完整版爬虫

requests

Python标准库中提供了：urllib、urllib2、httplib等模块以供Http请求，但是，它的 API 太渣了。它是为另一个时代、另一个互联网所创建的。它需要巨量的工作，甚至包括各种方法覆盖，来完成最简单的任务。

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

# 1、无参数实例
  
import requests
  
ret = requests.get('https://github.com/timeline.json')
  
print ret.url
print ret.text
  
# 2、有参数实例
  
import requests
  
payload = {'key1': 'value1', 'key2': 'value2'}
ret = requests.get("http://httpbin.org/get", params=payload)
  
print ret.url
print ret.text

2、POST请求

# 1、基本POST实例
  
import requests
  
payload = {'key1': 'value1', 'key2': 'value2'}
ret = requests.post("http://httpbin.org/post", data=payload)
  
print ret.text
  
  
# 2、发送请求头和数据实例
  
import requests
import json
  
url = 'https://api.github.com/some/endpoint'
payload = {'some': 'data'}
headers = {'content-type': 'application/json'}
  
ret = requests.post(url, data=json.dumps(payload), headers=headers)
  
print ret.text
print ret.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

def request(method, url, **kwargs):
    """Constructs and sends a :class:`Request <Request>`.

    :param method: method for the new :class:`Request` object.
    :param url: URL for the new :class:`Request` object.
    :param params: (optional) Dictionary or bytes to be sent in the query string for the :class:`Request`.
    :param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`.
    :param json: (optional) json data to send in the body of the :class:`Request`.
    :param headers: (optional) Dictionary of HTTP Headers to send with the :class:`Request`.
    :param cookies: (optional) Dict or CookieJar object to send with the :class:`Request`.
    :param files: (optional) Dictionary of ``'name': file-like-objects`` (or ``{'name': file-tuple}``) for multipart encoding upload.
        ``file-tuple`` can be a 2-tuple ``('filename', fileobj)``, 3-tuple ``('filename', fileobj, 'content_type')``
        or a 4-tuple ``('filename', fileobj, 'content_type', custom_headers)``, where ``'content-type'`` is a string
        defining the content type of the given file and ``custom_headers`` a dict-like object containing additional headers
        to add for the file.
    :param auth: (optional) Auth tuple to enable Basic/Digest/Custom HTTP Auth.
    :param timeout: (optional) How long to wait for the server to send data
        before giving up, as a float, or a :ref:`(connect timeout, read
        timeout) <timeouts>` tuple.
    :type timeout: float or tuple
    :param allow_redirects: (optional) Boolean. Set to True if POST/PUT/DELETE redirect following is allowed.
    :type allow_redirects: bool
    :param proxies: (optional) Dictionary mapping protocol to the URL of the proxy.
    :param verify: (optional) whether the SSL cert will be verified. A CA_BUNDLE path can also be provided. Defaults to ``True``.
    :param stream: (optional) if ``False``, the response content will be immediately downloaded.
    :param cert: (optional) if String, path to ssl client cert file (.pem). If Tuple, ('cert', 'key') pair.
    :return: :class:`Response <Response>` object
    :rtype: requests.Response

    Usage::

      >>> import requests
      >>> req = requests.request('GET', 'http://httpbin.org/get')
      <Response [200]>
    """

参数列表

def param_method_url():
    # requests.request(method='get', url='http://127.0.0.1:8000/test/')
    # requests.request(method='post', url='http://127.0.0.1:8000/test/')
    pass


def param_param():
    # - 可以是字典
    # - 可以是字符串
    # - 可以是字节（ascii编码以内）

    # requests.request(method='get',
    # url='http://127.0.0.1:8000/test/',
    # params={'k1': 'v1', 'k2': '水电费'})

    # requests.request(method='get',
    # url='http://127.0.0.1:8000/test/',
    # params="k1=v1&k2=水电费&k3=v3&k3=vv3")

    # requests.request(method='get',
    # url='http://127.0.0.1:8000/test/',
    # params=bytes("k1=v1&k2=k2&k3=v3&k3=vv3", encoding='utf8'))

    # 错误
    # requests.request(method='get',
    # url='http://127.0.0.1:8000/test/',
    # params=bytes("k1=v1&k2=水电费&k3=v3&k3=vv3", encoding='utf8'))
    pass


def param_data():
    # 可以是字典
    # 可以是字符串
    # 可以是字节
    # 可以是文件对象

    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # data={'k1': 'v1', 'k2': '水电费'})

    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # data="k1=v1; k2=v2; k3=v3; k3=v4"
    # )

    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # data="k1=v1;k2=v2;k3=v3;k3=v4",
    # headers={'Content-Type': 'application/x-www-form-urlencoded'}
    # )

    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # data=open('data_file.py', mode='r', encoding='utf-8'), # 文件内容是：k1=v1;k2=v2;k3=v3;k3=v4
    # headers={'Content-Type': 'application/x-www-form-urlencoded'}
    # )
    pass


def param_json():
    # 将json中对应的数据进行序列化成一个字符串，json.dumps(...)
    # 然后发送到服务器端的body中，并且Content-Type是 {'Content-Type': 'application/json'}
    requests.request(method='POST',
                     url='http://127.0.0.1:8000/test/',
                     json={'k1': 'v1', 'k2': '水电费'})


def param_headers():
    # 发送请求头到服务器端
    requests.request(method='POST',
                     url='http://127.0.0.1:8000/test/',
                     json={'k1': 'v1', 'k2': '水电费'},
                     headers={'Content-Type': 'application/x-www-form-urlencoded'}
                     )


def param_cookies():
    # 发送Cookie到服务器端
    requests.request(method='POST',
                     url='http://127.0.0.1:8000/test/',
                     data={'k1': 'v1', 'k2': 'v2'},
                     cookies={'cook1': 'value1'},
                     )
    # 也可以使用CookieJar（字典形式就是在此基础上封装）
    from http.cookiejar import CookieJar
    from http.cookiejar import Cookie

    obj = CookieJar()
    obj.set_cookie(Cookie(version=0, name='c1', value='v1', port=None, domain='', path='/', secure=False, expires=None,
                          discard=True, comment=None, comment_url=None, rest={'HttpOnly': None}, rfc2109=False,
                          port_specified=False, domain_specified=False, domain_initial_dot=False, path_specified=False)
                   )
    requests.request(method='POST',
                     url='http://127.0.0.1:8000/test/',
                     data={'k1': 'v1', 'k2': 'v2'},
                     cookies=obj)


def param_files():
    # 发送文件
    # file_dict = {
    # 'f1': open('readme', 'rb')
    # }
    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # files=file_dict)

    # 发送文件，定制文件名
    # file_dict = {
    # 'f1': ('test.txt', open('readme', 'rb'))
    # }
    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # files=file_dict)

    # 发送文件，定制文件名
    # file_dict = {
    # 'f1': ('test.txt', "hahsfaksfa9kasdjflaksdjf")
    # }
    # requests.request(method='POST',
    # url='http://127.0.0.1:8000/test/',
    # files=file_dict)

    # 发送文件，定制文件名
    # file_dict = {
    #     'f1': ('test.txt', "hahsfaksfa9kasdjflaksdjf", 'application/text', {'k1': '0'})
    # }
    # requests.request(method='POST',
    #                  url='http://127.0.0.1:8000/test/',
    #                  files=file_dict)

    pass


def param_auth():
    from requests.auth import HTTPBasicAuth, HTTPDigestAuth

    ret = requests.get('https://api.github.com/user', auth=HTTPBasicAuth('wupeiqi', 'sdfasdfasdf'))
    print(ret.text)

    # ret = requests.get('http://192.168.1.1',
    # auth=HTTPBasicAuth('admin', 'admin'))
    # ret.encoding = 'gbk'
    # print(ret.text)

    # ret = requests.get('http://httpbin.org/digest-auth/auth/user/pass', auth=HTTPDigestAuth('user', 'pass'))
    # print(ret)
    #


def param_timeout():
    # ret = requests.get('http://google.com/', timeout=1)
    # print(ret)

    # ret = requests.get('http://google.com/', timeout=(5, 1))
    # print(ret)
    pass


def param_allow_redirects():
    ret = requests.get('http://127.0.0.1:8000/test/', allow_redirects=False)
    print(ret.text)


def param_proxies():
    # proxies = {
    # "http": "61.172.249.96:80",
    # "https": "http://61.185.219.126:3128",
    # }

    # proxies = {'http://10.20.1.128': 'http://10.10.1.10:5323'}

    # ret = requests.get("http://www.proxy360.cn/Proxy", proxies=proxies)
    # print(ret.headers)


    # from requests.auth import HTTPProxyAuth
    #
    # proxyDict = {
    # 'http': '77.75.105.165',
    # 'https': '77.75.105.165'
    # }
    # auth = HTTPProxyAuth('username', 'mypassword')
    #
    # r = requests.get("http://www.google.com", proxies=proxyDict, auth=auth)
    # print(r.text)

    pass


def param_stream():
    ret = requests.get('http://127.0.0.1:8000/test/', stream=True)
    print(ret.content)
    ret.close()

    # from contextlib import closing
    # with closing(requests.get('http://httpbin.org/get', stream=True)) as r:
    # # 在此处理响应。
    # for i in r.iter_content():
    # print(i)


def requests_session():
    import requests

    session = requests.Session()

    ### 1、首先登陆任何页面，获取cookie

    i1 = session.get(url="http://dig.chouti.com/help/service")

    ### 2、用户登陆，携带上一次的cookie，后台对cookie中的 gpsd 进行授权
    i2 = session.post(
        url="http://dig.chouti.com/login",
        data={
            'phone': "8615131255089",
            'password': "xxxxxx",
            'oneMonth': ""
        }
    )

    i3 = session.post(
        url="http://dig.chouti.com/link/vote?linksId=8589623",
    )
    print(i3.text)

参数示例

官方文档：http://cn.python-requests.org/zh_CN/latest/user/quickstart.html#id4

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。

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')

安装：

1	`pip3 install beautifulsoup4`

使用示例：

from bs4 import BeautifulSoup
 
html_doc = """
<html><head><title>The Dormouse's story</title></head>
<body>
    ...
</body>
</html>
"""
 
soup = BeautifulSoup(html_doc, features="lxml")

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. attr，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

