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单线程、多线程、多进程、协程比较,以爬取新浪军事历史为例

时间:2017-05-27 21:17:06      阅读:511      评论:0      收藏:0      [点我收藏+]

标签:mozilla   内存   uil   一半   res   random   bre   return   img   

演示python单线程、多线程、多进程、协程

  1 import requests,json,random
  2 import re,threading,time
  3 from lxml import etree
  4 
  5 lock=threading.Lock()
  6 semaphore=threading.Semaphore(100)   ###每次限制只能100线程
  7 
  8 user_agent_list = [   9         "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1" , 10         "Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 (KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11",  11         "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6",  12         "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 (KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6",  13         "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 (KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1",  14         "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5",  15         "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 (KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5",  16         "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",  17         "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",  18         "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",  19         "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",  20         "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",  21         "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",  22         "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",  23         "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",  24         "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 (KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",  25         "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",  26         "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 (KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24"
 27     ]
 28 count=0
 29 
 30 def sina(page_url):    ##列表页
 31     if semaphore.acquire():
 32         header={}
 33 
 34         header[User-Agent]=random.choice(user_agent_list)
 35         header.update({
 36             "Host":"platform.sina.com.cn",
 37 
 38             #"Cookie":"global_cookie=fb1g6d0w64d2cmu86sv4g9n3va0j137sk48; vh_newhouse=3_1491312022_2816%5B%3A%7C%40%7C%3A%5D833300ee3177d88529c7aa418942ece9; newhouse_user_guid=2F163DE7-8201-7FA9-2FB6-E507FE6F03B1; SoufunSessionID_Esf=3_1495389730_232; sf_source=; s=; showAdsh=1; hlist_xfadhq_SZ=0%7c2017%2f5%2f25+1%3a21%3a47%7c; city=sz; __utmt_t0=1; __utmt_t1=1; __utmt_t2=1; logGuid=a768dd46-b85b-47f4-a7a0-0a6596cab4cd; __utma=147393320.1111837171.1491290389.1495646208.1495650134.9; __utmb=147393320.12.10.1495650134; __utmc=147393320; __utmz=147393320.1495650134.9.4.utmcsr=esf.sz.fang.com|utmccn=(referral)|utmcmd=referral|utmcct=/; unique_cookie=U_cqyov4ut5vv1al8e2858qhzgt17j2z06mph*14"
 39             })
 40         while(1):
 41             content=‘‘
 42             try:
 43                 content=requests.get(page_url,headers=header,timeout=5).content
 44 
 45             except Exception as e:
 46                 print e
 47             if content!=‘‘:
 48                 break
 49 
 50 
 51 
 52 
 53         jsona=re.findall(jQuery191012358189839869738_1495880348059\(([\s\S]*?"}]}}),content)[0]
 54         #print jsona
 55         dict= json.loads(jsona)
 56         #print type(dict)
 57         #print dict
 58         #print dict[‘result‘][‘data‘]
 59         for l in dict[result][data]:
 60             title= l[title]
 61             url= l[url]
 62             biaoqian=get_biaoqian(url)
 63 
 64             lock.acquire()
 65             global count
 66             count+=1
 67             print time.strftime(%H:%M:%S,time.localtime(time.time())),    ,count
 68             print 列表页:
 69              70             print  title: %s\n url: %s%(title,url)
 71 
 72             print 详情页:
 73             print  biaoqian: %s \n%(biaoqian)
 74             print **************************************************************
 75             lock.release()
 76 
 77         semaphore.release()
 78 
 79 
 80 
 81 def get_biaoqian(url):    ###新闻页,爬取标签
 82 
 83     header={User-Agent:random.choice(user_agent_list)}
 84     header.update({"Host":"mil.news.sina.com.cn"})
 85 
 86     while(1):
 87         content=‘‘
 88         try:
 89             content=requests.get(url,headers=header,timeout=10).content
 90         except Exception as  e:
 91             #print e
 92             pass
 93         if content!=‘‘:
 94             break
 95 
 96 
 97     se=etree.HTML(content)
 98     #print etree.tounicode(se)
 99     biaoqian=se.xpath(//p[@class="art_keywords"]/a/text())
100     return   .join(biaoqian)
101 
102 
103 
104 
105 def singe_req():
106     for i in range(1,301):
107         page_url=http://platform.sina.com.cn/news/news_list?app_key=2872801998&channel=mil&cat_1=lishi&show_all=0&show_cat=1&show_ext=1&tag=1&format=json&page=%s&show_num=10&callback=jQuery191012358189839869738_1495880348059&_=1495880348069%i
108         sina(page_url)
109     print over
110 
111 def threading_red():
112     threads=[]
113     for i in range(1,301):
114         t=threading.Thread(target=sina,args=(http://platform.sina.com.cn/news/news_list?app_key=2872801998&channel=mil&cat_1=lishi&show_all=0&show_cat=1&show_ext=1&tag=1&format=json&page=%s&show_num=10&callback=jQuery191012358189839869738_1495880348059&_=1495880348069%i,))
115         threads.append(t)
116         t.start()
117     for t in threads:
118         t.join()
119     print over
120 
121 def  muiltiprocessing_req():
122     import multiprocessing
123     pool = multiprocessing.Pool(100)
124     #pool = multiprocessing.Pool(multiprocessing.cpu_count())
125 
126     pool.map(sina, [http://platform.sina.com.cn/news/news_list?app_key=2872801998&channel=mil&cat_1=lishi&show_all=0&show_cat=1&show_ext=1&tag=1&format=json&page=%s&show_num=10&callback=jQuery191012358189839869738_1495880348059&_=1495880348069%i for i in range(1,301)])
127     pool.close()
128     pool.join()
129     print over
130 
131 def gevent_req():
132     ######################利用pool######################
133     from gevent import monkey
134     from gevent.pool import Pool
135 
136     monkey.patch_all()
137     pool = Pool(100)
138     data= pool.map(sina, [http://platform.sina.com.cn/news/news_list?app_key=2872801998&channel=mil&cat_1=lishi&show_all=0&show_cat=1&show_ext=1&tag=1&format=json&page=%s&show_num=10&callback=jQuery191012358189839869738_1495880348059&_=1495880348069%i for i in range(1,301)])
139     print over
140 
141 if __name__==__main__:
142     pass
143     singe_req()                     ##单线程
144     #threading_red()                  ###多线程
145     #muiltiprocessing_req()             ####多进程
146 #gevent_req() ##协程


