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NAVIGATION
* index
* Beautiful Soup 4.9.0 documentation »
* Beautiful Soup Documentation
BEAUTIFUL SOUP DOCUMENTATION¶
Beautiful Soup is a Python library for pulling data out of HTML and XML files.
It works with your favorite parser to provide idiomatic ways of navigating,
searching, and modifying the parse tree. It commonly saves programmers hours or
days of work.
These instructions illustrate all major features of Beautiful Soup 4, with
examples. I show you what the library is good for, how it works, how to use it,
how to make it do what you want, and what to do when it violates your
expectations.
This document covers Beautiful Soup version 4.11.0. The examples in this
documentation were written for Python 3.8.
You might be looking for the documentation for Beautiful Soup 3. If so, you
should know that Beautiful Soup 3 is no longer being developed and that all
support for it was dropped on December 31, 2020. If you want to learn about the
differences between Beautiful Soup 3 and Beautiful Soup 4, see Porting code to
BS4.
This documentation has been translated into other languages by Beautiful Soup
users:
* 这篇文档当然还有中文版.
* このページは日本語で利用できます(外部リンク)
* 이 문서는 한국어 번역도 가능합니다.
* Este documento também está disponível em Português do Brasil.
* Эта документация доступна на русском языке.
GETTING HELP¶
If you have questions about Beautiful Soup, or run into problems, send mail to
the discussion group. If your problem involves parsing an HTML document, be sure
to mention what the diagnose() function says about that document.
QUICK START¶
Here’s an HTML document I’ll be using as an example throughout this document.
It’s part of a story from Alice in Wonderland:
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>
"""
Running the “three sisters” document through Beautiful Soup gives us a
BeautifulSoup object, which represents the document as a nested data structure:
from bs4 import BeautifulSoup
soup = BeautifulSoup(html_doc, 'html.parser')
print(soup.prettify())
# <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 class="sister" href="http://example.com/elsie" id="link1">
# Elsie
# </a>
# ,
# <a class="sister" href="http://example.com/lacie" id="link2">
# Lacie
# </a>
# and
# <a class="sister" href="http://example.com/tillie" id="link3">
# Tillie
# </a>
# ; and they lived at the bottom of a well.
# </p>
# <p class="story">
# ...
# </p>
# </body>
# </html>
Here are some simple ways to navigate that data structure:
soup.title
# <title>The Dormouse's story</title>
soup.title.name
# u'title'
soup.title.string
# u'The Dormouse's story'
soup.title.parent.name
# u'head'
soup.p
# <p class="title"><b>The Dormouse's story</b></p>
soup.p['class']
# u'title'
soup.a
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
soup.find_all('a')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.find(id="link3")
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>
One common task is extracting all the URLs found within a page’s <a> tags:
for link in soup.find_all('a'):
print(link.get('href'))
# http://example.com/elsie
# http://example.com/lacie
# http://example.com/tillie
Another common task is extracting all the text from a page:
print(soup.get_text())
# The Dormouse's story
#
# The Dormouse's story
#
# Once upon a time there were three little sisters; and their names were
# Elsie,
# Lacie and
# Tillie;
# and they lived at the bottom of a well.
#
# ...
Does this look like what you need? If so, read on.
INSTALLING BEAUTIFUL SOUP¶
If you’re using a recent version of Debian or Ubuntu Linux, you can install
Beautiful Soup with the system package manager:
$ apt-get install python3-bs4
Beautiful Soup 4 is published through PyPi, so if you can’t install it with the
system packager, you can install it with easy_install or pip. The package name
is beautifulsoup4. Make sure you use the right version of pip or easy_install
for your Python version (these may be named pip3 and easy_install3
respectively).
$ easy_install beautifulsoup4
$ pip install beautifulsoup4
(The BeautifulSoup package is not what you want. That’s the previous major
release, Beautiful Soup 3. Lots of software uses BS3, so it’s still available,
but if you’re writing new code you should install beautifulsoup4.)
If you don’t have easy_install or pip installed, you can download the Beautiful
Soup 4 source tarball and install it with setup.py.
$ python setup.py install
If all else fails, the license for Beautiful Soup allows you to package the
entire library with your application. You can download the tarball, copy its bs4
directory into your application’s codebase, and use Beautiful Soup without
installing it at all.
I use Python 3.8 to develop Beautiful Soup, but it should work with other recent
versions.
INSTALLING A PARSER¶
Beautiful Soup supports the HTML parser included in Python’s standard library,
but it also supports a number of third-party Python parsers. One is the lxml
parser. Depending on your setup, you might install lxml with one of these
commands:
$ apt-get install python-lxml
$ easy_install lxml
$ pip install lxml
Another alternative is the pure-Python html5lib parser, which parses HTML the
way a web browser does. Depending on your setup, you might install html5lib with
one of these commands:
$ apt-get install python-html5lib
$ easy_install html5lib
$ pip install html5lib
This table summarizes the advantages and disadvantages of each parser library:
Parser
Typical usage
Advantages
Disadvantages
Python’s html.parser
BeautifulSoup(markup, "html.parser")
* Batteries included
* Decent speed
* Lenient (As of Python 3.2)
* Not as fast as lxml, less lenient than html5lib.
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
If you can, I recommend you install and use lxml for speed. If you’re using a
very old version of Python – earlier than 3.2.2 – it’s essential that you
install lxml or html5lib. Python’s built-in HTML parser is just not very good in
those old versions.
Note that if a document is invalid, different parsers will generate different
Beautiful Soup trees for it. See Differences between parsers for details.
MAKING THE SOUP¶
To parse a document, pass it into the BeautifulSoup constructor. You can pass in
a string or an open filehandle:
from bs4 import BeautifulSoup
with open("index.html") as fp:
soup = BeautifulSoup(fp, 'html.parser')
soup = BeautifulSoup("<html>a web page</html>", 'html.parser')
First, the document is converted to Unicode, and HTML entities are converted to
Unicode characters:
print(BeautifulSoup("<html><head></head><body>Sacré bleu!</body></html>", "html.parser"))
# <html><head></head><body>Sacré bleu!</body></html>
Beautiful Soup then parses the document using the best available parser. It will
use an HTML parser unless you specifically tell it to use an XML parser. (See
Parsing XML.)
KINDS OF OBJECTS¶
Beautiful Soup transforms a complex HTML document into a complex tree of Python
objects. But you’ll only ever have to deal with about four kinds of objects:
Tag, NavigableString, BeautifulSoup, and Comment.
TAG¶
A Tag object corresponds to an XML or HTML tag in the original document:
soup = BeautifulSoup('<b class="boldest">Extremely bold</b>', 'html.parser')
tag = soup.b
type(tag)
# <class 'bs4.element.Tag'>
Tags have a lot of attributes and methods, and I’ll cover most of them in
Navigating the tree and Searching the tree. For now, the most important features
of a tag are its name and attributes.
NAME¶
Every tag has a name, accessible as .name:
tag.name
# 'b'
If you change a tag’s name, the change will be reflected in any HTML markup
generated by Beautiful Soup:
tag.name = "blockquote"
tag
# <blockquote class="boldest">Extremely bold</blockquote>
ATTRIBUTES¶
A tag may have any number of attributes. The tag <b id="boldest"> has an
attribute “id” whose value is “boldest”. You can access a tag’s attributes by
treating the tag like a dictionary:
tag = BeautifulSoup('<b id="boldest">bold</b>', 'html.parser').b
tag['id']
# 'boldest'
You can access that dictionary directly as .attrs:
tag.attrs
# {'id': 'boldest'}
You can add, remove, and modify a tag’s attributes. Again, this is done by
treating the tag as a dictionary:
tag['id'] = 'verybold'
tag['another-attribute'] = 1
tag
# <b another-attribute="1" id="verybold"></b>
del tag['id']
del tag['another-attribute']
tag
# <b>bold</b>
tag['id']
# KeyError: 'id'
tag.get('id')
# None
MULTI-VALUED ATTRIBUTES¶
HTML 4 defines a few attributes that can have multiple values. HTML 5 removes a
couple of them, but defines a few more. The most common multi-valued attribute
is class (that is, a tag can have more than one CSS class). Others include rel,
rev, accept-charset, headers, and accesskey. Beautiful Soup presents the
value(s) of a multi-valued attribute as a list:
css_soup = BeautifulSoup('<p class="body"></p>', 'html.parser')
css_soup.p['class']
# ['body']
css_soup = BeautifulSoup('<p class="body strikeout"></p>', 'html.parser')
css_soup.p['class']
# ['body', 'strikeout']
If an attribute looks like it has more than one value, but it’s not a
multi-valued attribute as defined by any version of the HTML standard, Beautiful
Soup will leave the attribute alone:
id_soup = BeautifulSoup('<p id="my id"></p>', 'html.parser')
id_soup.p['id']
# 'my id'
When you turn a tag back into a string, multiple attribute values are
consolidated:
rel_soup = BeautifulSoup('<p>Back to the <a rel="index">homepage</a></p>', 'html.parser')
rel_soup.a['rel']
# ['index']
rel_soup.a['rel'] = ['index', 'contents']
print(rel_soup.p)
# <p>Back to the <a rel="index contents">homepage</a></p>
You can disable this by passing multi_valued_attributes=None as a keyword
argument into the BeautifulSoup constructor:
no_list_soup = BeautifulSoup('<p class="body strikeout"></p>', 'html.parser', multi_valued_attributes=None)
no_list_soup.p['class']
# 'body strikeout'
You can use get_attribute_list to get a value that’s always a list, whether or
not it’s a multi-valued atribute:
id_soup.p.get_attribute_list('id')
# ["my id"]
If you parse a document as XML, there are no multi-valued attributes:
xml_soup = BeautifulSoup('<p class="body strikeout"></p>', 'xml')
xml_soup.p['class']
# 'body strikeout'
Again, you can configure this using the multi_valued_attributes argument:
class_is_multi= { '*' : 'class'}
xml_soup = BeautifulSoup('<p class="body strikeout"></p>', 'xml', multi_valued_attributes=class_is_multi)
xml_soup.p['class']
# ['body', 'strikeout']
You probably won’t need to do this, but if you do, use the defaults as a guide.