1 2	`# body = soup.find('body')` `# v = body.children`

4. children,所有子子孙孙标签

1 2	`# 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

# tags = soup.find_all('a')
# print(tags)
 
# tags = soup.find_all('a',limit=1)
# print(tags)
 
# tags = soup.find_all(name='a', attrs={'class': 'sister'}, recursive=True, text='Lacie')
# # tags = soup.find(name='a', class_='sister', recursive=True, text='Lacie')
# print(tags)
 
 
# ####### 列表 #######
# v = soup.find_all(name=['a','div'])
# print(v)
 
# v = soup.find_all(class_=['sister0', 'sister'])
# print(v)
 
# v = soup.find_all(text=['Tillie'])
# print(v, type(v[0]))
 
 
# v = soup.find_all(id=['link1','link2'])
# print(v)
 
# v = soup.find_all(href=['link1','link2'])
# print(v)
 
# ####### 正则 #######
import re
# rep = re.compile('p')
# rep = re.compile('^p')
# v = soup.find_all(name=rep)
# print(v)
 
# rep = re.compile('sister.*')
# v = soup.find_all(class_=rep)
# print(v)
 
# rep = re.compile('http://www.oldboy.com/static/.*')
# v = soup.find_all(href=rep)
# print(v)
 
# ####### 方法筛选 #######
# def func(tag):
# return tag.has_attr('class') and tag.has_attr('id')
# v = soup.find_all(name=func)
# print(v)
 
 
# ## get,获取标签属性
# tag = soup.find('a')
# v = tag.get('id')
# print(v)

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

soup.select("title")
 
soup.select("p nth-of-type(3)")
 
soup.select("body a")
 
soup.select("html head title")
 
tag = soup.select("span,a")
 
soup.select("head > title")
 
soup.select("p > a")
 
soup.select("p > a:nth-of-type(2)")
 
soup.select("p > #link1")
 
soup.select("body > a")
 
soup.select("#link1 ~ .sister")
 
soup.select("#link1 + .sister")
 
soup.select(".sister")
 
soup.select("[class~=sister]")
 
soup.select("#link1")
 
soup.select("a#link2")
 
soup.select('a[href]')
 
soup.select('a[href="http://example.com/elsie"]')
 
soup.select('a[href^="http://example.com/"]')
 
soup.select('a[href$="tillie"]')
 
soup.select('a[href*=".com/el"]')
 
 
from bs4.element import Tag
 
def default_candidate_generator(tag):
    for child in tag.descendants:
        if not isinstance(child, Tag):
            continue
        if not child.has_attr('href'):
            continue
        yield child
 
tags = soup.find('body').select("a", _candidate_generator=default_candidate_generator)
print(type(tags), tags)
 
from bs4.element import Tag
def default_candidate_generator(tag):
    for child in tag.descendants:
        if not isinstance(child, Tag):
            continue
        if not child.has_attr('href'):
            continue
        yield child
 
tags = soup.find('body').select("a", _candidate_generator=default_candidate_generator, limit=1)
print(type(tags), tags)

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)

更多参数官方：http://beautifulsoup.readthedocs.io/zh_CN/v4.4.0/

一大波"自动登陆"示例

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


# ############## 方式一 ##############
"""
# ## 1、首先登陆任何页面，获取cookie
i1 = requests.get(url="http://dig.chouti.com/help/service")
i1_cookies = i1.cookies.get_dict()

# ## 2、用户登陆，携带上一次的cookie，后台对cookie中的 gpsd 进行授权
i2 = requests.post(
    url="http://dig.chouti.com/login",
    data={
        'phone': "8615131255089",
        'password': "xxooxxoo",
        'oneMonth': ""
    },
    cookies=i1_cookies
)

# ## 3、点赞（只需要携带已经被授权的gpsd即可）
gpsd = i1_cookies['gpsd']
i3 = requests.post(
    url="http://dig.chouti.com/link/vote?linksId=8589523",
    cookies={'gpsd': gpsd}
)

print(i3.text)
"""


# ############## 方式二 ##############
"""
import requests

session = requests.Session()
i1 = session.get(url="http://dig.chouti.com/help/service")
i2 = session.post(
    url="http://dig.chouti.com/login",
    data={
        'phone': "8615131255089",
        'password': "xxooxxoo",
        'oneMonth': ""
    }
)
i3 = session.post(
    url="http://dig.chouti.com/link/vote?linksId=8589523"
)
print(i3.text)

"""

抽屉新热榜

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

import requests
from bs4 import BeautifulSoup

# ############## 方式一 ##############
#
# # 1. 访问登陆页面，获取 authenticity_token
# i1 = requests.get('https://github.com/login')
# soup1 = BeautifulSoup(i1.text, features='lxml')
# tag = soup1.find(name='input', attrs={'name': 'authenticity_token'})
# authenticity_token = tag.get('value')
# c1 = i1.cookies.get_dict()
# i1.close()
#
# # 1. 携带authenticity_token和用户名密码等信息，发送用户验证
# form_data = {
# "authenticity_token": authenticity_token,
#     "utf8": "",
#     "commit": "Sign in",
#     "login": "wupeiqi@live.com",
#     'password': 'xxoo'
# }
#
# i2 = requests.post('https://github.com/session', data=form_data, cookies=c1)
# c2 = i2.cookies.get_dict()
# c1.update(c2)
# i3 = requests.get('https://github.com/settings/repositories', cookies=c1)
#
# soup3 = BeautifulSoup(i3.text, features='lxml')
# list_group = soup3.find(name='div', class_='listgroup')
#
# from bs4.element import Tag
#
# for child in list_group.children:
#     if isinstance(child, Tag):
#         project_tag = child.find(name='a', class_='mr-1')
#         size_tag = child.find(name='small')
#         temp = "项目:%s(%s); 项目路径:%s" % (project_tag.get('href'), size_tag.string, project_tag.string, )
#         print(temp)



# ############## 方式二 ##############
# session = requests.Session()
# # 1. 访问登陆页面，获取 authenticity_token
# i1 = session.get('https://github.com/login')
# soup1 = BeautifulSoup(i1.text, features='lxml')
# tag = soup1.find(name='input', attrs={'name': 'authenticity_token'})
# authenticity_token = tag.get('value')
# c1 = i1.cookies.get_dict()
# i1.close()
#
# # 1. 携带authenticity_token和用户名密码等信息，发送用户验证
# form_data = {
#     "authenticity_token": authenticity_token,
#     "utf8": "",
#     "commit": "Sign in",
#     "login": "wupeiqi@live.com",
#     'password': 'xxoo'
# }
#
# i2 = session.post('https://github.com/session', data=form_data)
# c2 = i2.cookies.get_dict()
# c1.update(c2)
# i3 = session.get('https://github.com/settings/repositories')
#
# soup3 = BeautifulSoup(i3.text, features='lxml')
# list_group = soup3.find(name='div', class_='listgroup')
#
# from bs4.element import Tag
#
# for child in list_group.children:
#     if isinstance(child, Tag):
#         project_tag = child.find(name='a', class_='mr-1')
#         size_tag = child.find(name='small')
#         temp = "项目:%s(%s); 项目路径:%s" % (project_tag.get('href'), size_tag.string, project_tag.string, )
#         print(temp)

github

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

import requests
from bs4 import BeautifulSoup

session = requests.Session()

i1 = session.get(
    url='https://www.zhihu.com/#signin',
    headers={
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36',
    }
)

soup1 = BeautifulSoup(i1.text, 'lxml')
xsrf_tag = soup1.find(name='input', attrs={'name': '_xsrf'})
xsrf = xsrf_tag.get('value')

current_time = time.time()
i2 = session.get(
    url='https://www.zhihu.com/captcha.gif',
    params={'r': current_time, 'type': 'login'},
    headers={
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36',
    })

with open('zhihu.gif', 'wb') as f:
    f.write(i2.content)

captcha = input('请打开zhihu.gif文件，查看并输入验证码：')
form_data = {
    "_xsrf": xsrf,
    'password': 'xxooxxoo',
    "captcha": 'captcha',
    'email': '424662508@qq.com'
}
i3 = session.post(
    url='https://www.zhihu.com/login/email',
    data=form_data,
    headers={
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36',
    }
)

i4 = session.get(
    url='https://www.zhihu.com/settings/profile',
    headers={
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_10_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/54.0.2840.98 Safari/537.36',
    }
)

soup4 = BeautifulSoup(i4.text, 'lxml')
tag = soup4.find(id='rename-section')
nick_name = tag.find('span',class_='name').string
print(nick_name)

知乎

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import re
import json
import base64

import rsa
import requests


def js_encrypt(text):
    b64der = 'MIGfMA0GCSqGSIb3DQEBAQUAA4GNADCBiQKBgQCp0wHYbg/NOPO3nzMD3dndwS0MccuMeXCHgVlGOoYyFwLdS24Im2e7YyhB0wrUsyYf0/nhzCzBK8ZC9eCWqd0aHbdgOQT6CuFQBMjbyGYvlVYU2ZP7kG9Ft6YV6oc9ambuO7nPZh+bvXH0zDKfi02prknrScAKC0XhadTHT3Al0QIDAQAB'
    der = base64.standard_b64decode(b64der)

    pk = rsa.PublicKey.load_pkcs1_openssl_der(der)
    v1 = rsa.encrypt(bytes(text, 'utf8'), pk)
    value = base64.encodebytes(v1).replace(b'\n', b'')
    value = value.decode('utf8')

    return value


session = requests.Session()

i1 = session.get('https://passport.cnblogs.com/user/signin')
rep = re.compile("'VerificationToken': '(.*)'")
v = re.search(rep, i1.text)
verification_token = v.group(1)

form_data = {
    'input1': js_encrypt('wptawy'),
    'input2': js_encrypt('asdfasdf'),
    'remember': False
}

i2 = session.post(url='https://passport.cnblogs.com/user/signin',
                  data=json.dumps(form_data),
                  headers={
                      'Content-Type': 'application/json; charset=UTF-8',
                      'X-Requested-With': 'XMLHttpRequest',
                      'VerificationToken': verification_token}
                  )

i3 = session.get(url='https://i.cnblogs.com/EditDiary.aspx')

print(i3.text)

博客园

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

import requests


# 第一步：访问登陆页,拿到X_Anti_Forge_Token，X_Anti_Forge_Code
# 1、请求url:https://passport.lagou.com/login/login.html
# 2、请求方法:GET
# 3、请求头:
#    User-agent
r1 = requests.get('https://passport.lagou.com/login/login.html',
                 headers={
                     'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36',
                 },
                 )

