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  • python BeautifulSoup库详解

    BeautifulSoup

    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

    官方文档链接,相同效果的库还有pyquery模块,详见此

    解析器

    对网页进行析取时,若未规定解析器,此时使用的是python内部默认的解析器“html.parser”。

    解析器是什么呢? BeautifulSoup做的工作就是对html标签进行解释和分类,不同的解析器对相同html标签会做出不同解释。

    举个官方文档上的例子:

    BeautifulSoup("<a></p>", "lxml")
    # <html><body><a></a></body></html>
    BeautifulSoup("<a></p>", "html5lib")
    # <html><head></head><body><a><p></p></a></body></html>
    BeautifulSoup("<a></p>", "html.parser")
    # <a></a>

    官方文档上多次提到推荐使用"lxml"和"html5lib"解析器,因为默认的"html.parser"自动补全标签的功能很差,经常会出问题。

    Parser Typical usage Advantages Disadvantages
    Python’s html.parser BeautifulSoup(markup,"html.parser")
    • Batteries included
    • Decent speed
    • Lenient (as of Python 2.7.3 and 3.2.)
    • Not very lenient (before Python 2.7.3 or 3.2.2)
    lxml’s HTML parser BeautifulSoup(markup,"lxml")
    • Very fast
    • Lenient
    • External C dependency
    lxml’s XML parser BeautifulSoup(markup,"lxml-xml") BeautifulSoup(markup,"xml")
    • Very fast
    • The only currently supported XML parser
    • External C dependency
    html5lib BeautifulSoup(markup,"html5lib")
    • Extremely lenient
    • Parses pages the same way a web browser does
    • Creates valid HTML5
    • Very slow
    • External Python dependency

    可以看出,“lxml”的解析速度非常快,对错误也有一定的容忍性。“html5lib”对错误的容忍度是最高的,而且一定能解析出合法的html5代码,但速度很慢。

    我们在实际爬取网站的时候,原网页的编码方式不统一,其中有一句乱码,用“html.parser”和“lxml”都解析到乱码的那句,后面的所有标签都被忽略了。而“html5lib”能够完美解决这个问题。

    安装及基本使用

    安装:

    #安装 Beautiful Soup
    pip install beautifulsoup4
    
    #安装解析器
    Beautiful Soup支持Python标准库中的HTML解析器,还支持一些第三方的解析器,其中一个是 lxml .根据操作系统不同,可以选择下列方法来安装lxml:
    
    $ apt-get install Python-lxml
    
    $ easy_install lxml
    
    $ pip install lxml
    
    另一个可供选择的解析器是纯Python实现的 html5lib , html5lib的解析方式与浏览器相同,可以选择下列方法来安装html5lib:
    
    $ apt-get install Python-html5lib
    
    $ easy_install html5lib
    
    $ pip install html5lib
    

    简单使用:

    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>
    """
    
    #基本使用:容错处理,文档的容错能力指的是在html代码不完整的情况下,使用该模块可以识别该错误。使用BeautifulSoup解析上述代码,能够得到一个 BeautifulSoup 的对象,并能按照标准的缩进格式的结构输出
    from bs4 import BeautifulSoup
    soup=BeautifulSoup(html_doc,'lxml') #具有容错功能
    res=soup.prettify() #处理好缩进,结构化显示
    print(res)
    

    各种api详解

    • 1. name,标签名称
    import requests
    from bs4 import BeautifulSoup
    
    ret = requests.get(url="https://www.autohome.com.cn/news/")
    soup = BeautifulSoup(ret.text, 'lxml')
    print(type(soup))
    # <class 'bs4.BeautifulSoup'>
    tag = soup.find('a')
    name = tag.name  # 获取
    print("=" * 120)
    print(tag)
    # <a class="orangelink" href="//www.autohome.com.cn/beijing/cheshi/" target="_blank"><i class="topbar-icon topbar-icon16 topbar-icon16-building"></i>进入北京车市</a>
    print(type(tag))
    # <class 'bs4.element.Tag'>
    print("=" * 120)
    
    print(name)  # a
    tag.name = 'span'  # 设置,将标签设置为span
    print(soup)  # a标签已经被修改成了span标签
    # <html>....<span class="orangelink" href="//www.autohome.com.cn/beijing/cheshi/" target="_blank"><i class="topbar-icon topbar-icon16 topbar-icon16-building"></i>进入北京车市</span>....</html>
    

      soup类型为BeautifulSoup,tag类型为bs4.element.tag,下面是tag的一些属性

    • 2. attr,标签属性
    tag = soup.find('a')
    attrs = tag.attrs  # 获取
    print(tag)
    # <a class="orangelink" href="//www.autohome.com.cn/beijing/cheshi/" target="_blank">
    print(attrs)
    # {'target': '_blank', 'href': '//www.autohome.com.cn/beijing/cheshi/', 'class': ['orangelink']}
    tag.attrs = {'ik': 123}  # 设置
    tag.attrs['id'] = 'iiiii'  # 添加
    print(soup.find("a"))
    # <a id="iiiii" ik="123">
    • 2.5 contents  获取标签内所有内容
    body = soup.find('body')
    v = body.contents
    • 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
    • 4.5 parent 父节点
    body = soup.find('a')
    v = body.parent
    
    • 4.6 parents 获取所有祖先节点
    body = soup.find('a')
    v = body.parents
    print(v)
    # <generator object parents at 0x000001E1225C4E60>
    是迭代器,要遍历输出
    

      

    • 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. 兄弟节点,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(str)
    # 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)
    

       

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  • 原文地址:https://www.cnblogs.com/wlx97e6/p/9960272.html
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