They implement the rules described in the HTML specification:
from bs4.builder import builder_registry
builder_registry.lookup('html').DEFAULT_CDATA_LIST_ATTRIBUTES
NAVIGABLESTRING¶
A string corresponds to a bit of text within a tag. Beautiful Soup uses the
NavigableString class to contain these bits of text:
soup = BeautifulSoup('<b class="boldest">Extremely bold</b>', 'html.parser')
tag = soup.b
tag.string
# 'Extremely bold'
type(tag.string)
# <class 'bs4.element.NavigableString'>
A NavigableString is just like a Python Unicode string, except that it also
supports some of the features described in Navigating the tree and Searching the
tree. You can convert a NavigableString to a Unicode string with str:
unicode_string = str(tag.string)
unicode_string
# 'Extremely bold'
type(unicode_string)
# <type 'str'>
You can’t edit a string in place, but you can replace one string with another,
using replace_with():
tag.string.replace_with("No longer bold")
tag
# <b class="boldest">No longer bold</b>
NavigableString supports most of the features described in Navigating the tree
and Searching the tree, but not all of them. In particular, since a string can’t
contain anything (the way a tag may contain a string or another tag), strings
don’t support the .contents or .string attributes, or the find() method.
If you want to use a NavigableString outside of Beautiful Soup, you should call
unicode() on it to turn it into a normal Python Unicode string. If you don’t,
your string will carry around a reference to the entire Beautiful Soup parse
tree, even when you’re done using Beautiful Soup. This is a big waste of memory.
BEAUTIFULSOUP¶
The BeautifulSoup object represents the parsed document as a whole. For most
purposes, you can treat it as a Tag object. This means it supports most of the
methods described in Navigating the tree and Searching the tree.
You can also pass a BeautifulSoup object into one of the methods defined in
Modifying the tree, just as you would a Tag. This lets you do things like
combine two parsed documents:
doc = BeautifulSoup("<document><content/>INSERT FOOTER HERE</document", "xml")
footer = BeautifulSoup("<footer>Here's the footer</footer>", "xml")
doc.find(text="INSERT FOOTER HERE").replace_with(footer)
# 'INSERT FOOTER HERE'
print(doc)
# <?xml version="1.0" encoding="utf-8"?>
# <document><content/><footer>Here's the footer</footer></document>
Since the BeautifulSoup object doesn’t correspond to an actual HTML or XML tag,
it has no name and no attributes. But sometimes it’s useful to look at its
.name, so it’s been given the special .name “[document]”:
soup.name
# '[document]'
COMMENTS AND OTHER SPECIAL STRINGS¶
Tag, NavigableString, and BeautifulSoup cover almost everything you’ll see in an
HTML or XML file, but there are a few leftover bits. The main one you’ll
probably encounter is the comment:
markup = "<b><!--Hey, buddy. Want to buy a used parser?--></b>"
soup = BeautifulSoup(markup, 'html.parser')
comment = soup.b.string
type(comment)
# <class 'bs4.element.Comment'>
The Comment object is just a special type of NavigableString:
comment
# 'Hey, buddy. Want to buy a used parser'
But when it appears as part of an HTML document, a Comment is displayed with
special formatting:
print(soup.b.prettify())
# <b>
# <!--Hey, buddy. Want to buy a used parser?-->
# </b>
Beautiful Soup also defines classes called Stylesheet, Script, and
TemplateString, for embedded CSS stylesheets (any strings found inside a <style>
tag), embedded Javascript (any strings found in a <script> tag), and HTML
templates (any strings inside a <template> tag). These classes work exactly the
same way as NavigableString; their only purpose is to make it easier to pick out
the main body of the page, by ignoring strings that represent something else.
(These classes are new in Beautiful Soup 4.9.0, and the html5lib parser doesn’t
use them.)
Beautiful Soup defines classes for anything else that might show up in an XML
document: CData, ProcessingInstruction, Declaration, and Doctype. Like Comment,
these classes are subclasses of NavigableString that add something extra to the
string. Here’s an example that replaces the comment with a CDATA block:
from bs4 import CData
cdata = CData("A CDATA block")
comment.replace_with(cdata)
print(soup.b.prettify())
# <b>
# <![CDATA[A CDATA block]]>
# </b>
NAVIGATING THE TREE¶
Here’s the “Three sisters” HTML document again:
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')
I’ll use this as an example to show you how to move from one part of a document
to another.
GOING DOWN¶
Tags may contain strings and other tags. These elements are the tag’s children.
Beautiful Soup provides a lot of different attributes for navigating and
iterating over a tag’s children.
Note that Beautiful Soup strings don’t support any of these attributes, because
a string can’t have children.
NAVIGATING USING TAG NAMES¶
The simplest way to navigate the parse tree is to say the name of the tag you
want. If you want the <head> tag, just say soup.head:
soup.head
# <head><title>The Dormouse's story</title></head>
soup.title
# <title>The Dormouse's story</title>
You can do use this trick again and again to zoom in on a certain part of the
parse tree. This code gets the first <b> tag beneath the <body> tag:
soup.body.b
# <b>The Dormouse's story</b>
Using a tag name as an attribute will give you only the first tag by that name:
soup.a
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
If you need to get all the <a> tags, or anything more complicated than the first
tag with a certain name, you’ll need to use one of the methods described in
Searching the tree, such as find_all():
soup.find_all('a')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
.CONTENTS AND .CHILDREN¶
A tag’s children are available in a list called .contents:
head_tag = soup.head
head_tag
# <head><title>The Dormouse's story</title></head>
head_tag.contents
# [<title>The Dormouse's story</title>]
title_tag = head_tag.contents[0]
title_tag
# <title>The Dormouse's story</title>
title_tag.contents
# ['The Dormouse's story']
The BeautifulSoup object itself has children. In this case, the <html> tag is
the child of the BeautifulSoup object.:
len(soup.contents)
# 1
soup.contents[0].name
# 'html'
A string does not have .contents, because it can’t contain anything:
text = title_tag.contents[0]
text.contents
# AttributeError: 'NavigableString' object has no attribute 'contents'
Instead of getting them as a list, you can iterate over a tag’s children using
the .children generator:
for child in title_tag.children:
print(child)
# The Dormouse's story
If you want to modify a tag’s children, use the methods described in Modifying
the tree. Don’t modify the the .contents list directly: that can lead to
problems that are subtle and difficult to spot.
.DESCENDANTS¶
The .contents and .children attributes only consider a tag’s direct children.
For instance, the <head> tag has a single direct child–the <title> tag:
head_tag.contents
# [<title>The Dormouse's story</title>]
But the <title> tag itself has a child: the string “The Dormouse’s story”.
There’s a sense in which that string is also a child of the <head> tag. The
.descendants attribute lets you iterate over all of a tag’s children,
recursively: its direct children, the children of its direct children, and so
on:
for child in head_tag.descendants:
print(child)
# <title>The Dormouse's story</title>
# The Dormouse's story
The <head> tag has only one child, but it has two descendants: the <title> tag
and the <title> tag’s child. The BeautifulSoup object only has one direct child
(the <html> tag), but it has a whole lot of descendants:
len(list(soup.children))
# 1
len(list(soup.descendants))
# 26
.STRING¶
If a tag has only one child, and that child is a NavigableString, the child is
made available as .string:
title_tag.string
# 'The Dormouse's story'
If a tag’s only child is another tag, and that tag has a .string, then the
parent tag is considered to have the same .string as its child:
head_tag.contents
# [<title>The Dormouse's story</title>]
head_tag.string
# 'The Dormouse's story'
If a tag contains more than one thing, then it’s not clear what .string should
refer to, so .string is defined to be None:
print(soup.html.string)
# None
.STRINGS AND STRIPPED_STRINGS¶
If there’s more than one thing inside a tag, you can still look at just the
strings. Use the .strings generator:
for string in soup.strings:
print(repr(string))
'\n'
# "The Dormouse's story"
# '\n'
# '\n'
# "The Dormouse's story"
# '\n'
# 'Once upon a time there were three little sisters; and their names were\n'
# 'Elsie'
# ',\n'
# 'Lacie'
# ' and\n'
# 'Tillie'
# ';\nand they lived at the bottom of a well.'
# '\n'
# '...'
# '\n'
These strings tend to have a lot of extra whitespace, which you can remove by
using the .stripped_strings generator instead:
for string in soup.stripped_strings:
print(repr(string))
# "The Dormouse's story"
# "The Dormouse's story"
# 'Once upon a time there were three little sisters; and their names were'
# 'Elsie'
# ','
# 'Lacie'
# 'and'
# 'Tillie'
# ';\n and they lived at the bottom of a well.'
# '...'
Here, strings consisting entirely of whitespace are ignored, and whitespace at
the beginning and end of strings is removed.
GOING UP¶
Continuing the “family tree” analogy, every tag and every string has a parent:
the tag that contains it.
.PARENT¶
You can access an element’s parent with the .parent attribute. In the example
“three sisters” document, the <head> tag is the parent of the <title> tag:
title_tag = soup.title
title_tag
# <title>The Dormouse's story</title>
title_tag.parent
# <head><title>The Dormouse's story</title></head>
The title string itself has a parent: the <title> tag that contains it:
title_tag.string.parent
# <title>The Dormouse's story</title>
The parent of a top-level tag like <html> is the BeautifulSoup object itself:
html_tag = soup.html
type(html_tag.parent)
# <class 'bs4.BeautifulSoup'>
And the .parent of a BeautifulSoup object is defined as None:
print(soup.parent)
# None
.PARENTS¶
You can iterate over all of an element’s parents with .parents. This example
uses .parents to travel from an <a> tag buried deep within the document, to the
very top of the document:
link = soup.a
link
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
for parent in link.parents:
print(parent.name)
# p
# body
# html
# [document]
GOING SIDEWAYS¶
Consider a simple document like this:
sibling_soup = BeautifulSoup("<a><b>text1</b><c>text2</c></a>", 'html.parser')
print(sibling_soup.prettify())
# <a>
# <b>
# text1
# </b>
# <c>
# text2
# </c>
# </a>
The <b> tag and the <c> tag are at the same level: they’re both direct children
of the same tag. We call them siblings. When a document is pretty-printed,
siblings show up at the same indentation level. You can also use this
relationship in the code you write.