X_Anti_Forge_Token = re.findall("X_Anti_Forge_Token = '(.*?)'", r1.text, re.S)[0]
X_Anti_Forge_Code = re.findall("X_Anti_Forge_Code = '(.*?)'", r1.text, re.S)[0]
print(X_Anti_Forge_Token, X_Anti_Forge_Code)
# print(r1.cookies.get_dict())
# 第二步：登陆
# 1、请求url:https://passport.lagou.com/login/login.json
# 2、请求方法:POST
# 3、请求头:
#    cookie
#    User-agent
#    Referer:https://passport.lagou.com/login/login.html
#    X-Anit-Forge-Code:53165984
#    X-Anit-Forge-Token:3b6a2f62-80f0-428b-8efb-ef72fc100d78
#    X-Requested-With:XMLHttpRequest
# 4、请求体：
# isValidate:true
# username:15131252215
# password:ab18d270d7126ea65915c50288c22c0d
# request_form_verifyCode:''
# submit:''
r2 = requests.post(
    'https://passport.lagou.com/login/login.json',
    headers={
        'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36',
        'Referer': 'https://passport.lagou.com/login/login.html',
        'X-Anit-Forge-Code': X_Anti_Forge_Code,
        'X-Anit-Forge-Token': X_Anti_Forge_Token,
        'X-Requested-With': 'XMLHttpRequest'
    },
    data={
        "isValidate": True,
        'username': '15131255089',
        'password': 'ab18d270d7126ea65915c50288c22c0d',
        'request_form_verifyCode': '',
        'submit': ''
    },
    cookies=r1.cookies.get_dict()
)
print(r2.text)

拉勾网

拉钩参考：猛击这里

性能相关

在编写爬虫时，性能的消耗主要在IO请求中，当单进程单线程模式下请求URL时必然会引起等待，从而使得请求整体变慢。

import requests

def fetch_async(url):
    response = requests.get(url)
    return response


url_list = ['http://www.github.com', 'http://www.bing.com']

for url in url_list:
    fetch_async(url)

1.同步执行

from concurrent.futures import ThreadPoolExecutor
import requests


def fetch_async(url):
    response = requests.get(url)
    return response


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
    pool.submit(fetch_async, url)
pool.shutdown(wait=True)

2.多线程执行

from concurrent.futures import ThreadPoolExecutor
import requests

def fetch_async(url):
    response = requests.get(url)
    return response


def callback(future):
    print(future.result())


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ThreadPoolExecutor(5)
for url in url_list:
    v = pool.submit(fetch_async, url)
    v.add_done_callback(callback)
pool.shutdown(wait=True)

2.多线程+回调函数执行

from concurrent.futures import ProcessPoolExecutor
import requests

def fetch_async(url):
    response = requests.get(url)
    return response


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ProcessPoolExecutor(5)
for url in url_list:
    pool.submit(fetch_async, url)
pool.shutdown(wait=True)

3.多进程执行

from concurrent.futures import ProcessPoolExecutor
import requests


def fetch_async(url):
    response = requests.get(url)
    return response


def callback(future):
    print(future.result())


url_list = ['http://www.github.com', 'http://www.bing.com']
pool = ProcessPoolExecutor(5)
for url in url_list:
    v = pool.submit(fetch_async, url)
    v.add_done_callback(callback)
pool.shutdown(wait=True)

3.多进程+回调函数执行

通过上述代码均可以完成对请求性能的提高，对于多线程和多进行的缺点是在IO阻塞时会造成了线程和进程的浪费，所以异步IO回事首选：

import asyncio


@asyncio.coroutine
def func1():
    print('before...func1......')
    yield from asyncio.sleep(5)
    print('end...func1......')


tasks = [func1(), func1()]

loop = asyncio.get_event_loop()
loop.run_until_complete(asyncio.gather(*tasks))
loop.close()

1.asyncio示例1

import asyncio


@asyncio.coroutine
def fetch_async(host, url='/'):
    print(host, url)
    reader, writer = yield from asyncio.open_connection(host, 80)

    request_header_content = """GET %s HTTP/1.0\r\nHost: %s\r\n\r\n""" % (url, host,)
    request_header_content = bytes(request_header_content, encoding='utf-8')

    writer.write(request_header_content)
    yield from writer.drain()
    text = yield from reader.read()
    print(host, url, text)
    writer.close()

tasks = [
    fetch_async('www.cnblogs.com', '/wupeiqi/'),
    fetch_async('dig.chouti.com', '/pic/show?nid=4073644713430508&lid=10273091')
]

loop = asyncio.get_event_loop()
results = loop.run_until_complete(asyncio.gather(*tasks))
loop.close()

1.asyncio示例2

import aiohttp
import asyncio


@asyncio.coroutine
def fetch_async(url):
    print(url)
    response = yield from aiohttp.request('GET', url)
    # data = yield from response.read()
    # print(url, data)
    print(url, response)
    response.close()


tasks = [fetch_async('http://www.google.com/'), fetch_async('http://www.chouti.com/')]

event_loop = asyncio.get_event_loop()
results = event_loop.run_until_complete(asyncio.gather(*tasks))
event_loop.close()

2.asyncio + aiohttp

import asyncio
import requests


@asyncio.coroutine
def fetch_async(func, *args):
    loop = asyncio.get_event_loop()
    future = loop.run_in_executor(None, func, *args)
    response = yield from future
    print(response.url, response.content)


tasks = [
    fetch_async(requests.get, 'http://www.cnblogs.com/wupeiqi/'),
    fetch_async(requests.get, 'http://dig.chouti.com/pic/show?nid=4073644713430508&lid=10273091')
]

loop = asyncio.get_event_loop()
results = loop.run_until_complete(asyncio.gather(*tasks))
loop.close()

3.asyncio + requests

import gevent

import requests
from gevent import monkey

monkey.patch_all()


def fetch_async(method, url, req_kwargs):
    print(method, url, req_kwargs)
    response = requests.request(method=method, url=url, **req_kwargs)
    print(response.url, response.content)

# ##### 发送请求 #####
gevent.joinall([
    gevent.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
    gevent.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
    gevent.spawn(fetch_async, method='get', url='https://github.com/', req_kwargs={}),
])

# ##### 发送请求（协程池控制最大协程数量） #####
# from gevent.pool import Pool
# pool = Pool(None)
# gevent.joinall([
#     pool.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
#     pool.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
#     pool.spawn(fetch_async, method='get', url='https://www.github.com/', req_kwargs={}),
# ])

4.gevent + requests

import grequests


request_list = [
    grequests.get('http://httpbin.org/delay/1', timeout=0.001),
    grequests.get('http://fakedomain/'),
    grequests.get('http://httpbin.org/status/500')
]


# ##### 执行并获取响应列表 #####
# response_list = grequests.map(request_list)
# print(response_list)


# ##### 执行并获取响应列表（处理异常） #####
# def exception_handler(request, exception):
# print(request,exception)
#     print("Request failed")

# response_list = grequests.map(request_list, exception_handler=exception_handler)
# print(response_list)

5.grequests

from twisted.web.client import getPage, defer
from twisted.internet import reactor


def all_done(arg):
    reactor.stop()


def callback(contents):
    print(contents)


deferred_list = []

url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
for url in url_list:
    deferred = getPage(bytes(url, encoding='utf8'))
    deferred.addCallback(callback)
    deferred_list.append(deferred)

dlist = defer.DeferredList(deferred_list)
dlist.addBoth(all_done)

reactor.run()

6.Twisted示例

from tornado.httpclient import AsyncHTTPClient
from tornado.httpclient import HTTPRequest
from tornado import ioloop


def handle_response(response):
    """
    处理返回值内容（需要维护计数器，来停止IO循环），调用 ioloop.IOLoop.current().stop()
    :param response: 
    :return: 
    """
    if response.error:
        print("Error:", response.error)
    else:
        print(response.body)


def func():
    url_list = [
        'http://www.baidu.com',
        'http://www.bing.com',
    ]
    for url in url_list:
        print(url)
        http_client = AsyncHTTPClient()
        http_client.fetch(HTTPRequest(url), handle_response)


ioloop.IOLoop.current().add_callback(func)
ioloop.IOLoop.current().start()

7.Tornado

from twisted.internet import reactor
from twisted.web.client import getPage
import urllib.parse


def one_done(arg):
    print(arg)
    reactor.stop()

post_data = urllib.parse.urlencode({'check_data': 'adf'})
post_data = bytes(post_data, encoding='utf8')
headers = {b'Content-Type': b'application/x-www-form-urlencoded'}
response = getPage(bytes('http://dig.chouti.com/login', encoding='utf8'),
                   method=bytes('POST', encoding='utf8'),
                   postdata=post_data,
                   cookies={},
                   headers=headers)
response.addBoth(one_done)

reactor.run()

Twisted更多

以上均是Python内置以及第三方模块提供异步IO请求模块，使用简便大大提高效率，而对于异步IO请求的本质则是【非阻塞Socket】+【IO多路复用】：

import select
import socket
import time


class AsyncTimeoutException(TimeoutError):
    """
    请求超时异常类
    """

    def __init__(self, msg):
        self.msg = msg
        super(AsyncTimeoutException, self).__init__(msg)


class HttpContext(object):
    """封装请求和相应的基本数据"""

    def __init__(self, sock, host, port, method, url, data, callback, timeout=5):
        """
        sock: 请求的客户端socket对象
        host: 请求的主机名
        port: 请求的端口
        port: 请求的端口
        method: 请求方式
        url: 请求的URL
        data: 请求时请求体中的数据
        callback: 请求完成后的回调函数
        timeout: 请求的超时时间
        """
        self.sock = sock
        self.callback = callback
        self.host = host
        self.port = port
        self.method = method
        self.url = url
        self.data = data

        self.timeout = timeout

        self.__start_time = time.time()
        self.__buffer = []

    def is_timeout(self):
        """当前请求是否已经超时"""
        current_time = time.time()
        if (self.__start_time + self.timeout) < current_time:
            return True

    def fileno(self):
        """请求sockect对象的文件描述符，用于select监听"""
        return self.sock.fileno()

    def write(self, data):
        """在buffer中写入响应内容"""
        self.__buffer.append(data)

    def finish(self, exc=None):
        """在buffer中写入响应内容完成，执行请求的回调函数"""
        if not exc:
            response = b''.join(self.__buffer)
            self.callback(self, response, exc)
        else:
            self.callback(self, None, exc)

