Python爬虫基础

今日概要：

  1. Requests与BeautifulSoup
  2. 爬取汽车之家的新闻资讯
  3. 爬github和抽屉
  4. 轮询和长轮询

一.HTTP知识扫盲

  1. http的get请求 是没有请求体,所有的参数都放在请求头的url里
  2. http的post请求 将请求内容放到请求体里
  3. http = 请求头+请求体 响应头+响应体
  4. http是无状态请求,一个请求，一次响应就会结束

二.Requests

Requests 是使用 Apache2 Licensed 许可证的 基于Python开发的HTTP 库，其在Python内置模块的基础上进行了高度的封装，从而使得Pythoner进行网络请求时，变得美好了许多，使用Requests可以轻而易举的完成浏览器可有的任何操作。

1.GET请求

无参数实例：

# 无参实例
import requests

data = requests.get("http://www.sina.com.cn/")
print(data.url)
print(data.text)

 有参实例：

import requests

payload = {'key1': 'value1', 'key2': 'value2'}
ret = requests.get("http://httpbin.org/get", params=payload)

print(ret.url)
print(ret.text)

 向 https://github.com/timeline.json 发送一个GET请求，将请求和响应相关均封装在 data对象中。

2.POST请求

基本POST实例：

import requests

payload = {'key1': 'value1', 'key2': 'value2'}
data = requests.post("http://httpbin.org/post", data=payload)

print(data.text)

 发送请求头和数据实例

# -*- coding:utf-8 -*-
# !/usr/bin/python

import requests
import json

url = 'https://api.github.com/some/endpoint'
payload = {'some': 'data'}
headers = {'content-type': 'application/json'}

data = requests.post(url, data=json.dumps(payload), headers=headers)

print(data.text)
print(data.cookies)

 3.其他请求

requests.get(url, params=None, **kwargs)
requests.post(url, data=None, json=None, **kwargs)
requests.put(url, data=None, **kwargs)
requests.head(url, **kwargs)
requests.delete(url, **kwargs)
requests.patch(url, data=None, **kwargs)
requests.options(url, **kwargs)
  
# 以上方法均是在此方法的基础上构建
requests.request(method, url, **kwargs)

 4.更多参数

 1 def request(method, url, **kwargs):
 2     """Constructs and sends a :class:`Request <Request>`.
 3 
 4     :param method: method for the new :class:`Request` object.
 5     :param url: URL for the new :class:`Request` object.
 6     :param params: (optional) Dictionary or bytes to be sent in the query string for the :class:`Request`.
 7     :param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`.
 8     :param json: (optional) json data to send in the body of the :class:`Request`.
 9     :param headers: (optional) Dictionary of HTTP Headers to send with the :class:`Request`.
10     :param cookies: (optional) Dict or CookieJar object to send with the :class:`Request`.
11     :param files: (optional) Dictionary of ``'name': file-like-objects`` (or ``{'name': file-tuple}``) for multipart encoding upload.
12         ``file-tuple`` can be a 2-tuple ``('filename', fileobj)``, 3-tuple ``('filename', fileobj, 'content_type')``
13         or a 4-tuple ``('filename', fileobj, 'content_type', custom_headers)``, where ``'content-type'`` is a string
14         defining the content type of the given file and ``custom_headers`` a dict-like object containing additional headers
15         to add for the file.
16     :param auth: (optional) Auth tuple to enable Basic/Digest/Custom HTTP Auth.
17     :param timeout: (optional) How long to wait for the server to send data
18         before giving up, as a float, or a :ref:`(connect timeout, read
19         timeout) <timeouts>` tuple.
20     :type timeout: float or tuple
21     :param allow_redirects: (optional) Boolean. Set to True if POST/PUT/DELETE redirect following is allowed.
22     :type allow_redirects: bool
23     :param proxies: (optional) Dictionary mapping protocol to the URL of the proxy.
24     :param verify: (optional) whether the SSL cert will be verified. A CA_BUNDLE path can also be provided. Defaults to ``True``.
25     :param stream: (optional) if ``False``, the response content will be immediately downloaded.
26     :param cert: (optional) if String, path to ssl client cert file (.pem). If Tuple, ('cert', 'key') pair.
27     :return: :class:`Response <Response>` object
28     :rtype: requests.Response
29 
30     Usage::
31 
32       >>> import requests
33       >>> req = requests.request('GET', 'http://httpbin.org/get')
34       <Response [200]>
35     """
36 
37 参数列表

