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、urllib2、httplib等模块以供Http请求，使用起来较为麻烦。requests是基于Python开发的HTTP 第三方库，在Python内置模块的基础上进行了高度的封装，使用了更简单，代码量更少。 官方文档：http://docs.python-requests.org/zh_CN/latest/user/quickstart.html
requests的api 主要包括了八个方法：
def get(url, params=None, **kwargs)： def options(url, **kwargs): def head(url, **kwargs): def post(url, data=None, json=None, **kwargs): def put(url, data=None, **kwargs): def patch(url, data=None, **kwargs): def delete(url, **kwargs): #上面方法都是基于request方法实现的（method参数） def request(method, url, **kwargs):
最常用的主要是get方法和post方法，其源码如下，都是基于request方法，参数和request方法一样。
def get(url, params=None, **kwargs): """Sends a GET request. :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 **kwargs: Optional arguments that ``request`` takes. :return: :class:`Response <Response>` object :rtype: requests.Response """ kwargs.setdefault('allow_redirects', True) return request('get', url, params=params, **kwargs) # 发送get请求，基于request方法，method=‘get’ def post(url, data=None, json=None, **kwargs): """Sends a POST request. :param url: URL for the new :class:`Request` object. :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 **kwargs: Optional arguments that ``request`` takes. :return: :class:`Response <Response>` object :rtype: requests.Response """ return request('post', url, data=data, json=json, **kwargs) # 发送post请求，基于request方法，method=‘post‘’
request方法源码如下：
def request(method, url, **kwargs): """Constructs and sends a :class:`Request <Request>`. :param method: method for the new :class:`Request` object. #method,对应‘get’，‘post’，‘put’,'delete'等。必须参数 :param url: URL for the new :class:`Request` object. # url,必须参数 :param params: (optional) Dictionary or bytes to be sent in the query string for the :class:`Request`. # params，url中的查询字符窜，字典或字节类型，urlencode方法 :param data: (optional) Dictionary, bytes, or file-like object to send in the body of the :class:`Request`. #data， 发送的数据，字典，字节，和类文件对象 :param json: (optional) json data to send in the body of the :class:`Request`. #json， 发送的数据，json格式的 :param headers: (optional) Dictionary of HTTP Headers to send with the :class:`Request`. # headers，请求头，字典格式 :param cookies: (optional) Dict or CookieJar object to send with the :class:`Request`. # cookies，字典或CookieJar对象 :param files: (optional) Dictionary of ``'name': file-like-objects`` (or ``{'name': file-tuple}``) for multipart encoding upload. #字典{‘name’：file-like obj} ``file-tuple`` can be a 2-tuple ``('filename', fileobj)``, 3-tuple ``('filename', fileobj, 'content_type')`` #或字典{‘name’：file-tuple} （嵌套元组） 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. #auth，元组 :param timeout: (optional) How long to wait for the server to send data #超时时间，浮点数或元组 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. #allow_redirects,是否允许重定向， :type allow_redirects: bool :param proxies: (optional) Dictionary mapping protocol to the URL of the proxy. #代理服务器，协议和url字典 {'http':proxy_ip} :param verify: (optional) whether the SSL cert will be verified. A CA_BUNDLE path can also be provided. Defaults to ``True``. #verify，是否ssl认证，默认为True :param stream: (optional) if ``False``, the response content will be immediately downloaded. # stream，默认为false，会直接下载到内存，文件较大时应设置为True :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]> """ # By using the 'with' statement we are sure the session is closed, thus we # avoid leaving sockets open which can trigger a ResourceWarning in some # cases, and look like a memory leak in others. with sessions.Session() as session: return session.request(method=method, url=url, **kwargs)
相关参数注意：data数据类型可以为字典，但若是嵌套字典时需要用json。参数举例如下：