    def send_request_data(self):
        content = """%s %s HTTP/1.0\r\nHost: %s\r\n\r\n%s""" % (
            self.method.upper(), self.url, self.host, self.data,)

        return content.encode(encoding='utf8')


class AsyncRequest(object):
    def __init__(self):
        self.fds = []
        self.connections = []

    def add_request(self, host, port, method, url, data, callback, timeout):
        """创建一个要请求"""
        client = socket.socket()
        client.setblocking(False)
        try:
            client.connect((host, port))
        except BlockingIOError as e:
            pass
            # print('已经向远程发送连接的请求')
        req = HttpContext(client, host, port, method, url, data, callback, timeout)
        self.connections.append(req)
        self.fds.append(req)

    def check_conn_timeout(self):
        """检查所有的请求，是否有已经连接超时，如果有则终止"""
        timeout_list = []
        for context in self.connections:
            if context.is_timeout():
                timeout_list.append(context)
        for context in timeout_list:
            context.finish(AsyncTimeoutException('请求超时'))
            self.fds.remove(context)
            self.connections.remove(context)

    def running(self):
        """事件循环，用于检测请求的socket是否已经就绪，从而执行相关操作"""
        while True:
            r, w, e = select.select(self.fds, self.connections, self.fds, 0.05)

            if not self.fds:
                return

            for context in r:
                sock = context.sock
                while True:
                    try:
                        data = sock.recv(8096)
                        if not data:
                            self.fds.remove(context)
                            context.finish()
                            break
                        else:
                            context.write(data)
                    except BlockingIOError as e:
                        break
                    except TimeoutError as e:
                        self.fds.remove(context)
                        self.connections.remove(context)
                        context.finish(e)
                        break

            for context in w:
                # 已经连接成功远程服务器，开始向远程发送请求数据
                if context in self.fds:
                    data = context.send_request_data()
                    context.sock.sendall(data)
                    self.connections.remove(context)

            self.check_conn_timeout()


if __name__ == '__main__':
    def callback_func(context, response, ex):
        """
        :param context: HttpContext对象，内部封装了请求相关信息
        :param response: 请求响应内容
        :param ex: 是否出现异常（如果有异常则值为异常对象；否则值为None）
        :return:
        """
        print(context, response, ex)

    obj = AsyncRequest()
    url_list = [
        {'host': 'www.google.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
         'callback': callback_func},
        {'host': 'www.baidu.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
         'callback': callback_func},
        {'host': 'www.bing.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
         'callback': callback_func},
    ]
    for item in url_list:
        print(item)
        obj.add_request(**item)

    obj.running()

史上最牛逼的异步IO模块

Scrapy

Scrapy是一个为了爬取网站数据，提取结构性数据而编写的应用框架。其可以应用在数据挖掘，信息处理或存储历史数据等一系列的程序中。
其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的，也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛，可以用于数据挖掘、监测和自动化测试。

Scrapy 使用了 Twisted异步网络库来处理网络通讯。整体架构大致如下

Scrapy主要包括了以下组件：

引擎(Scrapy)
用来处理整个系统的数据流处理, 触发事务(框架核心)
调度器(Scheduler)
用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL（抓取网页的网址或者说是链接）的优先队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址
下载器(Downloader)
用于下载网页内容, 并将网页内容返回给蜘蛛(Scrapy下载器是建立在twisted这个高效的异步模型上的)
爬虫(Spiders)
爬虫是主要干活的, 用于从特定的网页中提取自己需要的信息, 即所谓的实体(Item)。用户也可以从中提取出链接,让Scrapy继续抓取下一个页面
项目管道(Pipeline)
负责处理爬虫从网页中抽取的实体，主要的功能是持久化实体、验证实体的有效性、清除不需要的信息。当页面被爬虫解析后，将被发送到项目管道，并经过几个特定的次序处理数据。
下载器中间件(Downloader Middlewares)
位于Scrapy引擎和下载器之间的框架，主要是处理Scrapy引擎与下载器之间的请求及响应。
爬虫中间件(Spider Middlewares)
介于Scrapy引擎和爬虫之间的框架，主要工作是处理蜘蛛的响应输入和请求输出。
调度中间件(Scheduler Middewares)
介于Scrapy引擎和调度之间的中间件，从Scrapy引擎发送到调度的请求和响应。

Scrapy运行流程大概如下：

引擎从调度器中取出一个链接(URL)用于接下来的抓取
引擎把URL封装成一个请求(Request)传给下载器
下载器把资源下载下来，并封装成应答包(Response)
爬虫解析Response
解析出实体（Item）,则交给实体管道进行进一步的处理
解析出的是链接（URL）,则把URL交给调度器等待抓取

一、安装

Linux
      pip3 install scrapy
 
 
Windows
      a. pip3 install wheel
      b. 下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
      c. 进入下载目录，执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl
      d. pip3 install scrapy
      e. 下载并安装pywin32：https://sourceforge.net/projects/pywin32/files/

二、基本使用

1. 基本命令

1. scrapy startproject 项目名称
   - 在当前目录中创建中创建一个项目文件（类似于Django）
 
2. scrapy genspider [-t template] <name> <domain>
   - 创建爬虫应用
   如：
      scrapy gensipider -t basic oldboy oldboy.com
      scrapy gensipider -t xmlfeed autohome autohome.com.cn
   PS:
      查看所有命令：scrapy gensipider -l
      查看模板命令：scrapy gensipider -d 模板名称
 
3. scrapy list
   - 展示爬虫应用列表
 
4. scrapy crawl 爬虫应用名称
   - 运行单独爬虫应用

2.项目结构以及爬虫应用简介

project_name/
   scrapy.cfg
   project_name/
       __init__.py
       items.py
       pipelines.py
       settings.py
       spiders/
           __init__.py
           爬虫1.py
           爬虫2.py
           爬虫3.py

文件说明：

scrapy.cfg 项目的主配置信息。（真正爬虫相关的配置信息在settings.py文件中）
items.py 设置数据存储模板，用于结构化数据，如：Django的Model
pipelines 数据处理行为，如：一般结构化的数据持久化
settings.py 配置文件，如：递归的层数、并发数，延迟下载等
spiders 爬虫目录，如：创建文件，编写爬虫规则

注意：一般创建爬虫文件时，以网站域名命名

import scrapy
 
class XiaoHuarSpider(scrapy.spiders.Spider):
    name = "xiaohuar"                            # 爬虫名称 *****
    allowed_domains = ["xiaohuar.com"]  # 允许的域名
    start_urls = [
        "http://www.xiaohuar.com/hua/",   # 其实URL
    ]
 
    def parse(self, response):
        # 访问起始URL并获取结果后的回调函数

爬虫1.py

import sys,os
sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')

关于windows编码

3. 小试牛刀

import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
 
 
class DigSpider(scrapy.Spider):
    # 爬虫应用的名称，通过此名称启动爬虫命令
    name = "dig"
 
    # 允许的域名
    allowed_domains = ["chouti.com"]
 
    # 起始URL
    start_urls = [
        'http://dig.chouti.com/',
    ]
 
    has_request_set = {}
 
    def parse(self, response):
        print(response.url)
 
        hxs = HtmlXPathSelector(response)
        page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()
        for page in page_list:
            page_url = 'http://dig.chouti.com%s' % page
            key = self.md5(page_url)
            if key in self.has_request_set:
                pass
            else:
                self.has_request_set[key] = page_url
                obj = Request(url=page_url, method='GET', callback=self.parse)
                yield obj
 
    @staticmethod
    def md5(val):
        import hashlib
        ha = hashlib.md5()
        ha.update(bytes(val, encoding='utf-8'))
        key = ha.hexdigest()
        return key

执行此爬虫文件，则在终端进入项目目录执行如下命令：

1	`scrapy crawl dig` `--nolog`

对于上述代码重要之处在于：

Request是一个封装用户请求的类，在回调函数中yield该对象表示继续访问
HtmlXpathSelector用于结构化HTML代码并提供选择器功能

4. 选择器

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from scrapy.selector import Selector, HtmlXPathSelector
from scrapy.http import HtmlResponse
html = """<!DOCTYPE html>
<html>
    <head lang="en">
        <meta charset="UTF-8">
        <title></title>
    </head>
    <body>
        <ul>
            <li class="item-"><a id='i1' href="link.html">first item</a></li>
            <li class="item-0"><a id='i2' href="llink.html">first item</a></li>
            <li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li>
        </ul>
        <div><a href="llink2.html">second item</a></div>
    </body>
</html>
"""
response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8')
# hxs = HtmlXPathSelector(response)
# print(hxs)
# hxs = Selector(response=response).xpath('//a')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[2]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id="i1"]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[contains(@href, "link")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]')
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract()
# print(hxs)
# hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first()
# print(hxs)
 
# ul_list = Selector(response=response).xpath('//body/ul/li')
# for item in ul_list:
#     v = item.xpath('./a/span')
#     # 或
#     # v = item.xpath('a/span')
#     # 或
#     # v = item.xpath('*/a/span')
#     print(v)

# -*- coding: utf-8 -*-
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest


class ChouTiSpider(scrapy.Spider):
    # 爬虫应用的名称，通过此名称启动爬虫命令
    name = "chouti"
    # 允许的域名
    allowed_domains = ["chouti.com"]

    cookie_dict = {}
    has_request_set = {}

    def start_requests(self):
        url = 'http://dig.chouti.com/'
        # return [Request(url=url, callback=self.login)]
        yield Request(url=url, callback=self.login)

    def login(self, response):
        cookie_jar = CookieJar()
        cookie_jar.extract_cookies(response, response.request)
        for k, v in cookie_jar._cookies.items():
            for i, j in v.items():
                for m, n in j.items():
                    self.cookie_dict[m] = n.value

        req = Request(
            url='http://dig.chouti.com/login',
            method='POST',
            headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},
            body='phone=8615131255089&password=pppppppp&oneMonth=1',
            cookies=self.cookie_dict,
            callback=self.check_login
        )
        yield req

    def check_login(self, response):
        req = Request(
            url='http://dig.chouti.com/',
            method='GET',
            callback=self.show,
            cookies=self.cookie_dict,
            dont_filter=True
        )
        yield req

    def show(self, response):
        # print(response)
        hxs = HtmlXPathSelector(response)
        news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]')
        for new in news_list:
            # temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()
            link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()
            yield Request(
                url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),
                method='POST',
                cookies=self.cookie_dict,
                callback=self.do_favor
            )

        page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()
        for page in page_list:

            page_url = 'http://dig.chouti.com%s' % page
            import hashlib
            hash = hashlib.md5()
            hash.update(bytes(page_url,encoding='utf-8'))
            key = hash.hexdigest()
            if key in self.has_request_set:
                pass
            else:
                self.has_request_set[key] = page_url
                yield Request(
                    url=page_url,
                    method='GET',
                    callback=self.show
                )

    def do_favor(self, response):
        print(response.text)