 

 更多requests模块相关的文档见：http://cn.python-requests.org/zh_CN/latest/

5.爬取汽车之家新闻无需登录

# -*- coding:utf-8 -*-
# !/usr/bin/python
from bs4 import BeautifulSoup
import requests

# http方式
response = requests.get("http://www.autohome.com.cn/news/")
response.encoding = 'gbk'

soup = BeautifulSoup(response.text, "html.parser")
tag = soup.find(name="div", attrs={"id":"auto-channel-lazyload-article"})
li_list = tag.find_all("li") # [标签对象,标签对象]
for li in li_list:
    h3 = li.find(name="h3")
    if not h3:
        continue
    print(h3.text, li.find(name="a").get("href"))
"""
售13.59-18.59万元 别克新款威朗上市 //www.autohome.com.cn/news/201710/908038.html#pvareaid=102624
售11.99-14.69万元 别克阅朗正式上市 //www.autohome.com.cn/news/201710/908029.html#pvareaid=102624
售14.49-16.69万元 别克GL6正式上市 //www.autohome.com.cn/news/201710/908024.html#pvareaid=102624
售10.99-14.39万元 别克新款英朗上市 //www.autohome.com.cn/news/201710/908023.html#pvareaid=102624
中型SUV/1.6T动力 中华V7申报图曝光 //www.autohome.com.cn/news/201710/908128.html#pvareaid=102624
拉低门槛 奔驰C级或换装全新1.3T发动机 //www.autohome.com.cn/news/201710/908114.html#pvareaid=102624
外观造型硬朗 昌河全新SUV申报图曝光 //www.autohome.com.cn/news/201710/908111.html#pvareaid=102624
将于年内正式投产 捷豹XEL实车曝光 //www.autohome.com.cn/news/201710/908101.html#pvareaid=102624
与海外版一致 英菲尼迪新款Q50L申报图 //www.autohome.com.cn/news/201710/908108.html#pvareaid=102624
或11月上市/两种动力 荣威RX3实车到店 //www.autohome.com.cn/news/201710/908106.html#pvareaid=102624
更年轻 北汽新能源EC180/200推定制套装 //www.autohome.com.cn/news/201710/908107.html#pvareaid=102624
即将“复活” 别克全新凯越申报图曝光 //www.autohome.com.cn/news/201710/908105.html#pvareaid=102624
内饰焕然一新 全新牧马人产品手册曝光 //www.autohome.com.cn/news/201710/908102.html#pvareaid=102624
售16.78-17.98万元 长安CS95荣耀版上市 //www.autohome.com.cn/news/201710/908103.html#pvareaid=102624
售9.98-18.68万 2018款荣威RX5上市 //www.autohome.com.cn/news/201710/908094.html#pvareaid=102624
"""

三.BeautifulSoup

BeautifulSoup是一个模块，该模块用于接收一个HTML或XML字符串，然后将其进行格式化，之后遍可以使用他提供的方法进行快速查找指定元素，从而使得在HTML或XML中查找指定元素变得简单。

windows下安装BeautifulSoup模块：pip install BeautifulSoup4

from bs4 import BeautifulSoup
 
html_doc = """
<html><head><title>The Dormouse's story</title></head>
<body>
asdf
    <div class="title">
        <b>The Dormouse's story总共</b>
        <h1>f</h1>
    </div>
<div class="story">Once upon a time there were three little sisters; and their names were
    <a  class="sister0" id="link1">Els<span>f</span>ie</a>,
    <a href="http://example.com/lacie" class="sister" id="link2">Lacie</a> and
    <a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>;
and they lived at the bottom of a well.</div>
ad<br/>sf
<p class="story">...</p>
</body>
</html>
"""
 
soup = BeautifulSoup(html_doc, features="lxml")
# 找到第一个a标签
tag1 = soup.find(name='a')
# 找到所有的a标签
tag2 = soup.find_all(name='a')
# 找到id＝link2的标签
tag3 = soup.select('#link2')