.NEXT_SIBLING AND .PREVIOUS_SIBLING¶
You can use .next_sibling and .previous_sibling to navigate between page
elements that are on the same level of the parse tree:
sibling_soup.b.next_sibling
# <c>text2</c>
sibling_soup.c.previous_sibling
# <b>text1</b>
The <b> tag has a .next_sibling, but no .previous_sibling, because there’s
nothing before the <b> tag on the same level of the tree. For the same reason,
the <c> tag has a .previous_sibling but no .next_sibling:
print(sibling_soup.b.previous_sibling)
# None
print(sibling_soup.c.next_sibling)
# None
The strings “text1” and “text2” are not siblings, because they don’t have the
same parent:
sibling_soup.b.string
# 'text1'
print(sibling_soup.b.string.next_sibling)
# None
In real documents, the .next_sibling or .previous_sibling of a tag will usually
be a string containing whitespace. Going back to the “three sisters” document:
# <a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>
# <a href="http://example.com/lacie" class="sister" id="link2">Lacie</a>
# <a href="http://example.com/tillie" class="sister" id="link3">Tillie</a>
You might think that the .next_sibling of the first <a> tag would be the second
<a> tag. But actually, it’s a string: the comma and newline that separate the
first <a> tag from the second:
link = soup.a
link
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
link.next_sibling
# ',\n '
The second <a> tag is actually the .next_sibling of the comma:
link.next_sibling.next_sibling
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>
.NEXT_SIBLINGS AND .PREVIOUS_SIBLINGS¶
You can iterate over a tag’s siblings with .next_siblings or .previous_siblings:
for sibling in soup.a.next_siblings:
print(repr(sibling))
# ',\n'
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>
# ' and\n'
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>
# '; and they lived at the bottom of a well.'
for sibling in soup.find(id="link3").previous_siblings:
print(repr(sibling))
# ' and\n'
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>
# ',\n'
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
# 'Once upon a time there were three little sisters; and their names were\n'
GOING BACK AND FORTH¶
Take a look at the beginning of the “three sisters” document:
# <html><head><title>The Dormouse's story</title></head>
# <p class="title"><b>The Dormouse's story</b></p>
An HTML parser takes this string of characters and turns it into a series of
events: “open an <html> tag”, “open a <head> tag”, “open a <title> tag”, “add a
string”, “close the <title> tag”, “open a <p> tag”, and so on. Beautiful Soup
offers tools for reconstructing the initial parse of the document.
.NEXT_ELEMENT AND .PREVIOUS_ELEMENT¶
The .next_element attribute of a string or tag points to whatever was parsed
immediately afterwards. It might be the same as .next_sibling, but it’s usually
drastically different.
Here’s the final <a> tag in the “three sisters” document. Its .next_sibling is a
string: the conclusion of the sentence that was interrupted by the start of the
<a> tag.:
last_a_tag = soup.find("a", id="link3")
last_a_tag
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>
last_a_tag.next_sibling
# ';\nand they lived at the bottom of a well.'
But the .next_element of that <a> tag, the thing that was parsed immediately
after the <a> tag, is not the rest of that sentence: it’s the word “Tillie”:
last_a_tag.next_element
# 'Tillie'
That’s because in the original markup, the word “Tillie” appeared before that
semicolon. The parser encountered an <a> tag, then the word “Tillie”, then the
closing </a> tag, then the semicolon and rest of the sentence. The semicolon is
on the same level as the <a> tag, but the word “Tillie” was encountered first.
The .previous_element attribute is the exact opposite of .next_element. It
points to whatever element was parsed immediately before this one:
last_a_tag.previous_element
# ' and\n'
last_a_tag.previous_element.next_element
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>
.NEXT_ELEMENTS AND .PREVIOUS_ELEMENTS¶
You should get the idea by now. You can use these iterators to move forward or
backward in the document as it was parsed:
for element in last_a_tag.next_elements:
print(repr(element))
# 'Tillie'
# ';\nand they lived at the bottom of a well.'
# '\n'
# <p class="story">...</p>
# '...'
# '\n'
SEARCHING THE TREE¶
Beautiful Soup defines a lot of methods for searching the parse tree, but
they’re all very similar. I’m going to spend a lot of time explaining the two
most popular methods: find() and find_all(). The other methods take almost
exactly the same arguments, so I’ll just cover them briefly.
Once again, I’ll be using the “three sisters” document as an example:
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')
By passing in a filter to an argument like find_all(), you can zoom in on the
parts of the document you’re interested in.
KINDS OF FILTERS¶
Before talking in detail about find_all() and similar methods, I want to show
examples of different filters you can pass into these methods. These filters
show up again and again, throughout the search API. You can use them to filter
based on a tag’s name, on its attributes, on the text of a string, or on some
combination of these.
A STRING¶
The simplest filter is a string. Pass a string to a search method and Beautiful
Soup will perform a match against that exact string. This code finds all the <b>
tags in the document:
soup.find_all('b')
# [<b>The Dormouse's story</b>]
If you pass in a byte string, Beautiful Soup will assume the string is encoded
as UTF-8. You can avoid this by passing in a Unicode string instead.
A REGULAR EXPRESSION¶
If you pass in a regular expression object, Beautiful Soup will filter against
that regular expression using its search() method. This code finds all the tags
whose names start with the letter “b”; in this case, the <body> tag and the <b>
tag:
import re
for tag in soup.find_all(re.compile("^b")):
print(tag.name)
# body
# b
This code finds all the tags whose names contain the letter ‘t’:
for tag in soup.find_all(re.compile("t")):
print(tag.name)
# html
# title
A LIST¶
If you pass in a list, Beautiful Soup will allow a string match against any item
in that list. This code finds all the <a> tags and all the <b> tags:
soup.find_all(["a", "b"])
# [<b>The Dormouse's story</b>,
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
TRUE¶
The value True matches everything it can. This code finds all the tags in the
document, but none of the text strings:
for tag in soup.find_all(True):
print(tag.name)
# html
# head
# title
# body
# p
# b
# p
# a
# a
# a
# p
A FUNCTION¶
If none of the other matches work for you, define a function that takes an
element as its only argument. The function should return True if the argument
matches, and False otherwise.
Here’s a function that returns True if a tag defines the “class” attribute but
doesn’t define the “id” attribute:
def has_class_but_no_id(tag):
return tag.has_attr('class') and not tag.has_attr('id')
Pass this function into find_all() and you’ll pick up all the <p> tags:
soup.find_all(has_class_but_no_id)
# [<p class="title"><b>The Dormouse's story</b></p>,
# <p class="story">Once upon a time there were…bottom of a well.</p>,
# <p class="story">...</p>]
This function only picks up the <p> tags. It doesn’t pick up the <a> tags,
because those tags define both “class” and “id”. It doesn’t pick up tags like
<html> and <title>, because those tags don’t define “class”.
If you pass in a function to filter on a specific attribute like href, the
argument passed into the function will be the attribute value, not the whole
tag. Here’s a function that finds all a tags whose href attribute does not match
a regular expression:
import re
def not_lacie(href):
return href and not re.compile("lacie").search(href)
soup.find_all(href=not_lacie)
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
The function can be as complicated as you need it to be. Here’s a function that
returns True if a tag is surrounded by string objects:
from bs4 import NavigableString
def surrounded_by_strings(tag):
return (isinstance(tag.next_element, NavigableString)
and isinstance(tag.previous_element, NavigableString))
for tag in soup.find_all(surrounded_by_strings):
print(tag.name)
# body
# p
# a
# a
# a
# p
Now we’re ready to look at the search methods in detail.
FIND_ALL()¶
Method signature: find_all(name, attrs, recursive, string, limit, **kwargs)
The find_all() method looks through a tag’s descendants and retrieves all
descendants that match your filters. I gave several examples in Kinds of
filters, but here are a few more:
soup.find_all("title")
# [<title>The Dormouse's story</title>]
soup.find_all("p", "title")
# [<p class="title"><b>The Dormouse's story</b></p>]
soup.find_all("a")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.find_all(id="link2")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
import re
soup.find(string=re.compile("sisters"))
# 'Once upon a time there were three little sisters; and their names were\n'
Some of these should look familiar, but others are new. What does it mean to
pass in a value for string, or id? Why does find_all("p", "title") find a <p>
tag with the CSS class “title”? Let’s look at the arguments to find_all().
THE NAME ARGUMENT¶
Pass in a value for name and you’ll tell Beautiful Soup to only consider tags
with certain names. Text strings will be ignored, as will tags whose names that
don’t match.
This is the simplest usage:
soup.find_all("title")
# [<title>The Dormouse's story</title>]
Recall from Kinds of filters that the value to name can be a string, a regular
expression, a list, a function, or the value True.
THE KEYWORD ARGUMENTS¶
Any argument that’s not recognized will be turned into a filter on one of a
tag’s attributes. If you pass in a value for an argument called id, Beautiful
Soup will filter against each tag’s ‘id’ attribute:
soup.find_all(id='link2')
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
If you pass in a value for href, Beautiful Soup will filter against each tag’s
‘href’ attribute:
soup.find_all(href=re.compile("elsie"))
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
You can filter an attribute based on a string, a regular expression, a list, a
function, or the value True.
This code finds all tags whose id attribute has a value, regardless of what the
value is:
soup.find_all(id=True)
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
You can filter multiple attributes at once by passing in more than one keyword
argument:
soup.find_all(href=re.compile("elsie"), id='link1')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
Some attributes, like the data-* attributes in HTML 5, have names that can’t be
used as the names of keyword arguments:
data_soup = BeautifulSoup('<div data-foo="value">foo!</div>', 'html.parser')
data_soup.find_all(data-foo="value")
# SyntaxError: keyword can't be an expression
You can use these attributes in searches by putting them into a dictionary and
passing the dictionary into find_all() as the attrs argument:
data_soup.find_all(attrs={"data-foo": "value"})
# [<div data-foo="value">foo!</div>]
You can’t use a keyword argument to search for HTML’s ‘name’ element, because
Beautiful Soup uses the name argument to contain the name of the tag itself.