示例：自动登陆抽屉并点赞

# -*- coding: utf-8 -*-
import scrapy
from scrapy.http.response.html import HtmlResponse
from scrapy.http import Request
from scrapy.http.cookies import CookieJar


class ChoutiSpider(scrapy.Spider):
    name = "chouti"
    allowed_domains = ["chouti.com"]
    start_urls = (
        'http://www.chouti.com/',
    )

    def start_requests(self):
        url = 'http://dig.chouti.com/'
        yield Request(url=url, callback=self.login, meta={'cookiejar': True})

    def login(self, response):
        print(response.headers.getlist('Set-Cookie'))
        req = Request(
            url='http://dig.chouti.com/login',
            method='POST',
            headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},
            body='phone=8613121758648&password=woshiniba&oneMonth=1',
            callback=self.check_login,
            meta={'cookiejar': True}
        )
        yield req

    def check_login(self, response):
        print(response.text)

处理Cookie

注意：settings.py中设置DEPTH_LIMIT = 1来指定“递归”的层数。

5. 格式化处理

上述实例只是简单的处理，所以在parse方法中直接处理。如果对于想要获取更多的数据处理，则可以利用Scrapy的items将数据格式化，然后统一交由pipelines来处理。

import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest


class XiaoHuarSpider(scrapy.Spider):
    # 爬虫应用的名称，通过此名称启动爬虫命令
    name = "xiaohuar"
    # 允许的域名
    allowed_domains = ["xiaohuar.com"]

    start_urls = [
        "http://www.xiaohuar.com/list-1-1.html",
    ]
    # custom_settings = {
    #     'ITEM_PIPELINES':{
    #         'spider1.pipelines.JsonPipeline': 100
    #     }
    # }
    has_request_set = {}

    def parse(self, response):
        # 分析页面
        # 找到页面中符合规则的内容（校花图片），保存
        # 找到所有的a标签，再访问其他a标签，一层一层的搞下去

        hxs = HtmlXPathSelector(response)

        items = hxs.select('//div[@class="item_list infinite_scroll"]/div')
        for item in items:
            src = item.select('.//div[@class="img"]/a/img/@src').extract_first()
            name = item.select('.//div[@class="img"]/span/text()').extract_first()
            school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()
            url = "http://www.xiaohuar.com%s" % src
            from ..items import XiaoHuarItem
            obj = XiaoHuarItem(name=name, school=school, url=url)
            yield obj

        urls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href')
        for url in urls:
            key = self.md5(url)
            if key in self.has_request_set:
                pass
            else:
                self.has_request_set[key] = url
                req = Request(url=url,method='GET',callback=self.parse)
                yield req

    @staticmethod
    def md5(val):
        import hashlib
        ha = hashlib.md5()
        ha.update(bytes(val, encoding='utf-8'))
        key = ha.hexdigest()
        return key

spiders/xiahuar.py

import scrapy


class XiaoHuarItem(scrapy.Item):
    name = scrapy.Field()
    school = scrapy.Field()
    url = scrapy.Field()

items

import json
import os
import requests


class JsonPipeline(object):
    def __init__(self):
        self.file = open('xiaohua.txt', 'w')

    def process_item(self, item, spider):
        v = json.dumps(dict(item), ensure_ascii=False)
        self.file.write(v)
        self.file.write('\n')
        self.file.flush()
        return item


class FilePipeline(object):
    def __init__(self):
        if not os.path.exists('imgs'):
            os.makedirs('imgs')

    def process_item(self, item, spider):
        response = requests.get(item['url'], stream=True)
        file_name = '%s_%s.jpg' % (item['name'], item['school'])
        with open(os.path.join('imgs', file_name), mode='wb') as f:
            f.write(response.content)
        return item

pipelines

ITEM_PIPELINES = {
   'spider1.pipelines.JsonPipeline': 100,
   'spider1.pipelines.FilePipeline': 300,
}
# 每行后面的整型值，确定了他们运行的顺序，item按数字从低到高的顺序，通过pipeline，通常将这些数字定义在0-1000范围内。

settings

对于pipeline可以做更多，如下：

from scrapy.exceptions import DropItem

class CustomPipeline(object):
    def __init__(self,v):
        self.value = v

    def process_item(self, item, spider):
        # 操作并进行持久化

        # return表示会被后续的pipeline继续处理
        return item

        # 表示将item丢弃，不会被后续pipeline处理
        # raise DropItem()


    @classmethod
    def from_crawler(cls, crawler):
        """
        初始化时候，用于创建pipeline对象
        :param crawler: 
        :return: 
        """
        val = crawler.settings.getint('MMMM')
        return cls(val)

    def open_spider(self,spider):
        """
        爬虫开始执行时，调用
        :param spider: 
        :return: 
        """
        print('000000')

    def close_spider(self,spider):
        """
        爬虫关闭时，被调用
        :param spider: 
        :return: 
        """
        print('111111')

自定义pipeline

6.中间件

class SpiderMiddleware(object):

    def process_spider_input(self,response, spider):
        """
        下载完成，执行，然后交给parse处理
        :param response: 
        :param spider: 
        :return: 
        """
        pass

    def process_spider_output(self,response, result, spider):
        """
        spider处理完成，返回时调用
        :param response:
        :param result:
        :param spider:
        :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
        """
        return result

    def process_spider_exception(self,response, exception, spider):
        """
        异常调用
        :param response:
        :param exception:
        :param spider:
        :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
        """
        return None


    def process_start_requests(self,start_requests, spider):
        """
        爬虫启动时调用
        :param start_requests:
        :param spider:
        :return: 包含 Request 对象的可迭代对象
        """
        return start_requests

爬虫中间件

class DownMiddleware1(object):
    def process_request(self, request, spider):
        """
        请求需要被下载时，经过所有下载器中间件的process_request调用
        :param request: 
        :param spider: 
        :return:  
            None,继续后续中间件去下载；
            Response对象，停止process_request的执行，开始执行process_response
            Request对象，停止中间件的执行，将Request重新调度器
            raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
        """
        pass



    def process_response(self, request, response, spider):
        """
        spider处理完成，返回时调用
        :param response:
        :param result:
        :param spider:
        :return: 
            Response 对象：转交给其他中间件process_response
            Request 对象：停止中间件，request会被重新调度下载
            raise IgnoreRequest 异常：调用Request.errback
        """
        print('response1')
        return response

    def process_exception(self, request, exception, spider):
        """
        当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
        :param response:
        :param exception:
        :param spider:
        :return: 
            None：继续交给后续中间件处理异常；
            Response对象：停止后续process_exception方法
            Request对象：停止中间件，request将会被重新调用下载
        """
        return None

下载器中间件

7. 自定制命令

（1）一个项目里面同时运行多个爬虫：

在spiders同级创建任意目录，如：commands
在其中创建 crawlall.py 文件（此处文件名就是自定义的命令）

from scrapy.commands import ScrapyCommand
    from scrapy.utils.project import get_project_settings


    class Command(ScrapyCommand):

        requires_project = True

        def syntax(self):
            return '[options]'

        def short_desc(self):
            return 'Runs all of the spiders'

        def run(self, args, opts):
            spider_list = self.crawler_process.spiders.list()
            for name in spider_list:
                # 开启项目中的所有爬虫，也可以开启一些
                self.crawler_process.crawl(name, **opts.__dict__)
            self.crawler_process.start()

在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
在项目目录用终端执行命令：scrapy crawlall
如果不想使用终端开启的话，在项目下创建一个start.py文件（文件名随意），如下，直接开启文件就能运行上面配置的爬虫
```
import sys
from scrapy.cmdline import execute

if __name__ == '__main__':
    execute(["scrapy","crawlall","--nolog"])
```
（2）一个项目里面只启动单个项目，也用文件代替终端启动，无需其他配置，只需写个start.py文件（文件名随意），然后启动即可

8. 信号

信号是指，当程序执行某个地方的时候（信号），可以在这个地方写个函数（在信号中注册函数），通过函数可以做一些操作（比如日志等），但信号处不会向中间件一样能拦截请求那么大的威力。

Django信号

Django中提供了“信号调度”，用于在框架执行操作时解耦。通俗来讲，就是一些动作发生的时候，信号允许特定的发送者去提醒一些接受者。

1、Django内置信号

Model signals
    pre_init                    # django的modal执行其构造方法前，自动触发
    post_init                   # django的modal执行其构造方法后，自动触发
    pre_save                    # django的modal对象保存前，自动触发
    post_save                   # django的modal对象保存后，自动触发
    pre_delete                  # django的modal对象删除前，自动触发
    post_delete                 # django的modal对象删除后，自动触发
    m2m_changed                 # django的modal中使用m2m字段操作第三张表（add,remove,clear）前后，自动触发
    class_prepared              # 程序启动时，检测已注册的app中modal类，对于每一个类，自动触发
Management signals
    pre_migrate                 # 执行migrate命令前，自动触发
    post_migrate                # 执行migrate命令后，自动触发
Request/response signals
    request_started             # 请求到来前，自动触发
    request_finished            # 请求结束后，自动触发
    got_request_exception       # 请求异常后，自动触发
Test signals
    setting_changed             # 使用test测试修改配置文件时，自动触发
    template_rendered           # 使用test测试渲染模板时，自动触发
Database Wrappers
    connection_created          # 创建数据库连接时，自动触发

对于Django内置的信号，仅需注册指定信号，当程序执行相应操作时，自动触发注册函数

    # 在与django的settings同级目录的__init__.py文件中写上如下代码
    # （补充点其他知识：使用MySQL数据时也得在这个地方写点东西，参考bbs）

    from django.core.signals import request_finished
    from django.core.signals import request_started
    from django.core.signals import got_request_exception

    from django.db.models.signals import class_prepared
    from django.db.models.signals import pre_init, post_init
    from django.db.models.signals import pre_save, post_save
    from django.db.models.signals import pre_delete, post_delete
    from django.db.models.signals import m2m_changed
    from django.db.models.signals import pre_migrate, post_migrate

    from django.test.signals import setting_changed
    from django.test.signals import template_rendered

    from django.db.backends.signals import connection_created

    # django程序到达下面的所注册的信号处要执行的函数
    def callback(*args, **kwargs):
        print("xxoo_callback")
        print("有车来了，我要服务了",args，kwargs)