1. name，标签名称 

# tag = soup.find('a')
# name = tag.name # 获取
# print(name)
# tag.name = 'span' # 设置
# print(soup)

2.attrs，标签属性

# tag = soup.find('a')
# attrs = tag.attrs    # 获取
# print(attrs)
# tag.attrs = {'ik':123} # 设置
# tag.attrs['id'] = 'iiiii' # 设置
# print(soup)

 3.children,所有子标签

# body = soup.find('body')
# v = body.children

 4.children,所有子子孙孙标签

# body = soup.find('body')
# v = body.descendants

5.clear,将标签的所有子标签全部清空（保留标签名）

# tag = soup.find('body')
# tag.clear()
# print(soup)

 6.decompose,递归的删除所有的标签

# body = soup.find('body')
# body.decompose()
# print(soup)

 7.extract,递归的删除所有的标签，并获取删除的标签

# body = soup.find('body')
# v = body.extract()
# print(soup)

 8. decode,转换为字符串（含当前标签）；decode_contents（不含当前标签）

# body = soup.find('body')
# v = body.decode()
# v = body.decode_contents()
# print(v)

 9.encode,转换为字节（含当前标签）；encode_contents（不含当前标签）

# body = soup.find('body')
# v = body.encode()
# v = body.encode_contents()
# print(v)

 10. find,获取匹配的第一个标签

# tag = soup.find('a')
# print(tag)
# tag = soup.find(name='a', attrs={'class': 'sister'}, recursive=True, text='Lacie')
# tag = soup.find(name='a', class_='sister', recursive=True, text='Lacie')
# print(tag)

 11. find_all,获取匹配的所有标签

 1 # tags = soup.find_all('a')
 2 # print(tags)
 3  
 4 # tags = soup.find_all('a',limit=1)
 5 # print(tags)
 6  
 7 # tags = soup.find_all(name='a', attrs={'class': 'sister'}, recursive=True, text='Lacie')
 8 # # tags = soup.find(name='a', class_='sister', recursive=True, text='Lacie')
 9 # print(tags)
10  
11  
12 # ####### 列表 #######
13 # v = soup.find_all(name=['a','div'])
14 # print(v)
15  
16 # v = soup.find_all(class_=['sister0', 'sister'])
17 # print(v)
18  
19 # v = soup.find_all(text=['Tillie'])
20 # print(v, type(v[0]))
21  
22  
23 # v = soup.find_all(id=['link1','link2'])
24 # print(v)
25  
26 # v = soup.find_all(href=['link1','link2'])
27 # print(v)
28  
29 # ####### 正则 #######
30 import re
31 # rep = re.compile('p')
32 # rep = re.compile('^p')
33 # v = soup.find_all(name=rep)
34 # print(v)
35  
36 # rep = re.compile('sister.*')
37 # v = soup.find_all(class_=rep)
38 # print(v)
39  
40 # rep = re.compile('http://www.oldboy.com/static/.*')
41 # v = soup.find_all(href=rep)
42 # print(v)
43  
44 # ####### 方法筛选 #######
45 # def func(tag):
46 # return tag.has_attr('class') and tag.has_attr('id')
47 # v = soup.find_all(name=func)
48 # print(v)
49  
50  
51 # ## get,获取标签属性
52 # tag = soup.find('a')
53 # v = tag.get('id')
54 # print(v)
View Code

12. has_attr,检查标签是否具有该属性

# tag = soup.find('a')
# v = tag.has_attr('id')
# print(v)

 13.get_text,获取标签内部文本内容

# tag = soup.find('a')
# v = tag.get_text('id')
# print(v)

 14.index,检查标签在某标签中的索引位置

# tag = soup.find('body')
# v = tag.index(tag.find('div'))
# print(v)
 
# tag = soup.find('body')
# for i,v in enumerate(tag):
# print(i,v)

 15. is_empty_element,是否是空标签(是否可以是空)或者自闭合标签，判断是否是如下标签：'br' , 'hr', 'input', 'img', 'meta','spacer', 'link', 'frame', 'base'