Instead, you can give a value to ‘name’ in the attrs argument:
name_soup = BeautifulSoup('<input name="email"/>', 'html.parser')
name_soup.find_all(name="email")
# []
name_soup.find_all(attrs={"name": "email"})
# [<input name="email"/>]
SEARCHING BY CSS CLASS¶
It’s very useful to search for a tag that has a certain CSS class, but the name
of the CSS attribute, “class”, is a reserved word in Python. Using class as a
keyword argument will give you a syntax error. As of Beautiful Soup 4.1.2, you
can search by CSS class using the keyword argument class_:
soup.find_all("a", class_="sister")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
As with any keyword argument, you can pass class_ a string, a regular
expression, a function, or True:
soup.find_all(class_=re.compile("itl"))
# [<p class="title"><b>The Dormouse's story</b></p>]
def has_six_characters(css_class):
return css_class is not None and len(css_class) == 6
soup.find_all(class_=has_six_characters)
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
Remember that a single tag can have multiple values for its “class” attribute.
When you search for a tag that matches a certain CSS class, you’re matching
against any of its CSS classes:
css_soup = BeautifulSoup('<p class="body strikeout"></p>', 'html.parser')
css_soup.find_all("p", class_="strikeout")
# [<p class="body strikeout"></p>]
css_soup.find_all("p", class_="body")
# [<p class="body strikeout"></p>]
You can also search for the exact string value of the class attribute:
css_soup.find_all("p", class_="body strikeout")
# [<p class="body strikeout"></p>]
But searching for variants of the string value won’t work:
css_soup.find_all("p", class_="strikeout body")
# []
If you want to search for tags that match two or more CSS classes, you should
use a CSS selector:
css_soup.select("p.strikeout.body")
# [<p class="body strikeout"></p>]
In older versions of Beautiful Soup, which don’t have the class_ shortcut, you
can use the attrs trick mentioned above. Create a dictionary whose value for
“class” is the string (or regular expression, or whatever) you want to search
for:
soup.find_all("a", attrs={"class": "sister"})
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
THE STRING ARGUMENT¶
With string you can search for strings instead of tags. As with name and the
keyword arguments, you can pass in a string, a regular expression, a list, a
function, or the value True. Here are some examples:
soup.find_all(string="Elsie")
# ['Elsie']
soup.find_all(string=["Tillie", "Elsie", "Lacie"])
# ['Elsie', 'Lacie', 'Tillie']
soup.find_all(string=re.compile("Dormouse"))
# ["The Dormouse's story", "The Dormouse's story"]
def is_the_only_string_within_a_tag(s):
"""Return True if this string is the only child of its parent tag."""
return (s == s.parent.string)
soup.find_all(string=is_the_only_string_within_a_tag)
# ["The Dormouse's story", "The Dormouse's story", 'Elsie', 'Lacie', 'Tillie', '...']
Although string is for finding strings, you can combine it with arguments that
find tags: Beautiful Soup will find all tags whose .string matches your value
for string. This code finds the <a> tags whose .string is “Elsie”:
soup.find_all("a", string="Elsie")
# [<a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>]
The string argument is new in Beautiful Soup 4.4.0. In earlier versions it was
called text:
soup.find_all("a", text="Elsie")
# [<a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>]
THE LIMIT ARGUMENT¶
find_all() returns all the tags and strings that match your filters. This can
take a while if the document is large. If you don’t need all the results, you
can pass in a number for limit. This works just like the LIMIT keyword in SQL.
It tells Beautiful Soup to stop gathering results after it’s found a certain
number.
There are three links in the “three sisters” document, but this code only finds
the first two:
soup.find_all("a", limit=2)
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
THE RECURSIVE ARGUMENT¶
If you call mytag.find_all(), Beautiful Soup will examine all the descendants of
mytag: its children, its children’s children, and so on. If you only want
Beautiful Soup to consider direct children, you can pass in recursive=False. See
the difference here:
soup.html.find_all("title")
# [<title>The Dormouse's story</title>]
soup.html.find_all("title", recursive=False)
# []
Here’s that part of the document:
<html>
<head>
<title>
The Dormouse's story
</title>
</head>
...
The <title> tag is beneath the <html> tag, but it’s not directly beneath the
<html> tag: the <head> tag is in the way. Beautiful Soup finds the <title> tag
when it’s allowed to look at all descendants of the <html> tag, but when
recursive=False restricts it to the <html> tag’s immediate children, it finds
nothing.
Beautiful Soup offers a lot of tree-searching methods (covered below), and they
mostly take the same arguments as find_all(): name, attrs, string, limit, and
the keyword arguments. But the recursive argument is different: find_all() and
find() are the only methods that support it. Passing recursive=False into a
method like find_parents() wouldn’t be very useful.
CALLING A TAG IS LIKE CALLING FIND_ALL()¶
Because find_all() is the most popular method in the Beautiful Soup search API,
you can use a shortcut for it. If you treat the BeautifulSoup object or a Tag
object as though it were a function, then it’s the same as calling find_all() on
that object. These two lines of code are equivalent:
soup.find_all("a")
soup("a")
These two lines are also equivalent:
soup.title.find_all(string=True)
soup.title(string=True)
FIND()¶
Method signature: find(name, attrs, recursive, string, **kwargs)
The find_all() method scans the entire document looking for results, but
sometimes you only want to find one result. If you know a document only has one
<body> tag, it’s a waste of time to scan the entire document looking for more.
Rather than passing in limit=1 every time you call find_all, you can use the
find() method. These two lines of code are nearly equivalent:
soup.find_all('title', limit=1)
# [<title>The Dormouse's story</title>]
soup.find('title')
# <title>The Dormouse's story</title>
The only difference is that find_all() returns a list containing the single
result, and find() just returns the result.
If find_all() can’t find anything, it returns an empty list. If find() can’t
find anything, it returns None:
print(soup.find("nosuchtag"))
# None
Remember the soup.head.title trick from Navigating using tag names? That trick
works by repeatedly calling find():
soup.head.title
# <title>The Dormouse's story</title>
soup.find("head").find("title")
# <title>The Dormouse's story</title>
FIND_PARENTS() AND FIND_PARENT()¶
Method signature: find_parents(name, attrs, string, limit, **kwargs)
Method signature: find_parent(name, attrs, string, **kwargs)
I spent a lot of time above covering find_all() and find(). The Beautiful Soup
API defines ten other methods for searching the tree, but don’t be afraid. Five
of these methods are basically the same as find_all(), and the other five are
basically the same as find(). The only differences are in what parts of the tree
they search.
First let’s consider find_parents() and find_parent(). Remember that find_all()
and find() work their way down the tree, looking at tag’s descendants. These
methods do the opposite: they work their way up the tree, looking at a tag’s (or
a string’s) parents. Let’s try them out, starting from a string buried deep in
the “three daughters” document:
a_string = soup.find(string="Lacie")
a_string
# 'Lacie'
a_string.find_parents("a")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
a_string.find_parent("p")
# <p class="story">Once upon a time there were three little sisters; and their names were
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a> and
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>;
# and they lived at the bottom of a well.</p>
a_string.find_parents("p", class_="title")
# []
One of the three <a> tags is the direct parent of the string in question, so our
search finds it. One of the three <p> tags is an indirect parent of the string,
and our search finds that as well. There’s a <p> tag with the CSS class “title”
somewhere in the document, but it’s not one of this string’s parents, so we
can’t find it with find_parents().
You may have made the connection between find_parent() and find_parents(), and
the .parent and .parents attributes mentioned earlier. The connection is very
strong. These search methods actually use .parents to iterate over all the
parents, and check each one against the provided filter to see if it matches.
FIND_NEXT_SIBLINGS() AND FIND_NEXT_SIBLING()¶
Method signature: find_next_siblings(name, attrs, string, limit, **kwargs)
Method signature: find_next_sibling(name, attrs, string, **kwargs)
These methods use .next_siblings to iterate over the rest of an element’s
siblings in the tree. The find_next_siblings() method returns all the siblings
that match, and find_next_sibling() only returns the first one:
first_link = soup.a
first_link
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
first_link.find_next_siblings("a")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
first_story_paragraph = soup.find("p", "story")
first_story_paragraph.find_next_sibling("p")
# <p class="story">...</p>
FIND_PREVIOUS_SIBLINGS() AND FIND_PREVIOUS_SIBLING()¶
Method signature: find_previous_siblings(name, attrs, string, limit, **kwargs)
Method signature: find_previous_sibling(name, attrs, string, **kwargs)
These methods use .previous_siblings to iterate over an element’s siblings that
precede it in the tree. The find_previous_siblings() method returns all the
siblings that match, and find_previous_sibling() only returns the first one:
last_link = soup.find("a", id="link3")
last_link
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>
last_link.find_previous_siblings("a")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
first_story_paragraph = soup.find("p", "story")
first_story_paragraph.find_previous_sibling("p")
# <p class="title"><b>The Dormouse's story</b></p>
FIND_ALL_NEXT() AND FIND_NEXT()¶
Method signature: find_all_next(name, attrs, string, limit, **kwargs)
Method signature: find_next(name, attrs, string, **kwargs)
These methods use .next_elements to iterate over whatever tags and strings that
come after it in the document. The find_all_next() method returns all matches,
and find_next() only returns the first match:
first_link = soup.a
first_link
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
first_link.find_all_next(string=True)
# ['Elsie', ',\n', 'Lacie', ' and\n', 'Tillie',
# ';\nand they lived at the bottom of a well.', '\n', '...', '\n']
first_link.find_next("p")
# <p class="story">...</p>
In the first example, the string “Elsie” showed up, even though it was contained
within the <a> tag we started from. In the second example, the last <p> tag in
the document showed up, even though it’s not in the same part of the tree as the
<a> tag we started from. For these methods, all that matters is that an element
match the filter, and show up later in the document than the starting element.