    # xxoo指上述导入的内容（都是django内置的信号，将上面的函数注册进来， 
    # 当django程序走到这的时候就会先执行这个程序），普通的注册方法
    xxoo.connect(callback)

from django.core.signals import request_finished
from django.dispatch import receiver

# 另一种注册函数的方法（通常用上面一种即可）
@receiver(request_finished)
def my_callback(sender, **kwargs):
    print("Request finished!")

2、自定义信号（一般内置足够使用了）

a. 定义信号

1 2	`import` `django.dispatch` `pizza_done` `=` `django.dispatch.Signal(providing_args=["toppings",` `"size"])`

b. 注册信号

def callback(sender, **kwargs):
    print("callback")
    print(sender,kwargs)
 
pizza_done.connect(callback)

c. 触发信号

from 路径 import pizza_done
 
pizza_done.send(sender='seven',toppings=123, size=456)

由于内置信号的触发者已经集成到Django中，所以其会自动调用，而对于自定义信号则需要开发者在任意位置触发。

更多：猛击这里

自定义扩展时，利用信号在指定位置注册制定操作

from scrapy import signals


class MyExtension(object):
    def __init__(self, value):
        self.value = value

    @classmethod
    def from_crawler(cls, crawler):
        val = crawler.settings.getint('MMMM')
        ext = cls(val)

        crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
        crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)

        return ext

    def spider_opened(self, spider):
        print('open')

    def spider_closed(self, spider):
        print('close')

View Code

Flask信号

Flask框架中的信号依赖于blinker模块，其主要就是让开发者可是在flask请求过程中定制一些用户行为。

1	`pip3 install blinker`

1. 内置信号

request_started = _signals.signal('request-started')                # 请求到来前执行
request_finished = _signals.signal('request-finished')              # 请求结束后执行
 
before_render_template = _signals.signal('before-render-template')  # 模板渲染前执行
template_rendered = _signals.signal('template-rendered')            # 模板渲染后执行
 
got_request_exception = _signals.signal('got-request-exception')    # 请求执行出现异常时执行
 
request_tearing_down = _signals.signal('request-tearing-down')      # 请求执行完毕后自动执行（无论成功与否）
appcontext_tearing_down = _signals.signal('appcontext-tearing-down')# 应用上下文执行完毕后自动执行（无论成功与否）
 
appcontext_pushed = _signals.signal('appcontext-pushed')            # 应用上下文push时执行
appcontext_popped = _signals.signal('appcontext-popped')            # 应用上下文pop时执行
message_flashed = _signals.signal('message-flashed')                # 调用flask在其中添加数据时，自动触发

使用方法：（从下面执行结果可以看出，request_started信号处比before_request装饰器（当做中间件使用）还要先执行）

源码示例

request_started

request_finished

before_render_template

template_rendered

got_request_exception

request_tearing_down

appcontext_tearing_down

appcontext_pushed

appcontext_popped

message_flashed

2. 自定义信号（内置的足够）

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from flask import Flask, current_app, flash, render_template
from flask.signals import _signals
 
app = Flask(import_name=__name__)
 
 
# 自定义信号
xxxxx = _signals.signal('xxxxx')
 
 
def func(sender, *args, **kwargs):
    print(sender)
 
# 自定义信号中注册函数
xxxxx.connect(func)
 
 
@app.route("/x")
def index():
    # 触发信号
    xxxxx.send('123123', k1='v1')
    return 'Index'
 
 
if __name__ == '__main__':
    app.run()

3. 有信号这一工具了，那么Django中的中间件，Flask中的before_request装饰器还有什么存在的意义呢：区别在于信号无法拦截请求，只能在请求或响应等流程来的时候做个记录什么的（日志）；而中间件可以return点东西拦截请求，所以还是有意义的。

scrapy信号

scrapy内置的有如下信号：

使用方法（因为下载中间件中应用了信号，所以可以模仿下载中间件写一个自定义的使用信号的扩展模块）：

from scrapy import signals

# 单独写一个类，并在settings中共注册一下最下面的配置
class MyExtension(object):
    def __init__(self, value):
        self.value = value

    @classmethod
    def from_crawler(cls, crawler):
        val = crawler.settings.getint('MMMM')
        ext = cls(val)

# 将下面的函数注册到spider_opened和spider_closed信号中
# 其他的信号也是这样注册，都跟django和Flask类似
        crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
        crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)

        return ext

    def spider_opened(self, spider):
        print('open')

    def spider_closed(self, spider):
        print('close')


# 注意 ：在sittings配置文件中的配置中解注释并改为：
EXTENSIONS = {
                    'xdb.ext.MyExtension':666,
                }

9. 避免重复访问

scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重，相关配置有：

DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'
DUPEFILTER_DEBUG = False
JOBDIR = "保存范文记录的日志路径，如：/root/"  # 最终路径为 /root/requests.seen

class RepeatUrl:
    def __init__(self):
        self.visited_url = set()

    @classmethod
    def from_settings(cls, settings):
        """
        初始化时，调用
        :param settings: 
        :return: 
        """
        return cls()

    def request_seen(self, request):
        """
        检测当前请求是否已经被访问过
        :param request: 
        :return: True表示已经访问过；False表示未访问过
        """
        if request.url in self.visited_url:
            return True
        self.visited_url.add(request.url)
        return False

    def open(self):
        """
        开始爬去请求时，调用
        :return: 
        """
        print('open replication')

    def close(self, reason):
        """
        结束爬虫爬取时，调用
        :param reason: 
        :return: 
        """
        print('close replication')

    def log(self, request, spider):
        """
        记录日志
        :param request: 
        :param spider: 
        :return: 
        """
        print('repeat', request.url)

自定义URL去重操作

10.其他

# -*- coding: utf-8 -*-

# Scrapy settings for step8_king project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     http://doc.scrapy.org/en/latest/topics/settings.html
#     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html

# 1. 爬虫名称
BOT_NAME = 'step8_king'

# 2. 爬虫应用路径
SPIDER_MODULES = ['step8_king.spiders']
NEWSPIDER_MODULE = 'step8_king.spiders'

# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头
# USER_AGENT = 'step8_king (+http://www.yourdomain.com)'

# Obey robots.txt rules
# 4. 禁止爬虫配置
# ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数
# CONCURRENT_REQUESTS = 4

# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 6. 延迟下载秒数
# DOWNLOAD_DELAY = 2


# The download delay setting will honor only one of:
# 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名
# CONCURRENT_REQUESTS_PER_DOMAIN = 2
# 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP
# CONCURRENT_REQUESTS_PER_IP = 3

# Disable cookies (enabled by default)
# 8. 是否支持cookie，cookiejar进行操作cookie
# COOKIES_ENABLED = True
# COOKIES_DEBUG = True

# Disable Telnet Console (enabled by default)
# 9. Telnet用于查看当前爬虫的信息，操作爬虫等...
#    使用telnet ip port ，然后通过命令操作
# TELNETCONSOLE_ENABLED = True
# TELNETCONSOLE_HOST = '127.0.0.1'
# TELNETCONSOLE_PORT = [6023,]


# 10. 默认请求头
# Override the default request headers:
# DEFAULT_REQUEST_HEADERS = {
#     'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#     'Accept-Language': 'en',
# }


# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
# 11. 定义pipeline处理请求
# ITEM_PIPELINES = {
#    'step8_king.pipelines.JsonPipeline': 700,
#    'step8_king.pipelines.FilePipeline': 500,
# }



# 12. 自定义扩展，基于信号进行调用
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
# EXTENSIONS = {
#     # 'step8_king.extensions.MyExtension': 500,
# }


# 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度
# DEPTH_LIMIT = 3

# 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo

# 后进先出，深度优先
# DEPTH_PRIORITY = 0
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
# 先进先出，广度优先

# DEPTH_PRIORITY = 1
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'

# 15. 调度器队列
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler


# 16. 访问URL去重
# DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'


# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html

"""
17. 自动限速算法
    from scrapy.contrib.throttle import AutoThrottle
    自动限速设置
    1. 获取最小延迟 DOWNLOAD_DELAY
    2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY
    3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY
    4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间
    5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY
    target_delay = latency / self.target_concurrency
    new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间
    new_delay = max(target_delay, new_delay)
    new_delay = min(max(self.mindelay, new_delay), self.maxdelay)
    slot.delay = new_delay
"""

# 开始自动限速
# AUTOTHROTTLE_ENABLED = True
# The initial download delay
# 初始下载延迟
# AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
# 最大下载延迟
# AUTOTHROTTLE_MAX_DELAY = 10
# The average number of requests Scrapy should be sending in parallel to each remote server
# 平均每秒并发数
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0

# Enable showing throttling stats for every response received:
# 是否显示
# AUTOTHROTTLE_DEBUG = True

# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings


"""
18. 启用缓存
    目的用于将已经发送的请求或相应缓存下来，以便以后使用
    
    from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware
    from scrapy.extensions.httpcache import DummyPolicy
    from scrapy.extensions.httpcache import FilesystemCacheStorage
"""
# 是否启用缓存策略
# HTTPCACHE_ENABLED = True

# 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
# 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"

# 缓存超时时间
# HTTPCACHE_EXPIRATION_SECS = 0

# 缓存保存路径
# HTTPCACHE_DIR = 'httpcache'

# 缓存忽略的Http状态码
# HTTPCACHE_IGNORE_HTTP_CODES = []

# 缓存存储的插件
# HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'


"""
19. 代理，需要在环境变量中设置
    from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware
    
    方式一：使用默认
        os.environ
        {
            http_proxy:http://root:woshiniba@192.168.11.11:9999/
            https_proxy:http://192.168.11.11:9999/
        }
    方式二：使用自定义下载中间件
    
    def to_bytes(text, encoding=None, errors='strict'):
        if isinstance(text, bytes):
            return text
        if not isinstance(text, six.string_types):
            raise TypeError('to_bytes must receive a unicode, str or bytes '
                            'object, got %s' % type(text).__name__)
        if encoding is None:
            encoding = 'utf-8'
        return text.encode(encoding, errors)
        
    class ProxyMiddleware(object):
        def process_request(self, request, spider):
            PROXIES = [
                {'ip_port': '111.11.228.75:80', 'user_pass': ''},
                {'ip_port': '120.198.243.22:80', 'user_pass': ''},
                {'ip_port': '111.8.60.9:8123', 'user_pass': ''},
                {'ip_port': '101.71.27.120:80', 'user_pass': ''},
                {'ip_port': '122.96.59.104:80', 'user_pass': ''},
                {'ip_port': '122.224.249.122:8088', 'user_pass': ''},
            ]
            proxy = random.choice(PROXIES)
            if proxy['user_pass'] is not None:
                request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']）
                encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))
                request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)
                print "**************ProxyMiddleware have pass************" + proxy['ip_port']
            else:
                print "**************ProxyMiddleware no pass************" + proxy['ip_port']
                request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
    
