Python爬虫
要求：
Institute Bschool faculty directory
Stanford University https://www.gsb.stanford.edu/faculty-research/faculty
Harvard University https://www.hbs.edu/faculty/Pages/browse.aspx
Massachusetts Institute of Technology http://mitsloan.mit.edu/faculty-and-research/faculty-directory/
University of Cambridge https://www.jbs.cam.ac.uk/faculty-research/faculty-a-z/
University of Oxford https://www.sbs.ox.ac.uk/about-us/people?f[0]=department_facet%3A230
University of Chicago https://www.chicagobooth.edu/faculty/directory
Columbia University https://www8.gsb.columbia.edu/faculty-research/faculty-directory?full_time=y&division=All&op=Search&form_build_id=form-Gl3ByqgZuJU6goJNDyaIByhMhWNTlR8iWuhntfhsjf0&form_id=all_dept_form
Yale University https://som.yale.edu/faculty-research/faculty-directory
University of California, Berkeley http://facultybio.haas.berkeley.edu/faculty-photo/
University of Pennsylvania https://www.wharton.upenn.edu/faculty-directory/
只抓取以下职称：Professor，Associate Professor，Assistant Professor，Professor Emeritus
姓名、职称、邮箱、地址、电话、个人主页地址
个人背景介绍、研究领域、研究成果、教学（研究成果一般比较多，可以提供一个网页链接）
以下以Stanford University为例，进行爬虫。
因为该网站的反爬虫检测比较明显，所以需要设置代理ProxyHandler处理器。使用代理ip常常时爬虫和反爬虫比较好用的，因为很多网站会检测某一时间段某个Ip的访问次数，如果访问不像正常人，就会被禁止，而你的代码中就会报错（显示urlError,远程主机断开或者拒绝访问），而此时就要设置多个代理服务器，避免某个IP访问过于频繁。在urllib.request库中，通过ProxyHandler来设置使用代理服务器。
免费的开放代理获取基本没有成本，我们可以在一些代理网站上收集这些免费代理，测试后如果可以用，就把它收集起来用在爬虫上面。
免费短期代理网站举例：
西刺免费代理IP
快代理免费代理
Proxy360代理
全网代理IP
如果代理IP足够多，就可以像随机获取User-Agent一样，随机选择一个代理去访问网站。
import urllib.request
import urllib
import xlwt
from lxml import etree
import requests
from bs4 import BeautifulSoup
import time
import random
#36个
USER_AGENT = [
"Mozilla/5.0 (Macintosh; U; Intel Mac OS X 10_6_8; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
"Mozilla/5.0 (Windows; U; Windows NT 6.1; en-us) AppleWebKit/534.50 (KHTML, like Gecko) Version/5.1 Safari/534.50",
"Mozilla/5.0 (Windows NT 10.0; WOW64; rv:38.0) Gecko/20100101 Firefox/38.0",
"Mozilla/5.0 (Windows NT 10.0; WOW64; Trident/7.0; .NET4.0C; .NET4.0E; .NET CLR 2.0.50727; .NET CLR 3.0.30729; .NET CLR 3.5.30729; InfoPath.3; rv:11.0) like Gecko",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows NT 6.1; Trident/5.0)",
"Mozilla/4.0 (compatible; MSIE 8.0; Windows NT 6.0; Trident/4.0)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 6.0)",
"Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1)",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10.6; rv:2.0.1) Gecko/20100101 Firefox/4.0.1",
"Mozilla/5.0 (Windows NT 6.1; rv:2.0.1) Gecko/20100101 Firefox/4.0.1",
"Opera/9.80 (Macintosh; Intel Mac OS X 10.6.8; U; en) Presto/2.8.131 Version/11.11",
"Opera/9.80 (Windows NT 6.1; U; en) Presto/2.8.131 Version/11.11",