FIND_ALL_PREVIOUS() AND FIND_PREVIOUS()¶
Method signature: find_all_previous(name, attrs, string, limit, **kwargs)
Method signature: find_previous(name, attrs, string, **kwargs)
These methods use .previous_elements to iterate over the tags and strings that
came before it in the document. The find_all_previous() method returns all
matches, and find_previous() only returns the first match:
first_link = soup.a
first_link
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
first_link.find_all_previous("p")
# [<p class="story">Once upon a time there were three little sisters; ...</p>,
# <p class="title"><b>The Dormouse's story</b></p>]
first_link.find_previous("title")
# <title>The Dormouse's story</title>
The call to find_all_previous("p") found the first paragraph in the document
(the one with class=”title”), but it also finds the second paragraph, the <p>
tag that contains the <a> tag we started with. This shouldn’t be too surprising:
we’re looking at all the tags that show up earlier in the document than the one
we started with. A <p> tag that contains an <a> tag must have shown up before
the <a> tag it contains.
CSS SELECTORS¶
BeautifulSoup has a .select() method which uses the SoupSieve package to run a
CSS selector against a parsed document and return all the matching elements. Tag
has a similar method which runs a CSS selector against the contents of a single
tag.
(The SoupSieve integration was added in Beautiful Soup 4.7.0. Earlier versions
also have the .select() method, but only the most commonly-used CSS selectors
are supported. If you installed Beautiful Soup through pip, SoupSieve was
installed at the same time, so you don’t have to do anything extra.)
The SoupSieve documentation lists all the currently supported CSS selectors, but
here are some of the basics:
You can find tags:
soup.select("title")
# [<title>The Dormouse's story</title>]
soup.select("p:nth-of-type(3)")
# [<p class="story">...</p>]
Find tags beneath other tags:
soup.select("body a")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.select("html head title")
# [<title>The Dormouse's story</title>]
Find tags directly beneath other tags:
soup.select("head > title")
# [<title>The Dormouse's story</title>]
soup.select("p > a")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.select("p > a:nth-of-type(2)")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
soup.select("p > #link1")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
soup.select("body > a")
# []
Find the siblings of tags:
soup.select("#link1 ~ .sister")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.select("#link1 + .sister")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
Find tags by CSS class:
soup.select(".sister")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.select("[class~=sister]")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
Find tags by ID:
soup.select("#link1")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
soup.select("a#link2")
# [<a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
Find tags that match any selector from a list of selectors:
soup.select("#link1,#link2")
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>]
Test for the existence of an attribute:
soup.select('a[href]')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
Find tags by attribute value:
soup.select('a[href="http://example.com/elsie"]')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
soup.select('a[href^="http://example.com/"]')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>,
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>,
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.select('a[href$="tillie"]')
# [<a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>]
soup.select('a[href*=".com/el"]')
# [<a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>]
There’s also a method called select_one(), which finds only the first tag that
matches a selector:
soup.select_one(".sister")
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
If you’ve parsed XML that defines namespaces, you can use them in CSS
selectors.:
from bs4 import BeautifulSoup
xml = """<tag xmlns:ns1="http://namespace1/" xmlns:ns2="http://namespace2/">
<ns1:child>I'm in namespace 1</ns1:child>
<ns2:child>I'm in namespace 2</ns2:child>
</tag> """
soup = BeautifulSoup(xml, "xml")
soup.select("child")
# [<ns1:child>I'm in namespace 1</ns1:child>, <ns2:child>I'm in namespace 2</ns2:child>]
soup.select("ns1|child")
# [<ns1:child>I'm in namespace 1</ns1:child>]
When handling a CSS selector that uses namespaces, Beautiful Soup always tries
to use namespace prefixes that make sense based on what it saw while parsing the
document. You can always provide your own dictionary of abbreviations:
namespaces = dict(first="http://namespace1/", second="http://namespace2/")
soup.select("second|child", namespaces=namespaces)
# [<ns1:child>I'm in namespace 2</ns1:child>]
All this CSS selector stuff is a convenience for people who already know the CSS
selector syntax. You can do all of this with the Beautiful Soup API. And if CSS
selectors are all you need, you should parse the document with lxml: it’s a lot
faster. But this lets you combine CSS selectors with the Beautiful Soup API.
MODIFYING THE TREE¶
Beautiful Soup’s main strength is in searching the parse tree, but you can also
modify the tree and write your changes as a new HTML or XML document.
CHANGING TAG NAMES AND ATTRIBUTES¶
I covered this earlier, in Attributes, but it bears repeating. You can rename a
tag, change the values of its attributes, add new attributes, and delete
attributes:
soup = BeautifulSoup('<b class="boldest">Extremely bold</b>', 'html.parser')
tag = soup.b
tag.name = "blockquote"
tag['class'] = 'verybold'
tag['id'] = 1
tag
# <blockquote class="verybold" id="1">Extremely bold</blockquote>
del tag['class']
del tag['id']
tag
# <blockquote>Extremely bold</blockquote>
MODIFYING .STRING¶
If you set a tag’s .string attribute to a new string, the tag’s contents are
replaced with that string:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
tag = soup.a
tag.string = "New link text."
tag
# <a href="http://example.com/">New link text.</a>
Be careful: if the tag contained other tags, they and all their contents will be
destroyed.
APPEND()¶
You can add to a tag’s contents with Tag.append(). It works just like calling
.append() on a Python list:
soup = BeautifulSoup("<a>Foo</a>", 'html.parser')
soup.a.append("Bar")
soup
# <a>FooBar</a>
soup.a.contents
# ['Foo', 'Bar']
EXTEND()¶
Starting in Beautiful Soup 4.7.0, Tag also supports a method called .extend(),
which adds every element of a list to a Tag, in order:
soup = BeautifulSoup("<a>Soup</a>", 'html.parser')
soup.a.extend(["'s", " ", "on"])
soup
# <a>Soup's on</a>
soup.a.contents
# ['Soup', ''s', ' ', 'on']
NAVIGABLESTRING() AND .NEW_TAG()¶
If you need to add a string to a document, no problem–you can pass a Python
string in to append(), or you can call the NavigableString constructor:
soup = BeautifulSoup("<b></b>", 'html.parser')
tag = soup.b
tag.append("Hello")
new_string = NavigableString(" there")
tag.append(new_string)
tag
# <b>Hello there.</b>
tag.contents
# ['Hello', ' there']
If you want to create a comment or some other subclass of NavigableString, just
call the constructor:
from bs4 import Comment
new_comment = Comment("Nice to see you.")
tag.append(new_comment)
tag
# <b>Hello there<!--Nice to see you.--></b>
tag.contents
# ['Hello', ' there', 'Nice to see you.']
(This is a new feature in Beautiful Soup 4.4.0.)
What if you need to create a whole new tag? The best solution is to call the
factory method BeautifulSoup.new_tag():
soup = BeautifulSoup("<b></b>", 'html.parser')
original_tag = soup.b
new_tag = soup.new_tag("a", href="http://www.example.com")
original_tag.append(new_tag)
original_tag
# <b><a href="http://www.example.com"></a></b>
new_tag.string = "Link text."
original_tag
# <b><a href="http://www.example.com">Link text.</a></b>
Only the first argument, the tag name, is required.
INSERT()¶
Tag.insert() is just like Tag.append(), except the new element doesn’t
necessarily go at the end of its parent’s .contents. It’ll be inserted at
whatever numeric position you say. It works just like .insert() on a Python
list:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
tag = soup.a
tag.insert(1, "but did not endorse ")
tag
# <a href="http://example.com/">I linked to but did not endorse <i>example.com</i></a>
tag.contents
# ['I linked to ', 'but did not endorse', <i>example.com</i>]
INSERT_BEFORE() AND INSERT_AFTER()¶
The insert_before() method inserts tags or strings immediately before something
else in the parse tree:
soup = BeautifulSoup("<b>leave</b>", 'html.parser')
tag = soup.new_tag("i")
tag.string = "Don't"
soup.b.string.insert_before(tag)
soup.b
# <b><i>Don't</i>leave</b>
The insert_after() method inserts tags or strings immediately following
something else in the parse tree:
div = soup.new_tag('div')
div.string = 'ever'
soup.b.i.insert_after(" you ", div)
soup.b
# <b><i>Don't</i> you <div>ever</div> leave</b>
soup.b.contents
# [<i>Don't</i>, ' you', <div>ever</div>, 'leave']
CLEAR()¶
Tag.clear() removes the contents of a tag:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
tag = soup.a
tag.clear()
tag
# <a href="http://example.com/"></a>
EXTRACT()¶
PageElement.extract() removes a tag or string from the tree. It returns the tag
or string that was extracted:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
a_tag = soup.a
i_tag = soup.i.extract()
a_tag
# <a href="http://example.com/">I linked to</a>
i_tag
# <i>example.com</i>
print(i_tag.parent)
# None
At this point you effectively have two parse trees: one rooted at the
BeautifulSoup object you used to parse the document, and one rooted at the tag
that was extracted. You can go on to call extract on a child of the element you
extracted:
my_string = i_tag.string.extract()
my_string
# 'example.com'
print(my_string.parent)
# None
i_tag
# <i></i>
DECOMPOSE()¶
Tag.decompose() removes a tag from the tree, then completely destroys it and its
contents:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
a_tag = soup.a
i_tag = soup.i
i_tag.decompose()
a_tag
# <a href="http://example.com/">I linked to</a>
The behavior of a decomposed Tag or NavigableString is not defined and you
should not use it for anything. If you’re not sure whether something has been
decomposed, you can check its .decomposed property (new in Beautiful Soup
4.9.0):
i_tag.decomposed
# True
a_tag.decomposed
# False
REPLACE_WITH()¶
PageElement.replace_with() removes a tag or string from the tree, and replaces
it with one or more tags or strings of your choice:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
a_tag = soup.a
new_tag = soup.new_tag("b")
new_tag.string = "example.com"
a_tag.i.replace_with(new_tag)
a_tag
# <a href="http://example.com/">I linked to <b>example.com</b></a>
bold_tag = soup.new_tag("b")
bold_tag.string = "example"
i_tag = soup.new_tag("i")
i_tag.string = "net"
a_tag.b.replace_with(bold_tag, ".", i_tag)
a_tag
# <a href="http://example.com/">I linked to <b>example</b>.<i>net</i></a>
replace_with() returns the tag or string that got replaced, so that you can
examine it or add it back to another part of the tree.