    DOWNLOADER_MIDDLEWARES = {
       'step8_king.middlewares.ProxyMiddleware': 500,
    }
    
"""

"""
20. Https访问
    Https访问时有两种情况：
    1. 要爬取网站使用的可信任证书(默认支持)
        DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
        DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"
        
    2. 要爬取网站使用的自定义证书
        DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
        DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"
        
        # https.py
        from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory
        from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)
        
        class MySSLFactory(ScrapyClientContextFactory):
            def getCertificateOptions(self):
                from OpenSSL import crypto
                v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())
                v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())
                return CertificateOptions(
                    privateKey=v1,  # pKey对象
                    certificate=v2,  # X509对象
                    verify=False,
                    method=getattr(self, 'method', getattr(self, '_ssl_method', None))
                )
    其他：
        相关类
            scrapy.core.downloader.handlers.http.HttpDownloadHandler
            scrapy.core.downloader.webclient.ScrapyHTTPClientFactory
            scrapy.core.downloader.contextfactory.ScrapyClientContextFactory
        相关配置
            DOWNLOADER_HTTPCLIENTFACTORY
            DOWNLOADER_CLIENTCONTEXTFACTORY

"""



"""
21. 爬虫中间件
    class SpiderMiddleware(object):

        def process_spider_input(self,response, spider):
            '''
            下载完成，执行，然后交给parse处理
            :param response: 
            :param spider: 
            :return: 
            '''
            pass
    
        def process_spider_output(self,response, result, spider):
            '''
            spider处理完成，返回时调用
            :param response:
            :param result:
            :param spider:
            :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
            '''
            return result
    
        def process_spider_exception(self,response, exception, spider):
            '''
            异常调用
            :param response:
            :param exception:
            :param spider:
            :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
            '''
            return None
    
    
        def process_start_requests(self,start_requests, spider):
            '''
            爬虫启动时调用
            :param start_requests:
            :param spider:
            :return: 包含 Request 对象的可迭代对象
            '''
            return start_requests
    
    内置爬虫中间件：
        'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,
        'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,
        'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,
        'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,
        'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,

"""
# from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {
   # 'step8_king.middlewares.SpiderMiddleware': 543,
}


"""
22. 下载中间件
    class DownMiddleware1(object):
        def process_request(self, request, spider):
            '''
            请求需要被下载时，经过所有下载器中间件的process_request调用
            :param request:
            :param spider:
            :return:
                None,继续后续中间件去下载；
                Response对象，停止process_request的执行，开始执行process_response
                Request对象，停止中间件的执行，将Request重新调度器
                raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
            '''
            pass
    
    
    
        def process_response(self, request, response, spider):
            '''
            spider处理完成，返回时调用
            :param response:
            :param result:
            :param spider:
            :return:
                Response 对象：转交给其他中间件process_response
                Request 对象：停止中间件，request会被重新调度下载
                raise IgnoreRequest 异常：调用Request.errback
            '''
            print('response1')
            return response
    
        def process_exception(self, request, exception, spider):
            '''
            当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
            :param response:
            :param exception:
            :param spider:
            :return:
                None：继续交给后续中间件处理异常；
                Response对象：停止后续process_exception方法
                Request对象：停止中间件，request将会被重新调用下载
            '''
            return None

    
    默认下载中间件
    {
        'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,
        'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,
        'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,
        'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,
        'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,
        'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,
        'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,
        'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,
        'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,
        'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,
        'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,
        'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,
        'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,
        'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,
    }

"""
# from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# DOWNLOADER_MIDDLEWARES = {
#    'step8_king.middlewares.DownMiddleware1': 100,
#    'step8_king.middlewares.DownMiddleware2': 500,
# }

settings

11. 大文件下载

示例文件：猛击下载

11.TinyScrapy

from twisted.web.client import getPage
from twisted.internet import reactor
from twisted.internet import defer

url_list = ['http://www.bing.com', 'http://www.baidu.com', ]


def callback(arg):
    print('回来一个', arg)


defer_list = []
for url in url_list:
    ret = getPage(bytes(url, encoding='utf8'))
    ret.addCallback(callback)
    defer_list.append(ret)


def stop(arg):
    print('已经全部现在完毕', arg)
    reactor.stop()


d = defer.DeferredList(defer_list)
d.addBoth(stop)

reactor.run()

twisted示例一

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from twisted.web.client import getPage
from twisted.internet import reactor
from twisted.internet import defer


@defer.inlineCallbacks
def task(url):
    ret = getPage(bytes(url, encoding='utf8'))
    ret.addCallback(callback)
    yield ret


def callback(arg):
    print('回来一个', arg)


url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
defer_list = []
for url in url_list:
    ret = task(url)
    defer_list.append(ret)


def stop(arg):
    print('已经全部现在完毕', arg)
    reactor.stop()


d = defer.DeferredList(defer_list)
d.addBoth(stop)
reactor.run()

twisted示例二

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactor
import threading


def _next_request():
    _next_request_from_scheduler()


def _next_request_from_scheduler():
    ret = getPage(bytes('http://www.chouti.com', encoding='utf8'))
    ret.addCallback(callback)
    ret.addCallback(lambda _: reactor.callLater(0, _next_request))


_closewait = None

@defer.inlineCallbacks
def engine_start():
    global _closewait
    _closewait = defer.Deferred()
    yield _closewait


@defer.inlineCallbacks
def task(url):
    reactor.callLater(0, _next_request)
    yield engine_start()


counter = 0
def callback(arg):
    global counter
    counter +=1
    if counter == 10:
        _closewait.callback(None)
    print('one', len(arg))


def stop(arg):
    print('all done', arg)
    reactor.stop()


if __name__ == '__main__':
    url = 'http://www.cnblogs.com'

    defer_list = []
    deferObj = task(url)
    defer_list.append(deferObj)

    v = defer.DeferredList(defer_list)
    v.addBoth(stop)
    reactor.run()

twisted示例三

#!/usr/bin/env python
# -*- coding:utf-8 -*-
from twisted.web.client import getPage, defer
from twisted.internet import reactor
import queue


class Response(object):
    def __init__(self, body, request):
        self.body = body
        self.request = request
        self.url = request.url

    @property
    def text(self):
        return self.body.decode('utf-8')


class Request(object):
    def __init__(self, url, callback=None):
        self.url = url
        self.callback = callback


class Scheduler(object):
    def __init__(self, engine):
        self.q = queue.Queue()
        self.engine = engine

    def enqueue_request(self, request):
        self.q.put(request)

    def next_request(self):
        try:
            req = self.q.get(block=False)
        except Exception as e:
            req = None

        return req

    def size(self):
        return self.q.qsize()


class ExecutionEngine(object):
    def __init__(self):
        self._closewait = None
        self.running = True
        self.start_requests = None
        self.scheduler = Scheduler(self)

        self.inprogress = set()

    def check_empty(self, response):
        if not self.running:
            self._closewait.callback('......')

    def _next_request(self):
        while self.start_requests:
            try:
                request = next(self.start_requests)
            except StopIteration:
                self.start_requests = None
            else:
                self.scheduler.enqueue_request(request)

        while len(self.inprogress) < 5 and self.scheduler.size() > 0:  # 最大并发数为5

            request = self.scheduler.next_request()
            if not request:
                break

            self.inprogress.add(request)
            d = getPage(bytes(request.url, encoding='utf-8'))
            d.addBoth(self._handle_downloader_output, request)
            d.addBoth(lambda x, req: self.inprogress.remove(req), request)
            d.addBoth(lambda x: self._next_request())

        if len(self.inprogress) == 0 and self.scheduler.size() == 0:
            self._closewait.callback(None)

    def _handle_downloader_output(self, body, request):
        """
        获取内容，执行回调函数，并且把回调函数中的返回值获取，并添加到队列中
        :param response: 
        :param request: 
        :return: 
        """
        import types

        response = Response(body, request)
        func = request.callback or self.spider.parse
        gen = func(response)
        if isinstance(gen, types.GeneratorType):
            for req in gen:
                self.scheduler.enqueue_request(req)

    @defer.inlineCallbacks
    def start(self):
        self._closewait = defer.Deferred()
        yield self._closewait

    def open_spider(self, spider, start_requests):
        self.start_requests = start_requests
        self.spider = spider
        reactor.callLater(0, self._next_request)


class Crawler(object):
    def __init__(self, spidercls):
        self.spidercls = spidercls

        self.spider = None
        self.engine = None

    @defer.inlineCallbacks
    def crawl(self):
        self.engine = ExecutionEngine()
        self.spider = self.spidercls()
        start_requests = iter(self.spider.start_requests())
        start_requests = iter(start_requests)
        self.engine.open_spider(self.spider, start_requests)
        yield self.engine.start()


class CrawlerProcess(object):
    def __init__(self):
        self._active = set()
        self.crawlers = set()

    def crawl(self, spidercls, *args, **kwargs):
        crawler = Crawler(spidercls)

        self.crawlers.add(crawler)
        d = crawler.crawl(*args, **kwargs)
        self._active.add(d)
        return d

    def start(self):
        dl = defer.DeferredList(self._active)
        dl.addBoth(self._stop_reactor)
        reactor.run()

    def _stop_reactor(self, _=None):
        reactor.stop()


class Spider(object):
    def start_requests(self):
        for url in self.start_urls:
            yield Request(url)


class ChoutiSpider(Spider):
    name = "chouti"
    start_urls = [
        'http://dig.chouti.com/',
    ]

    def parse(self, response):
        print(response.text)


class CnblogsSpider(Spider):
    name = "cnblogs"
    start_urls = [
        'http://www.cnblogs.com/',
    ]

    def parse(self, response):
        print(response.text)


if __name__ == '__main__':

    spider_cls_list = [ChoutiSpider, CnblogsSpider]

    crawler_process = CrawlerProcess()
    for spider_cls in spider_cls_list:
        crawler_process.crawl(spider_cls)

    crawler_process.start()

