requests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)

  

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 # 获取属性
# print(attrs)
# tag.attrs = {'ik': 123} # 设置
# tag.attrs['id'] = 'v' # 设置
# print(soup)

3. children,所有子标签

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

4. children,所有子子孙孙标签

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

5. clear,将标签的所有子标签全部清空(保留标签名)

# body = soup.find('body')
# body.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)
# 使用class进行寻找的时候避免关键字,使用'class_'

11. find_all,获取匹配的所有标签

# tag = soup.find_all('a')
# print(tag) # tags = soup.find_all('a', limit=1) # 匹配到的第一个a标签
# 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) # recursive 递归查找 # ##### 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)

爬虫-request和BeautifulSoup模块的更多相关文章

  1. 【爬虫入门手记03】爬虫解析利器beautifulSoup模块的基本应用

    [爬虫入门手记03]爬虫解析利器beautifulSoup模块的基本应用 1.引言 网络爬虫最终的目的就是过滤选取网络信息,因此最重要的就是解析器了,其性能的优劣直接决定这网络爬虫的速度和效率.Bea ...

  2. 【网络爬虫入门03】爬虫解析利器beautifulSoup模块的基本应用

    [网络爬虫入门03]爬虫解析利器beautifulSoup模块的基本应用   1.引言 网络爬虫最终的目的就是过滤选取网络信息,因此最重要的就是解析器了,其性能的优劣直接决定这网络爬虫的速度和效率.B ...

  3. 爬虫-request以及beautisoup模块笔记

    requests模块 pip3 install requests res = requests.get('') res.text res.cookies.get_dict() res.content ...

  4. 爬虫----爬虫解析库Beautifulsoup模块

    一:介绍 Beautiful Soup 是一个可以从HTML或XML文件中提取数据的Python库.它能够通过你喜欢的转换器实现惯用的文档导航,查找,修改文档的方式.Beautiful Soup会帮你 ...

  5. 从0开始学爬虫7之BeautifulSoup模块的简单介绍

    参考文档: https://www.crummy.com/software/BeautifulSoup/bs4/doc.zh/ # 安装 beautifulsoup4 (pytools) D:\pyt ...

  6. Python 爬虫三 beautifulsoup模块

    beautifulsoup模块 BeautifulSoup模块 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 ...

  7. Python爬虫之Beautifulsoup模块的使用

    一 Beautifulsoup模块介绍 Beautiful Soup 是一个可以从HTML或XML文件中提取数据的Python库.它能够通过你喜欢的转换器实现惯用的文档导航,查找,修改文档的方式.Be ...

  8. requests和BeautifulSoup模块的使用

    用python写爬虫时,有两个很好用第三方模块requests库和beautifulsoup库,简单学习了下模块用法: 1,requests模块 Python标准库中提供了:urllib.urllib ...

  9. Python 实用爬虫-04-使用 BeautifulSoup 去水印下载 CSDN 博客图片

    Python 实用爬虫-04-使用 BeautifulSoup 去水印下载 CSDN 博客图片 其实没太大用,就是方便一些,因为现在各个平台之间的图片都不能共享,比如说在 CSDN 不能用简书的图片, ...

随机推荐

  1. openflow packet_out和packet_in分析

    任务目的 1. 掌握OpenFlow交换机发送Packet-in消息过程及其消息格式. 2. 掌握OpenFlow控制器发送Packet-out消息过程及其消息格式. 实验原理 Packet-In 使 ...

  2. vue stylus 格式化问题

    IDE是vscode 安装了.vetur插件 由于stylus可以仅用缩进不用写大括号之类的,所以十分方便, 但有个问题,按alt shift F 格式化时,vetur这个插件会默认添加上正常css的 ...

  3. C#使用WindowsMediaPlayer实现视频播放

    using System;using System.Collections.Generic;using System.ComponentModel;using System.Data;using Sy ...

  4. (N叉树 递归) leetcode 590. N-ary Tree Postorder Traversal

    Given an n-ary tree, return the postorder traversal of its nodes' values. For example, given a 3-ary ...

  5. [Luogu 4316] 绿豆蛙的归宿

    题目链接 一道基础的 \(DAG\) 上期望 \(DP\). 给出一个有向无环图,起点为 \(1\) 终点为 \(N\),每条边都有一个长度,并且从起点出发能够到达所有的点,所有的点也都能够到达终点. ...

  6. 如何将Windows电脑桌面上软件图标下的文字去掉

    如何将Windows电脑桌面上软件图标下的文字去掉 重命名的时候,点击鼠标右键.选择“插入Unicode控制字符” 效果

  7. 02-oracle中的基础sql

    1.SQL SQL(Structured Query Language) 语言是目前主流的关系型数据库上执行数据操作.数据检索以及数据库维护所需要的标准语言,是用户与数据库之间进行交流的接口,许多关系 ...

  8. python学习06

    流控制 和函数 1)流控制 1.条件语句 if elif else  if else 2.循环语句 while for 3.continue 和break continue是跳过本次循环,执行下一次循 ...

  9. Linux命令--tree

    目录 tree 最常用 带颜色显示2级目录 排除显示某个目录 tree tree -C :颜色显示 tree -f : 显示文件全路径 tree -L 2 :只显示2层 tree -P *.pl :只 ...

  10. 【汇编语言】DOXBox 0.74 常用debug命令

    1.查看.修改寄存器(r命令) ①-r ②-r  ax(要修改的寄存器) -:m(输入想要改成什么值) 2.查看内存单元(d命令) ①-d 查看128个内存单元内容. ②-d 段地址:偏移地址 查看指 ...