The ability to pass multiple arguments into replace_with() is new in Beautiful
Soup 4.10.0.
WRAP()¶
PageElement.wrap() wraps an element in the tag you specify. It returns the new
wrapper:
soup = BeautifulSoup("<p>I wish I was bold.</p>", 'html.parser')
soup.p.string.wrap(soup.new_tag("b"))
# <b>I wish I was bold.</b>
soup.p.wrap(soup.new_tag("div"))
# <div><p><b>I wish I was bold.</b></p></div>
This method is new in Beautiful Soup 4.0.5.
UNWRAP()¶
Tag.unwrap() is the opposite of wrap(). It replaces a tag with whatever’s inside
that tag. It’s good for stripping out markup:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
a_tag = soup.a
a_tag.i.unwrap()
a_tag
# <a href="http://example.com/">I linked to example.com</a>
Like replace_with(), unwrap() returns the tag that was replaced.
SMOOTH()¶
After calling a bunch of methods that modify the parse tree, you may end up with
two or more NavigableString objects next to each other. Beautiful Soup doesn’t
have any problems with this, but since it can’t happen in a freshly parsed
document, you might not expect behavior like the following:
soup = BeautifulSoup("<p>A one</p>", 'html.parser')
soup.p.append(", a two")
soup.p.contents
# ['A one', ', a two']
print(soup.p.encode())
# b'<p>A one, a two</p>'
print(soup.p.prettify())
# <p>
# A one
# , a two
# </p>
You can call Tag.smooth() to clean up the parse tree by consolidating adjacent
strings:
soup.smooth()
soup.p.contents
# ['A one, a two']
print(soup.p.prettify())
# <p>
# A one, a two
# </p>
This method is new in Beautiful Soup 4.8.0.
OUTPUT¶
PRETTY-PRINTING¶
The prettify() method will turn a Beautiful Soup parse tree into a nicely
formatted Unicode string, with a separate line for each tag and each string:
markup = '<html><head><body><a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup, 'html.parser')
soup.prettify()
# '<html>\n <head>\n </head>\n <body>\n <a href="http://example.com/">\n...'
print(soup.prettify())
# <html>
# <head>
# </head>
# <body>
# <a href="http://example.com/">
# I linked to
# <i>
# example.com
# </i>
# </a>
# </body>
# </html>
You can call prettify() on the top-level BeautifulSoup object, or on any of its
Tag objects:
print(soup.a.prettify())
# <a href="http://example.com/">
# I linked to
# <i>
# example.com
# </i>
# </a>
Since it adds whitespace (in the form of newlines), prettify() changes the
meaning of an HTML document and should not be used to reformat one. The goal of
prettify() is to help you visually understand the structure of the documents you
work with.
NON-PRETTY PRINTING¶
If you just want a string, with no fancy formatting, you can call str() on a
BeautifulSoup object, or on a Tag within it:
str(soup)
# '<html><head></head><body><a href="http://example.com/">I linked to <i>example.com</i></a></body></html>'
str(soup.a)
# '<a href="http://example.com/">I linked to <i>example.com</i></a>'
The str() function returns a string encoded in UTF-8. See Encodings for other
options.
You can also call encode() to get a bytestring, and decode() to get Unicode.
OUTPUT FORMATTERS¶
If you give Beautiful Soup a document that contains HTML entities like
“&lquot;”, they’ll be converted to Unicode characters:
soup = BeautifulSoup("“Dammit!” he said.", 'html.parser')
str(soup)
# '“Dammit!” he said.'
If you then convert the document to a bytestring, the Unicode characters will be
encoded as UTF-8. You won’t get the HTML entities back:
soup.encode("utf8")
# b'\xe2\x80\x9cDammit!\xe2\x80\x9d he said.'
By default, the only characters that are escaped upon output are bare ampersands
and angle brackets. These get turned into “&”, “<”, and “>”, so that
Beautiful Soup doesn’t inadvertently generate invalid HTML or XML:
soup = BeautifulSoup("<p>The law firm of Dewey, Cheatem, & Howe</p>", 'html.parser')
soup.p
# <p>The law firm of Dewey, Cheatem, & Howe</p>
soup = BeautifulSoup('<a href="http://example.com/?foo=val1&bar=val2">A link</a>', 'html.parser')
soup.a
# <a href="http://example.com/?foo=val1&bar=val2">A link</a>
You can change this behavior by providing a value for the formatter argument to
prettify(), encode(), or decode(). Beautiful Soup recognizes five possible
values for formatter.
The default is formatter="minimal". Strings will only be processed enough to
ensure that Beautiful Soup generates valid HTML/XML:
french = "<p>Il a dit <<Sacré bleu!>></p>"
soup = BeautifulSoup(french, 'html.parser')
print(soup.prettify(formatter="minimal"))
# <p>
# Il a dit <<Sacré bleu!>>
# </p>
If you pass in formatter="html", Beautiful Soup will convert Unicode characters
to HTML entities whenever possible:
print(soup.prettify(formatter="html"))
# <p>
# Il a dit <<Sacré bleu!>>
# </p>
If you pass in formatter="html5", it’s similar to formatter="html", but
Beautiful Soup will omit the closing slash in HTML void tags like “br”:
br = BeautifulSoup("<br>", 'html.parser').br
print(br.encode(formatter="html"))
# b'<br/>'
print(br.encode(formatter="html5"))
# b'<br>'
In addition, any attributes whose values are the empty string will become
HTML-style boolean attributes:
option = BeautifulSoup('<option selected=""></option>').option
print(option.encode(formatter="html"))
# b'<option selected=""></option>'
print(option.encode(formatter="html5"))
# b'<option selected></option>'
(This behavior is new as of Beautiful Soup 4.10.0.)
If you pass in formatter=None, Beautiful Soup will not modify strings at all on
output. This is the fastest option, but it may lead to Beautiful Soup generating
invalid HTML/XML, as in these examples:
print(soup.prettify(formatter=None))
# <p>
# Il a dit <<Sacré bleu!>>
# </p>
link_soup = BeautifulSoup('<a href="http://example.com/?foo=val1&bar=val2">A link</a>', 'html.parser')
print(link_soup.a.encode(formatter=None))
# b'<a href="http://example.com/?foo=val1&bar=val2">A link</a>'
If you need more sophisticated control over your output, you can use Beautiful
Soup’s Formatter class. Here’s a formatter that converts strings to uppercase,
whether they occur in a text node or in an attribute value:
from bs4.formatter import HTMLFormatter
def uppercase(str):
return str.upper()
formatter = HTMLFormatter(uppercase)
print(soup.prettify(formatter=formatter))
# <p>
# IL A DIT <<SACRÉ BLEU!>>
# </p>
print(link_soup.a.prettify(formatter=formatter))
# <a href="HTTP://EXAMPLE.COM/?FOO=VAL1&BAR=VAL2">
# A LINK
# </a>
Here’s a formatter that increases the indentation when pretty-printing:
formatter = HTMLFormatter(indent=8)
print(link_soup.a.prettify(formatter=formatter))
# <a href="http://example.com/?foo=val1&bar=val2">
# A link
# </a>
Subclassing HTMLFormatter or XMLFormatter will give you even more control over
the output. For example, Beautiful Soup sorts the attributes in every tag by
default:
attr_soup = BeautifulSoup(b'<p z="1" m="2" a="3"></p>', 'html.parser')
print(attr_soup.p.encode())
# <p a="3" m="2" z="1"></p>
To turn this off, you can subclass the Formatter.attributes() method, which
controls which attributes are output and in what order. This implementation also
filters out the attribute called “m” whenever it appears:
class UnsortedAttributes(HTMLFormatter):
def attributes(self, tag):
for k, v in tag.attrs.items():
if k == 'm':
continue
yield k, v
print(attr_soup.p.encode(formatter=UnsortedAttributes()))
# <p z="1" a="3"></p>
One last caveat: if you create a CData object, the text inside that object is
always presented exactly as it appears, with no formatting. Beautiful Soup will
call your entity substitution function, just in case you’ve written a custom
function that counts all the strings in the document or something, but it will
ignore the return value:
from bs4.element import CData
soup = BeautifulSoup("<a></a>", 'html.parser')
soup.a.string = CData("one < three")
print(soup.a.prettify(formatter="html"))
# <a>
# <![CDATA[one < three]]>
# </a>
GET_TEXT()¶
If you only want the human-readable text inside a document or tag, you can use
the get_text() method. It returns all the text in a document or beneath a tag,
as a single Unicode string:
markup = '<a href="http://example.com/">\nI linked to <i>example.com</i>\n</a>'
soup = BeautifulSoup(markup, 'html.parser')
soup.get_text()
'\nI linked to example.com\n'
soup.i.get_text()
'example.com'
You can specify a string to be used to join the bits of text together:
# soup.get_text("|")
'\nI linked to |example.com|\n'
You can tell Beautiful Soup to strip whitespace from the beginning and end of
each bit of text:
# soup.get_text("|", strip=True)
'I linked to|example.com'
But at that point you might want to use the .stripped_strings generator instead,
and process the text yourself:
[text for text in soup.stripped_strings]
# ['I linked to', 'example.com']
As of Beautiful Soup version 4.9.0, when lxml or html.parser are in use, the
contents of <script>, <style>, and <template> tags are generally not considered
to be ‘text’, since those tags are not part of the human-visible content of the
page.
As of Beautiful Soup version 4.10.0, you can call get_text(), .strings, or
.stripped_strings on a NavigableString object. It will either return the object
itself, or nothing, so the only reason to do this is when you’re iterating over
a mixed list.
