requests、BeautifulSoup、自动登陆示例
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
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': "",
'password': "xxxxxx",
'oneMonth': ""
}
) i3 = session.post(
url="http://dig.chouti.com/link/vote?linksId=8589623",
)
print(i3.text) 参数示例
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：
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
# 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/
自动登录示例
#!/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
requests、BeautifulSoup、自动登陆示例的更多相关文章
- 爬虫之Requests&beautifulsoup
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 ...
- requests+BeautifulSoup详解
简介 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 ...
- requests beautifulsoup
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, ...
- python 爬虫（一） requests+BeautifulSoup 爬取简单网页代码示例
以前搞偷偷摸摸的事,不对,是搞爬虫都是用urllib,不过真的是很麻烦,下面就使用requests + BeautifulSoup 爬爬简单的网页. 详细介绍都在代码中注释了,大家可以参阅. # -* ...
- pyspider示例代码七：自动登陆并获得PDF文件下载地址
自动登陆并获得PDF文件下载地址 #!/usr/bin/env python # -*- encoding: utf- -*- # Created on -- :: # Project: pdf_sp ...
- 2)实现github自动登陆获取信息
# -*- coding:utf-8 -*- # __author__ = 'lixiang' # 实现github自动登陆和获取数据 import requests from bs4 import ...
- 爬虫【自动登陆github和抽屉】
自动登陆github用户详情页 代码 #! /usr/bin/env python # -*- coding: utf- -*- # __author__ = "wuxiaoyu" ...
- 使用python抓取并分析数据—链家网(requests+BeautifulSoup)（转）
本篇文章是使用python抓取数据的第一篇,使用requests+BeautifulSoup的方法对页面进行抓取和数据提取.通过使用requests库对链家网二手房列表页进行抓取,通过Beautifu ...
- Python之BeautifulSoup的使用示例
import requests from bs4 import BeautifulSoup url = 'http://pm25.in/'+city_pinyin r = requests.get(u ...
随机推荐
- jenkins升级为2.134
由于前面装的jenkins版本为2.130版本,昨天(2018.7.26)发现了两个jenkins的漏洞,影响范围为:Jenkins weekly 2.132 以及更早的版本.Jenkins LTS ...
- 【java请求】- jmeter_jdbc脚本实战
一,导入 使用Jmeter运行Java脚本,需要用到Jmeter的提供的框架jar包(分别在jmeter目录下的lib和ext目录下)1.ApacheJMeter_core.jar2.ApacheJM ...
- spark读取外部配置文件的方法
spark读取外部配置文件的方法 spark-submit --files /tmp/fileName /tmp/test.jar 使用spark提交时使用--files参数,spark会将将本地的 ...
- Java解惑之TreeSet是如何去重的
引言: 最近在处理一个问题,大致是这个样子,从数据库里面取出一个集合,取出来的数据放到一个JavaBean里面.结果得到的集合长度为1. TreeSetSet的一个实现,默认实现排序:故TreeSet ...
- 亚马逊拟斥资15亿美元建航空货运中心 - Amazon to spend $1.49 bln on air cargo hub, fans talk of bigger ambitions - ReutersFebruary 1, 2017
2月1日消息,亚马逊本周二宣布将在肯塔基州开建其第一个航空货运中心,以应对高速增长的航空货运需求.亚马逊预计,该项目将带来2000个工作岗位. 据悉,该项计划总投入约为15亿美元,亚马逊或可从当地政府 ...
- 王者荣耀交流协会final冲刺第五次scrum会议
成员王超,高远博,冉华,王磊,王玉玲,任思佳,袁玥全部到齐,王磊拍照. master:高远博 2.时间跨度 2017年12月5日 18:00 - 18:31,总计31分钟 3.地点 一食堂二楼沙发座椅 ...
- 路由器DMZ功能
环境描述 172.17* 校园网 实验室路由器接入校园网,通过nat分化出网段 192.168.. 实验过程 主机A(windows)接入路由器(192.168.1.110),主机B(Ubuntu)接 ...
- Java中的网络编程-3
用户数据协议(UDP)是网络信息传输的另外一种形式, 基于UDP的通信不同于基于TCP的通信, 基于UDP的信息传递更快, 但是不提供可靠的保证. 使用UDP传输数据时, 用户无法知道数据能否正确地到 ...
- 第15章 磁盘配额（Quota）与高级文件系统管理
磁盘配额(quota)的应用与实践 什么是quota 举例来说,用户的默认主文件夹是在/home下面,如果/home是个独立的分区,假设是10G,/home下有30个账号,这样30个用户共享这10G的 ...
- 在服务器中使用 Entity Framework 的 Migration 更新数据库
在开发环境中,每次我们对要对数据库进行更改,比如增加修改表字段等.改好Entity类后,我们只需在Nuget程序包管理控制台运行 update-database 脚本却可: update-databa ...