"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_7_0) AppleWebKit/535.11 (KHTML, like Gecko) Chrome/17.0.963.56 Safari/535.11",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Maxthon 2.0)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; TencentTraveler 4.0)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; The World)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Trident/4.0; SE 2.X MetaSr 1.0; SE 2.X MetaSr 1.0; .NET CLR 2.0.50727; SE 2.X MetaSr 1.0)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; 360SE)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1; Avant Browser)",
"Mozilla/4.0 (compatible; MSIE 7.0; Windows NT 5.1)",
"Mozilla/5.0 (iPhone; U; CPU iPhone OS 4_3_3 like Mac OS X; en-us) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8J2 Safari/6533.18.5",
"Mozilla/5.0 (iPod; U; CPU iPhone OS 4_3_3 like Mac OS X; en-us) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8J2 Safari/6533.18.5",
"Mozilla/5.0 (iPad; U; CPU OS 4_3_3 like Mac OS X; en-us) AppleWebKit/533.17.9 (KHTML, like Gecko) Version/5.0.2 Mobile/8J2 Safari/6533.18.5",
"Mozilla/5.0 (Linux; U; Android 2.3.7; en-us; Nexus One Build/FRF91) AppleWebKit/533.1 (KHTML, like Gecko) Version/4.0 Mobile Safari/533.1",
"MQQBrowser/26 Mozilla/5.0 (Linux; U; Android 2.3.7; zh-cn; MB200 Build/GRJ22; CyanogenMod-7) AppleWebKit/533.1 (KHTML, like Gecko) Version/4.0 Mobile Safari/533.1",
"Opera/9.80 (Android 2.3.4; Linux; Opera Mobi/build-1107180945; U; en-GB) Presto/2.8.149 Version/11.10",
"Mozilla/5.0 (Linux; U; Android 3.0; en-us; Xoom Build/HRI39) AppleWebKit/534.13 (KHTML, like Gecko) Version/4.0 Safari/534.13",
"Mozilla/5.0 (BlackBerry; U; BlackBerry 9800; en) AppleWebKit/534.1+ (KHTML, like Gecko) Version/6.0.0.337 Mobile Safari/534.1+",
"Mozilla/5.0 (hp-tablet; Linux; hpwOS/3.0.0; U; en-US) AppleWebKit/534.6 (KHTML, like Gecko) wOSBrowser/233.70 Safari/534.6 TouchPad/1.0",
"Mozilla/5.0 (SymbianOS/9.4; Series60/5.0 NokiaN97-1/20.0.019; Profile/MIDP-2.1 Configuration/CLDC-1.1) AppleWebKit/525 (KHTML, like Gecko) BrowserNG/7.1.18124",
"Mozilla/5.0 (compatible; MSIE 9.0; Windows Phone OS 7.5; Trident/5.0; IEMobile/9.0; HTC; Titan)",
"UCWEB7.0.2.37/28/999",
"NOKIA5700/ UCWEB7.0.2.37/28/999",
"Openwave/ UCWEB7.0.2.37/28/999",
"Mozilla/4.0 (compatible; MSIE 6.0; ) Opera/UCWEB7.0.2.37/28/999",
# iPhone 6：
"Mozilla/6.0 (iPhone; CPU iPhone OS 8_0 like Mac OS X) AppleWebKit/536.26 (KHTML, like Gecko) Version/8.0 Mobile/10A5376e Safari/8536.25",
]
# 代理ip
IPS = [ {'http':'115.223.253.171:9000'},
{'http':'58.254.220.116:53579'},
{'http':'119.254.94.103:45431'},
{'http':'117.35.57.196:80'},
{'http':'221.2.155.35:8060'},
{ 'http': '118.190.95.35:9001'},
{'http': '124.235.181.175:80'},
{ 'http': '110.73.6.70:8123'},
{ 'http': '110.73.0.121:8123'},
{ 'http': '222.94.145.158:808'},
{ 'http': '118.190.95.35:9001'},
{ 'http': '124.235.181.175:80'},
{'http':'112.230.247.164:8060'},
{'http':'121.196.196.105:80'},
{'http':'219.145.170.23'},
{'http':'115.218.215.184:9000'},
{'http':'58.254.220.116:53579'},
{'http':'119.254.94.103:45431'},
{'http':'117.35.57.196:80'},
{'http':'221.2.155.35:8060'},
{'http':'47.106.92.90:8081'}
]
访问主页的url,并抓取主页上的teacher,（至于想要通过例如职位之类的筛选，可以之后再处理）
k = ['A', 'B', 'C', 'D', 'E', 'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'K', 'U', 'V', 'W',