SPECIFYING THE PARSER TO USE¶
If you just need to parse some HTML, you can dump the markup into the
BeautifulSoup constructor, and it’ll probably be fine. Beautiful Soup will pick
a parser for you and parse the data. But there are a few additional arguments
you can pass in to the constructor to change which parser is used.
The first argument to the BeautifulSoup constructor is a string or an open
filehandle–the markup you want parsed. The second argument is how you’d like the
markup parsed.
If you don’t specify anything, you’ll get the best HTML parser that’s installed.
Beautiful Soup ranks lxml’s parser as being the best, then html5lib’s, then
Python’s built-in parser. You can override this by specifying one of the
following:
* What type of markup you want to parse. Currently supported are “html”, “xml”,
and “html5”.
* The name of the parser library you want to use. Currently supported options
are “lxml”, “html5lib”, and “html.parser” (Python’s built-in HTML parser).
The section Installing a parser contrasts the supported parsers.
If you don’t have an appropriate parser installed, Beautiful Soup will ignore
your request and pick a different parser. Right now, the only supported XML
parser is lxml. If you don’t have lxml installed, asking for an XML parser won’t
give you one, and asking for “lxml” won’t work either.
DIFFERENCES BETWEEN PARSERS¶
Beautiful Soup presents the same interface to a number of different parsers, but
each parser is different. Different parsers will create different parse trees
from the same document. The biggest differences are between the HTML parsers and
the XML parsers. Here’s a short document, parsed as HTML using the parser that
comes with Python:
BeautifulSoup("<a><b/></a>", "html.parser")
# <a><b></b></a>
Since a standalone <b/> tag is not valid HTML, html.parser turns it into a
<b></b> tag pair.
Here’s the same document parsed as XML (running this requires that you have lxml
installed). Note that the standalone <b/> tag is left alone, and that the
document is given an XML declaration instead of being put into an <html> tag.:
print(BeautifulSoup("<a><b/></a>", "xml"))
# <?xml version="1.0" encoding="utf-8"?>
# <a><b/></a>
There are also differences between HTML parsers. If you give Beautiful Soup a
perfectly-formed HTML document, these differences won’t matter. One parser will
be faster than another, but they’ll all give you a data structure that looks
exactly like the original HTML document.
But if the document is not perfectly-formed, different parsers will give
different results. Here’s a short, invalid document parsed using lxml’s HTML
parser. Note that the <a> tag gets wrapped in <body> and <html> tags, and the
dangling </p> tag is simply ignored:
BeautifulSoup("<a></p>", "lxml")
# <html><body><a></a></body></html>
Here’s the same document parsed using html5lib:
BeautifulSoup("<a></p>", "html5lib")
# <html><head></head><body><a><p></p></a></body></html>
Instead of ignoring the dangling </p> tag, html5lib pairs it with an opening <p>
tag. html5lib also adds an empty <head> tag; lxml didn’t bother.
Here’s the same document parsed with Python’s built-in HTML parser:
BeautifulSoup("<a></p>", "html.parser")
# <a></a>
Like lxml, this parser ignores the closing </p> tag. Unlike html5lib or lxml,
this parser makes no attempt to create a well-formed HTML document by adding
<html> or <body> tags.
Since the document “<a></p>” is invalid, none of these techniques is the
‘correct’ way to handle it. The html5lib parser uses techniques that are part of
the HTML5 standard, so it has the best claim on being the ‘correct’ way, but all
three techniques are legitimate.
Differences between parsers can affect your script. If you’re planning on
distributing your script to other people, or running it on multiple machines,
you should specify a parser in the BeautifulSoup constructor. That will reduce
the chances that your users parse a document differently from the way you parse
it.
ENCODINGS¶
Any HTML or XML document is written in a specific encoding like ASCII or UTF-8.
But when you load that document into Beautiful Soup, you’ll discover it’s been
converted to Unicode:
markup = "<h1>Sacr\xc3\xa9 bleu!</h1>"
soup = BeautifulSoup(markup, 'html.parser')
soup.h1
# <h1>Sacré bleu!</h1>
soup.h1.string
# 'Sacr\xe9 bleu!'
It’s not magic. (That sure would be nice.) Beautiful Soup uses a sub-library
called Unicode, Dammit to detect a document’s encoding and convert it to
Unicode. The autodetected encoding is available as the .original_encoding
attribute of the BeautifulSoup object:
soup.original_encoding
'utf-8'
Unicode, Dammit guesses correctly most of the time, but sometimes it makes
mistakes. Sometimes it guesses correctly, but only after a byte-by-byte search
of the document that takes a very long time. If you happen to know a document’s
encoding ahead of time, you can avoid mistakes and delays by passing it to the
BeautifulSoup constructor as from_encoding.
Here’s a document written in ISO-8859-8. The document is so short that Unicode,
Dammit can’t get a lock on it, and misidentifies it as ISO-8859-7:
markup = b"<h1>\xed\xe5\xec\xf9</h1>"
soup = BeautifulSoup(markup, 'html.parser')
print(soup.h1)
# <h1>νεμω</h1>
print(soup.original_encoding)
# iso-8859-7
We can fix this by passing in the correct from_encoding:
soup = BeautifulSoup(markup, 'html.parser', from_encoding="iso-8859-8")
print(soup.h1)
# <h1>םולש</h1>
print(soup.original_encoding)
# iso8859-8
If you don’t know what the correct encoding is, but you know that Unicode,
Dammit is guessing wrong, you can pass the wrong guesses in as
exclude_encodings:
soup = BeautifulSoup(markup, 'html.parser', exclude_encodings=["iso-8859-7"])
print(soup.h1)
# <h1>םולש</h1>
print(soup.original_encoding)
# WINDOWS-1255
Windows-1255 isn’t 100% correct, but that encoding is a compatible superset of
ISO-8859-8, so it’s close enough. (exclude_encodings is a new feature in
Beautiful Soup 4.4.0.)
In rare cases (usually when a UTF-8 document contains text written in a
completely different encoding), the only way to get Unicode may be to replace
some characters with the special Unicode character “REPLACEMENT CHARACTER”
(U+FFFD, �). If Unicode, Dammit needs to do this, it will set the
.contains_replacement_characters attribute to True on the UnicodeDammit or
BeautifulSoup object. This lets you know that the Unicode representation is not
an exact representation of the original–some data was lost. If a document
contains �, but .contains_replacement_characters is False, you’ll know that the
� was there originally (as it is in this paragraph) and doesn’t stand in for
missing data.
OUTPUT ENCODING¶
When you write out a document from Beautiful Soup, you get a UTF-8 document,
even if the document wasn’t in UTF-8 to begin with. Here’s a document written in
the Latin-1 encoding:
markup = b'''
<html>
<head>
<meta content="text/html; charset=ISO-Latin-1" http-equiv="Content-type" />
</head>
<body>
<p>Sacr\xe9 bleu!</p>
</body>
</html>
'''
soup = BeautifulSoup(markup, 'html.parser')
print(soup.prettify())
# <html>
# <head>
# <meta content="text/html; charset=utf-8" http-equiv="Content-type" />
# </head>
# <body>
# <p>
# Sacré bleu!
# </p>
# </body>
# </html>
Note that the <meta> tag has been rewritten to reflect the fact that the
document is now in UTF-8.
If you don’t want UTF-8, you can pass an encoding into prettify():
print(soup.prettify("latin-1"))
# <html>
# <head>
# <meta content="text/html; charset=latin-1" http-equiv="Content-type" />
# ...
You can also call encode() on the BeautifulSoup object, or any element in the
soup, just as if it were a Python string:
soup.p.encode("latin-1")
# b'<p>Sacr\xe9 bleu!</p>'
soup.p.encode("utf-8")
# b'<p>Sacr\xc3\xa9 bleu!</p>'
Any characters that can’t be represented in your chosen encoding will be
converted into numeric XML entity references. Here’s a document that includes
the Unicode character SNOWMAN:
markup = u"<b>\N{SNOWMAN}</b>"
snowman_soup = BeautifulSoup(markup, 'html.parser')
tag = snowman_soup.b
The SNOWMAN character can be part of a UTF-8 document (it looks like ☃), but
there’s no representation for that character in ISO-Latin-1 or ASCII, so it’s
converted into “☃” for those encodings:
print(tag.encode("utf-8"))
# b'<b>\xe2\x98\x83</b>'
print(tag.encode("latin-1"))
# b'<b>☃</b>'
print(tag.encode("ascii"))
# b'<b>☃</b>'
UNICODE, DAMMIT¶
You can use Unicode, Dammit without using Beautiful Soup. It’s useful whenever
you have data in an unknown encoding and you just want it to become Unicode:
from bs4 import UnicodeDammit
dammit = UnicodeDammit("Sacr\xc3\xa9 bleu!")
print(dammit.unicode_markup)
# Sacré bleu!
dammit.original_encoding
# 'utf-8'
Unicode, Dammit’s guesses will get a lot more accurate if you install one of
these Python libraries: charset-normalizer, chardet, or cchardet. The more data
you give Unicode, Dammit, the more accurately it will guess. If you have your
own suspicions as to what the encoding might be, you can pass them in as a list:
dammit = UnicodeDammit("Sacr\xe9 bleu!", ["latin-1", "iso-8859-1"])
print(dammit.unicode_markup)
# Sacré bleu!
dammit.original_encoding
# 'latin-1'
Unicode, Dammit has two special features that Beautiful Soup doesn’t use.
SMART QUOTES¶
You can use Unicode, Dammit to convert Microsoft smart quotes to HTML or XML
entities:
markup = b"<p>I just \x93love\x94 Microsoft Word\x92s smart quotes</p>"
UnicodeDammit(markup, ["windows-1252"], smart_quotes_to="html").unicode_markup
# '<p>I just “love” Microsoft Word’s smart quotes</p>'
UnicodeDammit(markup, ["windows-1252"], smart_quotes_to="xml").unicode_markup
# '<p>I just “love” Microsoft Word’s smart quotes</p>'
You can also convert Microsoft smart quotes to ASCII quotes:
UnicodeDammit(markup, ["windows-1252"], smart_quotes_to="ascii").unicode_markup
# '<p>I just "love" Microsoft Word\'s smart quotes</p>'
Hopefully you’ll find this feature useful, but Beautiful Soup doesn’t use it.