# tag = soup.find('br')
# v = tag.is_empty_element
# print(v)

 16. 当前的关联标签

# soup.next
# soup.next_element
# soup.next_elements
# soup.next_sibling
# soup.next_siblings
 
#
# tag.previous
# tag.previous_element
# tag.previous_elements
# tag.previous_sibling
# tag.previous_siblings
 
#
# tag.parent
# tag.parents

 17. 查找某标签的关联标签

# tag.find_next(...)
# tag.find_all_next(...)
# tag.find_next_sibling(...)
# tag.find_next_siblings(...)
 
# tag.find_previous(...)
# tag.find_all_previous(...)
# tag.find_previous_sibling(...)
# tag.find_previous_siblings(...)
 
# tag.find_parent(...)
# tag.find_parents(...)
 
# 参数同find_all

 18. select,select_one, CSS选择器

 1 soup.select("title")
 2  
 3 soup.select("p nth-of-type(3)")
 4  
 5 soup.select("body a")
 6  
 7 soup.select("html head title")
 8  
 9 tag = soup.select("span,a")
10  
11 soup.select("head > title")
12  
13 soup.select("p > a")
14  
15 soup.select("p > a:nth-of-type(2)")
16  
17 soup.select("p > #link1")
18  
19 soup.select("body > a")
20  
21 soup.select("#link1 ~ .sister")
22  
23 soup.select("#link1 + .sister")
24  
25 soup.select(".sister")
26  
27 soup.select("[class~=sister]")
28  
29 soup.select("#link1")
30  
31 soup.select("a#link2")
32  
33 soup.select('a[href]')
34  
35 soup.select('a[href="http://example.com/elsie"]')
36  
37 soup.select('a[href^="http://example.com/"]')
38  
39 soup.select('a[href$="tillie"]')
40  
41 soup.select('a[href*=".com/el"]')
42  
43  
44 from bs4.element import Tag
45  
46 def default_candidate_generator(tag):
47     for child in tag.descendants:
48         if not isinstance(child, Tag):
49             continue
50         if not child.has_attr('href'):
51             continue
52         yield child
53  
54 tags = soup.find('body').select("a", _candidate_generator=default_candidate_generator)
55 print(type(tags), tags)
56  
57 from bs4.element import Tag
58 def default_candidate_generator(tag):
59     for child in tag.descendants:
60         if not isinstance(child, Tag):
61             continue
62         if not child.has_attr('href'):
63             continue
64         yield child
65  
66 tags = soup.find('body').select("a", _candidate_generator=default_candidate_generator, limit=1)
67 print(type(tags), tags)
View Code

19. 标签的内容

# tag = soup.find('span')
# print(tag.string)          # 获取
# tag.string = 'new content' # 设置
# print(soup)
 
# tag = soup.find('body')
# print(tag.string)
# tag.string = 'xxx'
# print(soup)
 
# tag = soup.find('body')
# v = tag.stripped_strings  # 递归内部获取所有标签的文本
# print(v)

 20.append在当前标签内部追加一个标签

# tag = soup.find('body')
# tag.append(soup.find('a'))
# print(soup)
#
# from bs4.element import Tag
# obj = Tag(name='i',attrs={'id': 'it'})
# obj.string = '我是一个新来的'
# tag = soup.find('body')
# tag.append(obj)
# print(soup)

 21.insert在当前标签内部指定位置插入一个标签

# from bs4.element import Tag
# obj = Tag(name='i', attrs={'id': 'it'})
# obj.string = '我是一个新来的'
# tag = soup.find('body')
# tag.insert(2, obj)
# print(soup)

 22. insert_after,insert_before 在当前标签后面或前面插入

# from bs4.element import Tag
# obj = Tag(name='i', attrs={'id': 'it'})
# obj.string = '我是一个新来的'
# tag = soup.find('body')
# # tag.insert_before(obj)
# tag.insert_after(obj)
# print(soup)

23. replace_with 在当前标签替换为指定标签

# from bs4.element import Tag
# obj = Tag(name='i', attrs={'id': 'it'})
# obj.string = '我是一个新来的'
# tag = soup.find('div')
# tag.replace_with(obj)
# print(soup)