模拟scrapy框架

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import types
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactor



class Request(object):
    def __init__(self, url, callback):
        self.url = url
        self.callback = callback
        self.priority = 0


class HttpResponse(object):
    def __init__(self, content, request):
        self.content = content
        self.request = request


class ChouTiSpider(object):

    def start_requests(self):
        url_list = ['http://www.cnblogs.com/', 'http://www.bing.com']
        for url in url_list:
            yield Request(url=url, callback=self.parse)

    def parse(self, response):
        print(response.request.url)
        # yield Request(url="http://www.baidu.com", callback=self.parse)




from queue import Queue
Q = Queue()


class CallLaterOnce(object):
    def __init__(self, func, *a, **kw):
        self._func = func
        self._a = a
        self._kw = kw
        self._call = None

    def schedule(self, delay=0):
        if self._call is None:
            self._call = reactor.callLater(delay, self)

    def cancel(self):
        if self._call:
            self._call.cancel()

    def __call__(self):
        self._call = None
        return self._func(*self._a, **self._kw)


class Engine(object):
    def __init__(self):
        self.nextcall = None
        self.crawlling = []
        self.max = 5
        self._closewait = None

    def get_response(self,content, request):
        response = HttpResponse(content, request)
        gen = request.callback(response)
        if isinstance(gen, types.GeneratorType):
            for req in gen:
                req.priority = request.priority + 1
                Q.put(req)


    def rm_crawlling(self,response,d):
        self.crawlling.remove(d)

    def _next_request(self,spider):
        if Q.qsize() == 0 and len(self.crawlling) == 0:
            self._closewait.callback(None)

        if len(self.crawlling) >= 5:
            return
        while len(self.crawlling) < 5:
            try:
                req = Q.get(block=False)
            except Exception as e:
                req = None
            if not req:
                return
            d = getPage(req.url.encode('utf-8'))
            self.crawlling.append(d)
            d.addCallback(self.get_response, req)
            d.addCallback(self.rm_crawlling,d)
            d.addCallback(lambda _: self.nextcall.schedule())


    @defer.inlineCallbacks
    def crawl(self):
        spider = ChouTiSpider()
        start_requests = iter(spider.start_requests())
        flag = True
        while flag:
            try:
                req = next(start_requests)
                Q.put(req)
            except StopIteration as e:
                flag = False

        self.nextcall = CallLaterOnce(self._next_request,spider)
        self.nextcall.schedule()

        self._closewait = defer.Deferred()
        yield self._closewait

    @defer.inlineCallbacks
    def pp(self):
        yield self.crawl()

_active = set()
obj = Engine()
d = obj.crawl()
_active.add(d)

li = defer.DeferredList(_active)
li.addBoth(lambda _,*a,**kw: reactor.stop())

reactor.run()

参考版

点击下载

更多文档参见：http://scrapy-chs.readthedocs.io/zh_CN/latest/index.html

scrapy-redis

scrapy-redis是一个基于redis的scrapy组件，通过它可以快速实现简单分布式爬虫程序，它用了共一千行左右的代码，主要的目的就是将去重规则和调度器，以及pipeline中的数据写入到redis中，便于分布式提供快速的爬虫，该组件本质上提供了三大功能（注意：这三大功能单独使用也是可以的，无需三者联合使用，配置互不影响）：

dupefilter - URL去重规则（被调度器使用）
scheduler - 调度器
pipeline - 数据持久化

1. URL去重

接着先上面第九条开始入手讲，去重五部曲：

第一部：scrapy中自带的有去重规则，在默认的scrapy.dupefilter.RFPDupeFilter，无需任何配置就能自动调用。DUPEFILTER

第二部：可以改变一下scrapy中的去重规则，如9中的自定义的去重规则一样，继承一下RFPDupeFilter的父类BaseDupeFilter，并重写这个类即可，最后在settings中配置一下DUPEFILTER_CLASS = 'scrapy.xxx.xxxRFPDupeFilter'即可

第三部：可以改变一下scrapy中的去重规则，如9中的自定义的去重规则一样（跟上一部几乎一样的做法），但是重写类的时候将请求写在了redis中，这是自己在类中连接的redis，还没有用到redis组件，最后在settings中配置一下DUPEFILTER_CLASS = 'scrapy.xxx.xxxRFPDupeFilter'即可。

from scrapy.dupefilter import BaseDupeFilter
import redis
from scrapy.utils.request import request_fingerprint


class DupFilter(BaseDupeFilter):
    def __init__(self):
        self.conn = redis.Redis(host='140.143.227.206',port=8888,password='beta')

    def request_seen(self, request):
        """
        检测当前请求是否已经被访问过
        :param request: 
        :return: True表示已经访问过；False表示未访问过
        """
        fid = request_fingerprint(request)
        result = self.conn.sadd('visited_urls', fid)
        if result == 1:
            return False
        return True

第四部：不用自己重写类，不用自己造轮子了，人家scrapy-redis组件早都做好了，只要在settings中配置一下redis连接，然后将上面的DUPEFILTER_CLASS = 'scrapy.xxx.xxxRFPDupeFilter'改为DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'即可无需重写类，就能将封装好的请求写到redis中去了，注意这个类是scrapy_redis组件中的，并不是第一部中默认的类。

第五部：直接使用组将将数据写到redis中非常方便，但是对应key值更时间戳有关，容易发生改变，这里在第四部的基础上还是需要重写一下scrapy-redis组件中的RFPDupeFilter类，只重写一个from_settings方法即可，其他功能不变，但是要将DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'改为DUPEFILTER_CLASS = 'scrapy.xxx.xxxxxRFPDupeFilter'，同时默认的DUPEFILTER_KEY = 'dupefilter:%(timestamp)s'要加上或者解注释，但是不用修改

定义去重规则（被调度器调用并应用）
 
    a. 内部会使用以下配置进行连接Redis
 
        # REDIS_HOST = 'localhost'                            # 主机名
        # REDIS_PORT = 6379                                   # 端口
        # REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
        # REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
        # REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
        # REDIS_ENCODING = "utf-8"                            # redis编码类型             默认：'utf-8'
     
    b. 原本的去重规则中通过redis的集合完成，集合的Key为：
     
        key = defaults.DUPEFILTER_KEY % {'timestamp': int(time.time())}
           可根据上面图片中修改这个key的这个值，下面的配置文件不用修改，还是用默认的即可，但要写上，如果settings中有的话就解注释即可
        默认配置：
            DUPEFILTER_KEY = 'dupefilter:%(timestamp)s'
 

2. 调度器

将下面a. 调度器中的配置配好之后，无需其他操作就能将调度器中的任务写到redis中了，具体的settings参数如下，也能结合130中scrapy-redis.py理解一下，此外关于所有scrapy的settings文件中的配置结合130课dbd项目中settings文件理解，讲解几乎所有的配置含义。

"""
调度器，调度器使用PriorityQueue（有序集合）、FifoQueue（列表）、LifoQueue（列表）进行保存请求，并且使用RFPDupeFilter对URL去重
     
    a. 调度器
           SCHEDULER = "scrapy_redis.scheduler.Scheduler"                      # 实例化scrapy_redis的调度器
        SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'          # 默认使用优先级队列（默认），其他：PriorityQueue（有序集合（这个需要与DEPTH_PRIORITY = 1 # 广度优先     或者
# DEPTH_PRIORITY = -1 # 深度优先    配合使用）），FifoQueue（列表（相当于队列，广度优先））、LifoQueue（列表（相当于栈，深度优先））
        SCHEDULER_QUEUE_KEY = '%(spider)s:requests'                         # 调度器中请求存放在redis中的key
        SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"                  # 对保存到redis中的数据进行序列化，默认使用pickle
        SCHEDULER_PERSIST = True                                            # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空
        SCHEDULER_FLUSH_ON_START = True                                     # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空
        SCHEDULER_IDLE_BEFORE_CLOSE = 10                                    # 去调度器中获取数据时，如果为空，最多等待时间（最后没数据，未获取到）。
        SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'                  # 去重规则，在redis中保存时对应的key
        SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重规则对应处理的类
 
"""

3. 数据持久化

2. 定义持久化，爬虫yield Item对象时执行RedisPipeline
     
    a. 将item持久化到redis时，指定key和序列化函数
     
        REDIS_ITEMS_KEY = '%(spider)s:items'
        REDIS_ITEMS_SERIALIZER = 'json.dumps'
     
    b. 使用列表保存item数据

4. 起始URL相关

配置配好之后，主要是为了让爬虫结束后不停止夯住，等输入新的url的时候，又继续爬，如下配置，暂时可以不需要，有工作需求的时候，具体还得结合视频理解

"""
起始URL相关
 
    a. 获取起始URL时，去集合中获取还是去列表中获取？True，集合；False，列表
        REDIS_START_URLS_AS_SET = False    # 获取起始URL时，如果为True，则使用self.server.spop；如果为False，则使用self.server.lpop
    b. 编写爬虫时，起始URL从redis的Key中获取
        REDIS_START_URLS_KEY = '%(name)s:start_urls'
         
"""
# If True, it uses redis' ``spop`` operation. This could be useful if you
# want to avoid duplicates in your start urls list. In this cases, urls must
# be added via ``sadd`` command or you will get a type error from redis.
# REDIS_START_URLS_AS_SET = False
 
# Default start urls key for RedisSpider and RedisCrawlSpider.
# REDIS_START_URLS_KEY = '%(name)s:start_urls'

作者：E-QUAL
出处：https://www.cnblogs.com/liujiajia_me/
本文版权归作者和博客园共有，不得转载，未经作者同意参考时必须保留此段声明，且在文章页面明显位置给出原文连接。

本文内容参考如下网络文献得来，用于个人学习，如有侵权，请您告知删除修改。

参考链接： https://www.cnblogs.com/wupeiqi/articles/5246483.html

https://www.cnblogs.com/wupeiqi/articles/8249576.html

https://www.cnblogs.com/wupeiqi/articles/6912807.html

https://www.cnblogs.com/wupeiqi/articles/6229292.html

https://www.cnblogs.com/wupeiqi/articles/6283017.html

posted @ 2020-03-14 00:53 E-QUAL 阅读(167) 评论(0) 编辑收藏举报

E-QUAL

Just stick to what you love and believe in,and it will come naturally.