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。
Requests(官方文档:https://2.python-requests.org//zh_CN/latest/user/quickstart.html)
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
import urllib2
import json
import cookielib
def urllib2_request(url, method="GET", cookie="", headers={}, data=None):
"""
:param url: 要请求的url
:param cookie: 请求方式,GET、POST、DELETE、PUT..
:param cookie: 要传入的cookie,cookie= 'k1=v1;k1=v2'
:param headers: 发送数据时携带的请求头,headers = {'ContentType':'application/json; charset=UTF-8'}
:param data: 要发送的数据GET方式需要传入参数,data={'d1': 'v1'}
:return: 返回元祖,响应的字符串内容 和 cookiejar对象
对于cookiejar对象,可以使用for循环访问:
for item in cookiejar:
print item.name,item.value
"""
if data:
data = json.dumps(data)
cookie_jar = cookielib.CookieJar()
handler = urllib2.HTTPCookieProcessor(cookie_jar)
opener = urllib2.build_opener(handler)
opener.addheaders.append(['Cookie', 'k1=v1;k1=v2'])
request = urllib2.Request(url=url, data=data, headers=headers)
request.get_method = lambda: method
response = opener.open(request)
origin = response.read()
return origin, cookie_jar
# GET
result = urllib2_request('http://127.0.0.1:8001/index/', method="GET")
# POST
result = urllib2_request('http://127.0.0.1:8001/index/', method="POST", data= {'k1': 'v1'})
# PUT
result = urllib2_request('http://127.0.0.1:8001/index/', method="PUT", data= {'k1': 'v1'})
封装urllib请求
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。
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)
# 获取cookie
res=requests.post(url)
cookie=res.cookies.get_dict() # 得到字典形式
参数:
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
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
(1)所有子标签
# body = soup.find('body')
# v = body.children
(2)所有子子孙孙标签
# body = soup.find('body')
# v = body.descendants
4.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)
5. decompose,递归的删除所有的标签
# body = soup.find('body')
# body.decompose()
# print(soup)
6. 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)
7. 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)
8. 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)
9. 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)
10. 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)
11. has_attr,检查标签是否具有该属性
# tag = soup.find('a')
# v = tag.has_attr('id')
# print(v)
12. get_text,获取标签内部文本内容
# tag = soup.find('a')
# v = tag.get_text('id')
# print(v)
13. 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)
14. 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)
15. 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
16. 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
17. 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)
18. 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)
19.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)
20.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)
21. 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)
22. 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)
23. 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)
24. 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)
25. 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)
简单的例子:
# 访问首页
import requests
from bs4 import BeautifulSoup
rs=requests.get(
url="https://dig.chouti.com/",
headers={"user-agent":"Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3423.2 Safari/537.36"}
)
# 登录
r2=requests.post(
url="https://dig.chouti.com/login",
headers={"user-agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3423.2 Safari/537.36"},
data={
"phone": "86+已注册电话号码",
"password": "密码",
"oneMonth": "1"
},
cookies=rs.cookies.get_dict()
)
# print(r2.text)
#点赞
r3=requests.post(
url="https://dig.chouti.com/link/vote?linksId=20438991",
headers={"user-agent": "Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/68.0.3423.2 Safari/537.36"},
cookies=rs.cookies.get_dict()
)
print(r3.text)
beautifulsoup文档:http://beautifulsoup.readthedocs.io/zh_CN/v4.4.0/
requests文档:https://2.python-requests.org//zh_CN/latest/user/quickstart.html