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：
