.什么是爬虫
爬虫，即网络爬虫，大家可以理解为在网络上爬行的一直蜘蛛，互联网就比作一张大网，而爬虫便是在这张网上爬来爬去的蜘蛛咯，如果它遇到资源，那么它就会抓取下来。想抓取什么？这个由你来控制它咯。
比如它在抓取一个网页，在这个网中他发现了一条道路，其实就是指向网页的超链接，那么它就可以爬到另一张网上来获取数据。这样，整个连在一起的大网对这之蜘蛛来说触手可及，分分钟爬下来不是事儿。
2.浏览网页的过程
在用户浏览网页的过程中，我们可能会看到许多好看的图片，比如 http://image.baidu.com/ ，我们会看到几张的图片以及百度搜索框，这个过程其实就是用户输入网址之后，经过DNS服务器，找到服务器主机，向服务器发出一个请求，服务器经过解析之后，发送给用户的浏览器 HTML、JS、CSS 等文件，浏览器解析出来，用户便可以看到形形色色的图片了。
因此，用户看到的网页实质是由 HTML 代码构成的，爬虫爬来的便是这些内容，通过分析和过滤这些 HTML 代码，实现对图片、文字等资源的获取。
3.URL的含义
URL，即统一资源定位符，也就是我们说的网址，统一资源定位符是对可以从互联网上得到的资源的位置和访问方法的一种简洁的表示，是互联网上标准资源的地址。互联网上的每个文件都有一个唯一的URL，它包含的信息指出文件的位置以及浏览器应该怎么处理它。
URL的格式由三部分组成：
①第一部分是协议(或称为服务方式)。
②第二部分是存有该资源的主机IP地址(有时也包括端口号)。
③第三部分是主机资源的具体地址，如目录和文件名等。
爬虫爬取数据时必须要有一个目标的URL才可以获取数据，因此，它是爬虫获取数据的基本依据
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]> """
参数示例
复制代码 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. 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)
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）
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
oup.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/