Python 爬虫

网络爬虫（又被称为网页蜘蛛，网络机器人，在FOAF社区中间，更经常的称为网页追逐者），是一种按照一定的规则，自动地抓取万维网信息的程序或者脚本。另外一些不常使用的名字还有蚂蚁、自动索引、模拟程序或者蠕虫。

关于Python的爬虫框架Scrapy

请移步至这篇博文——>>> Python爬虫框架——Scrapy

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、其它请求

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]>
    """

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)

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。

# 安装  pip3 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，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

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

4，descendants，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

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/

"破解"微信公众号

根据Django和Requests分析破解微信公众号

"破解"微信公众号其实就是使用Python代码自动实现【扫码登陆个人微信】->【获取个人所有联系人】-> 【向某联系人或群组或公众号发送消息】。如下图

那么，是如何登陆获取联系人的呢？？？

代码及解释请移步——>>> https://github.com/bingdujianer/WebWeChat