method： # requests.request(method='get', url='http://127.0.0.1:8000/test/') # requests.request(method='post', url='http://127.0.0.1:8000/test/'） params: # - 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')) 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'} # ) 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'}) 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'} ) 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) 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) auth: 认证方法 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) timeout: 超时时间 # ret = requests.get('http://google.com/', timeout=1) # print(ret) # ret = requests.get('http://google.com/', timeout=(5, 1)) # print(ret) allow_redirects: ret = requests.get('http://127.0.0.1:8000/test/', allow_redirects=False) print(ret.text) 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)
stream: ret = requests.get('http://127.0.0.1:8000/test/', stream=True) #默认为false，会直接将文件下载到内存，文件过大时会撑满内存， 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(): # 设置成True时，遍历内容时才开始下载 # print(i)
request方法的最后调用了Session 类，其内部也实现了request，get，post等方法，部分源码如下：
class Session(SessionRedirectMixin): """A Requests session. Provides cookie persistence, connection-pooling, and configuration. Basic Usage:: >>> import requests >>> s = requests.Session() >>> s.get('http://httpbin.org/get') <Response [200]> Or as a context manager:: >>> with requests.Session() as s: >>> s.get('http://httpbin.org/get') <Response [200]>
1.1 Seeeion 对象
下面代码两者的区别：requests.get相当于每次请求时都新建了一个session对象，而requests.session()是新建一个session对象，然后重复利用该session对象，从而实现保持session对象的cookie，参数等在不同请求中保持持久化。（所以Session对象拥有requests的所有http method）
官方文档：http://docs.python-requests.org/en/latest/user/advanced/#session-objects
参考博客：https://stackabuse.com/the-python-requests-module/
#利用Session
client = requests.session() resp = client.get(url='...')
#利用requests resp = requests.get(url='...')
不同session的cookie保持：如下面的代码，对于first_session每次请求都会带上{"cookies":{"cookieone":"111"}}， 而对于second_session，每次请求都会带上{"cookies":{"cookietwo":"222"}}；
import requests first_session = requests.Session() second_session = requests.Session() first_session.get('http://httpbin.org/cookies/set/cookieone/111') r = first_session.get('http://httpbin.org/cookies') print(r.text) second_session.get('http://httpbin.org/cookies/set/cookietwo/222') r = second_session.get('http://httpbin.org/cookies') print(r.text) r = first_session.get('http://httpbin.org/anything') print(r.text)
output：
{"cookies":{"cookieone":"111"}}
{"cookies":{"cookietwo":"222"}}
{"args":{},"data":"","files":{},"form":{},"headers":{"Accept":"*/*","Accept-Encoding":"gzip, deflate","Connection":"close","Cookie":"cookieone=111","Host":"httpbin.org","User-Agent":"python-requests/2.9.1"},"json":null,"method":"GET","origin":"103.9.74.222","url":"http://httpbin.org/anything"}
session的cookie更新： 如下面代码中，通过first_session.cookies更新的cookie会跟随每次请求，而first_session.get() 请求中cookies参数传入的cookie，只对该请求有效，不会被持久化。
import requests first_session = requests.Session() first_session.cookies.update({'default_cookie': 'default'}) r = first_session.get('http://httpbin.org/cookies', cookies={'first-cookie': '111'}) print(r.text) r = first_session.get('http://httpbin.org/cookies') print(r.text)
output：
{"cookies":{"default_cookie":"default","first-cookie":"111"}}
{"cookies":{"default_cookie":"default"}}
session应用举例：
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': "" } ) # 3，保持会话，自动带着授权的cookie进行访问 i3 = session.post( url="http://dig.chouti.com/link/vote?linksId=8589623", ) print(i3.text)
1.2 Response
request的返回值为Response对象，其有很多有用的属性和方法，如下：
通过response.cookies，response.headers，response.status_code，encoding可以拿到服务器返回的cookies, 响应头，状态码，编码等信息。
通过response.content和text，可以分别拿到响应网页的二进制和unicode数据。
class Response(object): """The :class:`Response <Response>` object, which contains a server's response to an HTTP request. """ __attrs__ = [ '_content', 'status_code', 'headers', 'url', 'history', 'encoding', 'reason', 'cookies', 'elapsed', 'request' ]
@property
def content(self): """Content of the response, in bytes."""
@property
def text(self): """Content of the response, in unicode."""
