opts.comm_value[0]>opts.comm_value[1]: print "终止值比起始值还小?" exit(); if opts.log_switch=="on": log_switch="on" else: log_switch="off" initapp(opts.comm_value[0],opts.comm_value[1],log_switch) exit(); if opts.verbose: print "WebSite Scider V1.0 beta." exit;
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Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.

Python and C have significant differences in memory management and control. 1. Python uses automatic memory management, based on reference counting and garbage collection, simplifying the work of programmers. 2.C requires manual management of memory, providing more control but increasing complexity and error risk. Which language to choose should be based on project requirements and team technology stack.

Python's applications in scientific computing include data analysis, machine learning, numerical simulation and visualization. 1.Numpy provides efficient multi-dimensional arrays and mathematical functions. 2. SciPy extends Numpy functionality and provides optimization and linear algebra tools. 3. Pandas is used for data processing and analysis. 4.Matplotlib is used to generate various graphs and visual results.

Whether to choose Python or C depends on project requirements: 1) Python is suitable for rapid development, data science, and scripting because of its concise syntax and rich libraries; 2) C is suitable for scenarios that require high performance and underlying control, such as system programming and game development, because of its compilation and manual memory management.

Python is widely used in data science and machine learning, mainly relying on its simplicity and a powerful library ecosystem. 1) Pandas is used for data processing and analysis, 2) Numpy provides efficient numerical calculations, and 3) Scikit-learn is used for machine learning model construction and optimization, these libraries make Python an ideal tool for data science and machine learning.

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.


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