 24. 创建标签之间的关系

# tag = soup.find('div')
# a = soup.find('a')
# tag.setup(previous_sibling=a)
# print(tag.previous_sibling)

 25. wrap，将指定标签把当前标签包裹起来

# from bs4.element import Tag
# obj1 = Tag(name='div', attrs={'id': 'it'})
# obj1.string = '我是一个新来的'
#
# tag = soup.find('a')
# v = tag.wrap(obj1)
# print(soup)
 
# tag = soup.find('a')
# v = tag.wrap(soup.find('p'))
# print(soup)

 26. unwrap，去掉当前标签，将保留其包裹的标签

# tag = soup.find('a')
# v = tag.unwrap()
# print(soup)

 四.爬取GitHub和抽屉的新闻页

GitHub自动登录

# -*- coding:utf-8 -*-
# !/usr/bin/python
from bs4 import BeautifulSoup
import requests

# 1. 获取token和cookie
r1 = requests.get(url='https://github.com/login')
s1 = BeautifulSoup(r1.text,'html.parser')
val = s1.find(attrs={'name':'authenticity_token'}).get('value')
# cookie返回给你
r1_cookie_dict = r1.cookies.get_dict()

# 发送用户认证
r2 = requests.post(
    url='https://github.com/session',
    data={
        'commit':'Sign in',
        'utf8':'✓',
        'authenticity_token':val,
        'login':'xxx',
        'password':'xxx'
    },
    cookies = r1_cookie_dict
)

r2_cookie_dict = r2.cookies.get_dict()

print(r1_cookie_dict)
print(r2_cookie_dict)

all_cookies = {}

all_cookies.update(r1_cookie_dict)
all_cookies.update(r2_cookie_dict)

# 3.github直接用带token之后的cookies就行

r3 = requests.get('https://github.com/settings/emails',cookies=r2_cookie_dict)
print(r3.text)

 登录抽屉并自动点赞

# -*- coding:utf-8 -*-
# !/usr/bin/python
from bs4 import BeautifulSoup
import requests

r1 = requests.get(url='http://dig.chouti.com/')
r1_cookies_dict = r1.cookies.get_dict()

r2 = requests.post(
    url='http://dig.chouti.com/login',
    data={
        'phone':'xxx',
        'password':'xxx',
        'oneMonth':1
    },
    cookies = r1_cookies_dict
)
r2_cookies_dict = r2.cookies.get_dict()

print(r1_cookies_dict)
print(r2_cookies_dict)

all_cookies = {}

all_cookies.update(r1_cookies_dict)
all_cookies.update(r2_cookies_dict)


r3 = requests.post('http://dig.chouti.com/link/vote?linksId=14708906',cookies=r1_cookies_dict)
print(r3.text)

 注意:有的登录页面,登录的时候不一定会给cookie,需要get一次才给cookie,而登录的时候仅仅是授权,get的时候的cookie,这样就不需要带第二次的cookie去请求

五.轮询和长轮询

  1. 轮询：客户端定时向服务器发送Ajax请求，服务器接到请求后马上返回响应信息并关闭连接。
    优点：后端程序编写比较容易。
    缺点：请求中有大半是无用，浪费带宽和服务器资源。
    实例：适于小型应用。

  2. 长轮询：客户端向服务器发送Ajax请求，服务器接到请求后hold住连接，直到有新消息才返回响应信息并关闭连接，客户端处理完响应信息后再向服务器发送新的请求，服务器端会设置超时时间,当出现超时的时候，服务端会断开链接，客户端会再次请求服务端hold住
    优点：在无消息的情况下不会频繁的请求。
    缺点：服务器hold连接会消耗资源。
    实例：WebQQ、Hi网页版、Facebook IM。

　　另外，对于长连接和socket连接也有区分：

      1. 长连接：在页面里嵌入一个隐蔵iframe，将这个隐蔵iframe的src属性设为对一个长连接的请求，服务器端就能源源不断地往客户端输入数据。
        优点：消息即时到达，不发无用请求。
        缺点：服务器维护一个长连接会增加开销。
        实例：Gmail聊天

 

posted @ 2017-10-16 23:36  Crazy_小乐  阅读(1582)  评论(0)  编辑  收藏  举报