'X', 'Y', 'Z']
def get_html(i):
proxy = random.choice(IPS)
b = random.choice(USER_AGENT)
header2 = {"User-Agent": b}
httpproxy_handler = urllib.request.ProxyHandler(proxy)
opener = urllib.request.build_opener(httpproxy_handler)
url = 'https://www.gsb.stanford.edu/faculty-research/faculty?last_name=' + k[i]
req = urllib.request.Request(url, headers=header2)
response=opener.open(req)
html = response.read().decode('utf-8')
return html
因为在主页中，并不是把所有的老师都放在同一个页面上，而是按照名字的字母进行分类，所以需要先把所有的老师的name，以及个人主页的网址爬出来。
def get_data(html):
soup = BeautifulSoup(html, 'html.parser')
div_people_list = soup.find_all('div' , attrs = {'class' : 'field-item even'})
div_job_list=soup.find_all('div' , attrs = {'class' : 'person-position'})
for list in div_people_list:
a_s=list.find_all('a')
for a in a_s :
df=a['href'].replace(' ','')
df.replace('\n','')
url = 'https://www.gsb.stanford.edu%s'%df
url.replace('\n','')
url=url.replace('\n','')
name = a.get_text()
names.append(name)
PersonalWebsites.append(url)
for jlist in div_job_list:
if(jlist!=None):
j_s=jlist.string
else:
j_s='null'
jobs.append(j_s)
time.sleep(2)
再每次url切换的时候，可以通过time.sleep()、response.close等方式来减缓访问过于频繁。
然后就是根据每次得到的某个teacher的个人主页进行，爬取自己想要的部分数据
def get_data2(url):
proxy = random.choice(IPS)
print(proxy)
b = random.choice(USER_AGENT)
header2 = {"User-Agent": b}
httpproxy_handler = urllib.request.ProxyHandler(proxy)
opener = urllib.request.build_opener(httpproxy_handler)
req = urllib.request.Request(url, headers=header2)
response = opener.open(req)
html = response.read().decode('utf-8')
soup = BeautifulSoup(html, 'html.parser') # html.parser是解析器
s = etree.HTML(html)
#研究领域(Academic Area)
aca=soup.find('div', attrs={'class': 'field-name-field-academic-area-single'})
if(aca!=None):
acade=aca.find('a')
academic=acade.get_text()
else:
academic='null'
Academics.append(academic)
emi = s.xpath('//*[@id="block-system-main"]/div/div/div[1]/fieldset/div/div[2]/div/div/span/a/@href')
if (emi != []):
email = emi[0]
else:
email = 'null'
emails.append(email)
# 获取联系方式
te = s.xpath('//*[@id="block-system-main"]/div/div/div[1]/fieldset/div/div[1]/div[1]/div/div/a/text()')
if (te!=[]):
tel = te[0]
else:
tel = 'null'
tels.append(tel)
# 获取背景介绍
s = etree.HTML(html)
backgro = s.xpath('//*[@id="block-system-main"]/div/div/div[2]/div/div[1]/div[1]/p[1]/text()')
if (backgro == []):
background = 'null'
else:
background=backgro[0]
Backgrounds.append(background)
# 研究兴趣（Research Interests)
inter = s.xpath('//*[@id="block-system-main"]/div/div/div[2]/div[4]/div/ul/li/text()')
interes=''
if (inter!=[]):
for ints in inter:
interes=interes+ints+" "
interest = interes
else:
interest='null'
InterestsAreas.append(interest)
response.close()
time.sleep(2)
最后就是写主函数，调用自己写的方法了。完整的源码以及最后得到的结果可以从我上传的资源里查看（附上的是斯坦福和哈佛的）。
我遇到的其中一个问题是，本来是利用BeautifulSoup包，通过选择器来定位，但是存在一个问题，就是tag标签的嵌套问题。
比如一个段落里面<p>m,ssmn<br></br>nbmd<a href='www.baidu.com'>wewerw</a></p>,如果想要<p>之间的所有文本，就会出错，返回空列表；而利用xpath的方法定位到p标签的位置，可以得到最前部分的文本，但文本不全。
如果有人知道怎么解决这个问题，欢迎留言