另外下载文件时的官方推荐写法如下，stream=True表示采用数据流，边下载边写入，而不是一次性全部写入内存，r.iter_content(chunk_size=256)表示每次下载256字节数据。
import requests r = requests.get('https://cdn.pixabay.com/photo/2018/07/05/02/50/sun-hat-3517443_1280.jpg', stream=True) downloaded_file = open("sun-hat.jpg", "wb") for chunk in r.iter_content(chunk_size=256): if chunk: downloaded_file.write(chunk)
#下面方法能拿到原始的数据
import requests
r = requests.get("http://exampleurl.com", stream=True)
r.raw 2，BeautifulSoup模块
BeautifulSopu模块是一个可以从HTML或XML文件中提取数据的Python第三方库。其接受一个html或xml字符串（或html，xml文档句柄），将文档被转换成Unicode，利用解析器来解析这段文档。BeautifulSoup支持几种不同的解析器：python标准库中的html.parser，以及第三方库lxml，lxml-xml和html5lib。Beautiful Soup最终将复杂HTML文档转换成一个复杂的树形结构,每个节点都是Python对象,所有对象可以归纳为4种: Tag , NavigableString , BeautifulSoup , Comment .
官方文档：https://beautifulsoup.readthedocs.io/zh_CN/v4.4.0/
BeautifulSoup的构造方法接受html文档后，得到实例化BeautifulSoup对象，由于该对象继承了Tag类，拥有Tag类的属性和方法。Beautiful部分源码：
class BeautifulSoup(Tag): ROOT_TAG_NAME = u'[document]' DEFAULT_BUILDER_FEATURES = ['html', 'fast'] ASCII_SPACES = 'x20x0ax09x0cx0d' NO_PARSER_SPECIFIED_WARNING = "No parser was explicitly specified, so I'm using the best available %(markup_type)s parser for this system ("%(parser)s"). This usually isn't a problem, but if you run this code on another system, or in a different virtual environment, it may use a different parser and behave differently. The code that caused this warning is on line %(line_number)s of the file %(filename)s. To get rid of this warning, change code that looks like this: BeautifulSoup([your markup]) to this: BeautifulSoup([your markup], "%(parser)s") " def __init__(self, markup="", features=None, builder=None, parse_only=None, from_encoding=None, exclude_encodings=None, **kwargs): """The Soup object is initialized as the 'root tag', and the provided markup (which can be a string or a file-like object) is fed into the underlying parser."""
Tag对象与XML或HTML原生文档中的tag相同，Tag类中有很多方法和属性来遍历html文档中节点和属性：
html_doc = """ <html><head><title>The Dormouse's story</title></head> <body> <p class="title"><b>The Dormouse's story</b></p> <p class="story">Once upon a time there were three little sisters; and their names were <a href="http://example.com/elsie" class="sister" id="link1">Elsie</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.</p> <p class="story">...</p> """ from bs4 import BeautifulSoup soup = BeautifulSoup(html_doc, 'html.parser')
对于上面的BeautifulSoup对象：
name, 标签名字： # tag = soup.find('a') # name = tag.name # 获取 # print(name) # tag.name = 'span' # 设置 # print(soup) # soup.head #拿到head标签
attrs, 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)
#tag['id'] #直接拿到属性
children, 所有子标签，返回生成器 contents，所有子标签，返回列表
parent，父节点
next_sibling,下一个兄弟节点
previous_sibling，上一个兄弟节点
# body = soup.find('body')
# v = body.children #
v = body.contents[0]
decendants, 所有的子孙节点
parents，所有父辈节点
next_siblings,下面所有兄弟节点
previous_siblings，上面所有兄弟节点
# body = soup.find('body')
# v = body.descendants
string: tag只有一个 NavigableString 类型子节点,那么这个tag可以使用 .string 得到子节点 (NavigableString,类似一个unicode字符窜，string拿到文本) strings: tag中包含多个字符串 [2] ,可以使用 .strings 来循环获取 stripped_strings: 输出的字符串中可能包含了很多空格或空行,使用 .stripped_strings 可以去除多余空白内容:
# tag = soup.find('a')
#tag.string
#for string in tag.strings:
# print(repr(string))
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() decompose(), 递归的删除所有的标签(不保留标签名) # body = soup.find('body') # body.decompose() 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()