这篇主要是用四种方法来实现爬虫。无论是100线程还是100进程或者100协程,网速都撑满了,爬取速度很快,单线程对网速利用很不充分,当然就爬取缓慢。

 

 

 

特别是我之前在面试房极客时候,那主管告诉我,他说他看了网上说python多线程是假的,所以他从来就没使用过多线程,只用多进程,他认为多线程不能加快爬虫速度。

关于这一点我是非常确定python多线程能加快爬取速度的,因为我使用多线程的时间很长,那主管应该只看了一半,python对cpu密集型速度提升不了多少,但对于io密集型的速度提升是立竿见影的,特别是对timeout比较大的网站,多线程爬取优势非常明显,因为爬虫是打开页面,请求服务器后端,服务器后端操作数据库查询数据,数据库返回给后端返回给前段,这种属于io密集型,多线程在爬虫和性能测试都是可以的。而多进程实在是开销太大了,开100进程,任务管理器可以看到100个python.exe,每个占用20M内存,多进程启动时候占用cpu极高。爬虫是非常适合多线程的,或者利用协程也可以。

 

发下运行结果:

技术分享

 

单线程、多线程、多进程、协程比较,以爬取新浪军事历史为例

标签:mozilla   内存   uil   一半   res   random   bre   return   img   

原文地址:http://www.cnblogs.com/ydf0509/p/6914384.html

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