decode,转换数据为字符串（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)
def decode(self, indent_level=None,eventual_encoding=DEFAULT_OUTPUT_ENCODING, formatter="minimal"): """Returns a Unicode representation of this tag and its contents. 默认encoding=‘utf-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)
def encode(self, encoding=DEFAULT_OUTPUT_ENCODING,indent_level=None, formatter="minimal",errors="xmlcharrefreplace"): 默认encoding=‘utf-8’
find_all() :搜索当前tag的所有tag子节点,获取匹配的所有标签,以列表形式返回 def find_all(self, name=None, attrs={}, recursive=True, text=None, limit=None, **kwargs): """Extracts a list of Tag objects that match the given criteria. You can specify the name of the Tag and any attributes you want the Tag to have. The value of a key-value pair in the 'attrs' map can be a string, a list of strings, a regular expression object, or a callable that takes a string and returns whether or not the string matches for some custom definition of 'matches'. The same is true of the tag name.""" name：查找所有名字为 name 的tag （name可以为字符串，正则表达式，列表，方法，True） #True匹配任意标签名 # tags = soup.find_all('a') # print(tags) # tags = soup.find_all('a',limit=1) # limit,只匹配一次；类似于find（） # print(tags) attrs参数：tag的属性值包含筛选条件 # tags = soup.find_all(name='a', attrs={'class': 'sister'}, recursive=True, text='Lacie') # # tags = soup.find(name='a', class_='sister', recursive=True, text='Lacie') soup.find_all("a", class_="sister") # print(tags) # ####### 列表 ####### # v = soup.find_all(name=['a','div']) # print(v) # v = soup.find_all(class_=['sister0', 'sister']) #class 为python关键字，所以加下划线 # 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
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)
get(),获取标签属性
def get(self, key, default=None):
return self.attrs.get(key, default)
# tag = soup.find('a')
# v = tag.get('id')
#类似于tag.attrs['id'] # print(v)
has_attr(),检查标签是否具有该属性 # tag = soup.find('a') # v = tag.has_attr('id') # print(v) def has_attr(self, key): return key in self.attrs
get_text(),获取标签内部文本内容 #类似string # tag = soup.find('a') # v = tag.get_text('id') # print(v)
index(),检查标签在某标签中的索引位置 def index(self, element): """ Find the index of a child by identity, not value. Avoids issues with tag.contents.index(element) getting the index of equal elements. """ for i, child in enumerate(self.contents): if child is element: return i raise ValueError("Tag.index: element not in tag") # tag = soup.find('body') # v = tag.index(tag.find('div')) # print(v)
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)
select,select_one, CSS选择器 （和css选择器一样） soup.select("title") soup.select("p nth-of-type(3)") #父元素中第三个p标签 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)
修改文档树标签的内容 # 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)
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)insert():指定位置插入标签
# tag = soup.find('body') # tag.insert(2, obj) # print(soup)insert_after(),insert_before() 在当前标签后面或前面插入
replace_with()当前标签替换为指定标签
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)wrap，将指定标签把当前标签包裹起来
# tag = soup.find('a')# v = tag.wrap(soup.find('p')) #a包裹p
# print(soup)unwrap，去掉当前标签，将保留其包裹的标签
# tag = soup.find('a')# v = tag.unwrap() # a包裹的标签
# print(soup)示例：使用BeautifulSoup模块解析当前网页，并提取出所有链接属性和文本内容，代码如下：
#coding:utf-8
import requestsfrom bs4 import BeautifulSoup #下载当前网页html文件 response = requests.get("https://www.cnblogs.com/silence-cho/p/9786069.html") print type(response.text) with open('python.html','w') as f: f.write(response.text.encode('utf-8')) with open('python.html','r') as f: html_file = f.read().decode('utf-8') #使用Beautiful模块 soup = BeautifulSoup(html_file,'lxml') a_tags = soup.find_all('a') for a_tag in a_tags: if a_tag.has_attr('href'): print a_tag.attrs['href'] text = soup.get_text().encode('gbk',errors='ignore') #使用get_text()方法，拿到所有文本 with open('text1.txt','w') as f: f.write(text) strings = soup.strings #使用strings属性，拿到所有文本 with open('string.txt','w') as f: for string in strings: #strings 为generator类型，包含拿到的所有文本 f.write(string.encode('gbk',errors='ignore'))
3，爬虫应用
登录抽屉
''' 自动登录抽屉热搜榜流程：先访问主页，获取cookie1，然后携带用户名，密码和cookie1访问登陆页面对cookie1授权，随后就能利用cookie1直接访问个人主页等。 注意真正起作用的是cookie1里面gpsd': '2c805bc26ead2dfcc09ef738249abf65，第二次进行登陆时对这个值进行了认证， 随后就能利用cookie1进行访问了，进行登录时也会返回cookie2，但cookie2并不起作用 ''' import requests from bs4 import BeautifulSoup #访问首页 response=requests.get( url="https://dig.chouti.com/", headers={"User-Agent":"Mozilla/5.0 (Windows NT 6.1; rv:62.0) Gecko/20100101 Firefox/62.0"} ) cookie_dict = response.cookies.get_dict() print cookie_dict #登录页面，发送post response2= requests.post( url="https://dig.chouti.com/login", data={ "oneMonth":"1", "password":"你自己的密码", "phone":"8618626429847", }, headers={"User-Agent":"Mozilla/5.0 (Windows NT 6.1; rv:62.0) Gecko/20100101 Firefox/62.0"}, cookies=cookie_dict, ) #携带cookie，访问首页，显示为登录状态 response3= requests.get( url="https://dig.chouti.com/", headers={"User-Agent":"Mozilla/5.0 (Windows NT 6.1; rv:62.0) Gecko/20100101 Firefox/62.0"}, cookies = cookie_dict ) #携带cookie，进行点赞，返回推送成功 response4 = requests.post( url="https://dig.chouti.com/link/vote?linksId=22650731", headers={"User-Agent":"Mozilla/5.0 (Windows NT 6.1; rv:62.0) Gecko/20100101 Firefox/62.0"}, cookies = cookie_dict ) print response4.text #{"result":{"code":"9999", "message":"推荐成功", "data":{"jid":"cdu_53961215992","likedTime":"1539697099953000","lvCount":"13","nick":"silence624","uvCount":"1","voteTime":"小于1分钟前"}}}
登陆github
import requests from bs4 import BeautifulSoup response1 = requests.get( url="https://github.com/login", #url为https://github.com/时拿到的cookie不行 headers={"User-Agent":"Mozilla/5.0 (Windows NT 6.1; rv:62.0) Gecko/20100101 Firefox/62.0"}, ) cookie_dict = response1.cookies.get_dict() #拿到cookie print cookie_dict soup = BeautifulSoup(response1.text,features='html.parser') tag = soup.find(name='input',attrs={"name":"authenticity_token"}) authenticity_token = tag.attrs.get('value') # 从前端页面拿到跨站伪造请求token值 print authenticity_token response = requests.post( url='https://github.com/session', data={ "authenticity_token":authenticity_token, "commit":"Sign+in", "login":"xxx", "password":"xxx", "utf8":"" }, headers={"User-Agent":"Mozilla/5.0 (Windows NT 6.1; rv:62.0) Gecko/20100101 Firefox/62.0"}, cookies = cookie_dict, ) # print response.text c2=response.cookies.get_dict() cookie_dict.update(c2) #自动登录，对cookie值进行更新 r = requests.get(url="https://github.com/settings/repositories",cookies=cookie_dict) #利用更新后的cookie保持会话，拿到仓库名 soup2 = BeautifulSoup(r.text,features='html.parser') tags = soup2.find_all(name='a',attrs={'class':'mr-1'}) for item in tags: print item.get_text()
参考博客：http://www.cnblogs.com/wupeiqi/articles/6283017.html