Beautiful Soup prefers the default behavior, which is to convert Microsoft smart
quotes to Unicode characters along with everything else:
UnicodeDammit(markup, ["windows-1252"]).unicode_markup
# '<p>I just “love” Microsoft Word’s smart quotes</p>'
INCONSISTENT ENCODINGS¶
Sometimes a document is mostly in UTF-8, but contains Windows-1252 characters
such as (again) Microsoft smart quotes. This can happen when a website includes
data from multiple sources. You can use UnicodeDammit.detwingle() to turn such a
document into pure UTF-8. Here’s a simple example:
snowmen = (u"\N{SNOWMAN}" * 3)
quote = (u"\N{LEFT DOUBLE QUOTATION MARK}I like snowmen!\N{RIGHT DOUBLE QUOTATION MARK}")
doc = snowmen.encode("utf8") + quote.encode("windows_1252")
This document is a mess. The snowmen are in UTF-8 and the quotes are in
Windows-1252. You can display the snowmen or the quotes, but not both:
print(doc)
# ☃☃☃�I like snowmen!�
print(doc.decode("windows-1252"))
# ☃☃☃“I like snowmen!”
Decoding the document as UTF-8 raises a UnicodeDecodeError, and decoding it as
Windows-1252 gives you gibberish. Fortunately, UnicodeDammit.detwingle() will
convert the string to pure UTF-8, allowing you to decode it to Unicode and
display the snowmen and quote marks simultaneously:
new_doc = UnicodeDammit.detwingle(doc)
print(new_doc.decode("utf8"))
# ☃☃☃“I like snowmen!”
UnicodeDammit.detwingle() only knows how to handle Windows-1252 embedded in
UTF-8 (or vice versa, I suppose), but this is the most common case.
Note that you must know to call UnicodeDammit.detwingle() on your data before
passing it into BeautifulSoup or the UnicodeDammit constructor. Beautiful Soup
assumes that a document has a single encoding, whatever it might be. If you pass
it a document that contains both UTF-8 and Windows-1252, it’s likely to think
the whole document is Windows-1252, and the document will come out looking like
☃☃☃“I like snowmen!”.
UnicodeDammit.detwingle() is new in Beautiful Soup 4.1.0.
LINE NUMBERS¶
The html.parser and html5lib parsers can keep track of where in the original
document each Tag was found. You can access this information as Tag.sourceline
(line number) and Tag.sourcepos (position of the start tag within a line):
markup = "<p\n>Paragraph 1</p>\n <p>Paragraph 2</p>"
soup = BeautifulSoup(markup, 'html.parser')
for tag in soup.find_all('p'):
print(repr((tag.sourceline, tag.sourcepos, tag.string)))
# (1, 0, 'Paragraph 1')
# (3, 4, 'Paragraph 2')
Note that the two parsers mean slightly different things by sourceline and
sourcepos. For html.parser, these numbers represent the position of the initial
less-than sign. For html5lib, these numbers represent the position of the final
greater-than sign:
soup = BeautifulSoup(markup, 'html5lib')
for tag in soup.find_all('p'):
print(repr((tag.sourceline, tag.sourcepos, tag.string)))
# (2, 0, 'Paragraph 1')
# (3, 6, 'Paragraph 2')
You can shut off this feature by passing store_line_numbers=False` into the
``BeautifulSoup constructor:
markup = "<p\n>Paragraph 1</p>\n <p>Paragraph 2</p>"
soup = BeautifulSoup(markup, 'html.parser', store_line_numbers=False)
print(soup.p.sourceline)
# None
This feature is new in 4.8.1, and the parsers based on lxml don’t support it.
COMPARING OBJECTS FOR EQUALITY¶
Beautiful Soup says that two NavigableString or Tag objects are equal when they
represent the same HTML or XML markup. In this example, the two <b> tags are
treated as equal, even though they live in different parts of the object tree,
because they both look like “<b>pizza</b>”:
markup = "<p>I want <b>pizza</b> and more <b>pizza</b>!</p>"
soup = BeautifulSoup(markup, 'html.parser')
first_b, second_b = soup.find_all('b')
print(first_b == second_b)
# True
print(first_b.previous_element == second_b.previous_element)
# False
If you want to see whether two variables refer to exactly the same object, use
is:
print(first_b is second_b)
# False
COPYING BEAUTIFUL SOUP OBJECTS¶
You can use copy.copy() to create a copy of any Tag or NavigableString:
import copy
p_copy = copy.copy(soup.p)
print(p_copy)
# <p>I want <b>pizza</b> and more <b>pizza</b>!</p>
The copy is considered equal to the original, since it represents the same
markup as the original, but it’s not the same object:
print(soup.p == p_copy)
# True
print(soup.p is p_copy)
# False
The only real difference is that the copy is completely detached from the
original Beautiful Soup object tree, just as if extract() had been called on it:
print(p_copy.parent)
# None
This is because two different Tag objects can’t occupy the same space at the
same time.
ADVANCED PARSER CUSTOMIZATION¶
Beautiful Soup offers a number of ways to customize how the parser treats
incoming HTML and XML. This section covers the most commonly used customization
techniques.
PARSING ONLY PART OF A DOCUMENT¶
Let’s say you want to use Beautiful Soup look at a document’s <a> tags. It’s a
waste of time and memory to parse the entire document and then go over it again
looking for <a> tags. It would be much faster to ignore everything that wasn’t
an <a> tag in the first place. The SoupStrainer class allows you to choose which
parts of an incoming document are parsed. You just create a SoupStrainer and
pass it in to the BeautifulSoup constructor as the parse_only argument.
(Note that this feature won’t work if you’re using the html5lib parser. If you
use html5lib, the whole document will be parsed, no matter what. This is because
html5lib constantly rearranges the parse tree as it works, and if some part of
the document didn’t actually make it into the parse tree, it’ll crash. To avoid
confusion, in the examples below I’ll be forcing Beautiful Soup to use Python’s
built-in parser.)
SOUPSTRAINER¶
The SoupStrainer class takes the same arguments as a typical method from
Searching the tree: name, attrs, string, and **kwargs. Here are three
SoupStrainer objects:
from bs4 import SoupStrainer
only_a_tags = SoupStrainer("a")
only_tags_with_id_link2 = SoupStrainer(id="link2")
def is_short_string(string):
return string is not None and len(string) < 10
only_short_strings = SoupStrainer(string=is_short_string)
I’m going to bring back the “three sisters” document one more time, and we’ll
see what the document looks like when it’s parsed with these three SoupStrainer
objects:
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>
"""
print(BeautifulSoup(html_doc, "html.parser", parse_only=only_a_tags).prettify())
# <a class="sister" href="http://example.com/elsie" id="link1">
# Elsie
# </a>
# <a class="sister" href="http://example.com/lacie" id="link2">
# Lacie
# </a>
# <a class="sister" href="http://example.com/tillie" id="link3">
# Tillie
# </a>
print(BeautifulSoup(html_doc, "html.parser", parse_only=only_tags_with_id_link2).prettify())
# <a class="sister" href="http://example.com/lacie" id="link2">
# Lacie
# </a>
print(BeautifulSoup(html_doc, "html.parser", parse_only=only_short_strings).prettify())
# Elsie
# ,
# Lacie
# and
# Tillie
# ...
#
You can also pass a SoupStrainer into any of the methods covered in Searching
the tree. This probably isn’t terribly useful, but I thought I’d mention it:
soup = BeautifulSoup(html_doc, 'html.parser')
soup.find_all(only_short_strings)
# ['\n\n', '\n\n', 'Elsie', ',\n', 'Lacie', ' and\n', 'Tillie',
# '\n\n', '...', '\n']
CUSTOMIZING MULTI-VALUED ATTRIBUTES¶
In an HTML document, an attribute like class is given a list of values, and an
attribute like id is given a single value, because the HTML specification treats
those attributes differently:
markup = '<a class="cls1 cls2" id="id1 id2">'
soup = BeautifulSoup(markup, 'html.parser')
soup.a['class']
# ['cls1', 'cls2']
soup.a['id']
# 'id1 id2'
You can turn this off by passing in multi_valued_attributes=None. Than all
attributes will be given a single value:
soup = BeautifulSoup(markup, 'html.parser', multi_valued_attributes=None)
soup.a['class']
# 'cls1 cls2'
soup.a['id']
# 'id1 id2'
You can customize this behavior quite a bit by passing in a dictionary for
multi_valued_attributes. If you need this, look at
HTMLTreeBuilder.DEFAULT_CDATA_LIST_ATTRIBUTES to see the configuration Beautiful
Soup uses by default, which is based on the HTML specification.
(This is a new feature in Beautiful Soup 4.8.0.)
HANDLING DUPLICATE ATTRIBUTES¶
When using the html.parser parser, you can use the on_duplicate_attribute
constructor argument to customize what Beautiful Soup does when it encounters a
tag that defines the same attribute more than once:
markup = '<a href="http://url1/" href="http://url2/">'
The default behavior is to use the last value found for the tag:
soup = BeautifulSoup(markup, 'html.parser')
soup.a['href']
# http://url2/
soup = BeautifulSoup(markup, 'html.parser', on_duplicate_attribute='replace')
soup.a['href']
# http://url2/
With on_duplicate_attribute='ignore' you can tell Beautiful Soup to use the
first value found and ignore the rest:
soup = BeautifulSoup(markup, 'html.parser', on_duplicate_attribute='ignore')
soup.a['href']
# http://url1/
(lxml and html5lib always do it this way; their behavior can’t be configured
from within Beautiful Soup.)
If you need more, you can pass in a function that’s called on each duplicate
value:
def accumulate(attributes_so_far, key, value):
if not isinstance(attributes_so_far[key], list):
attributes_so_far[key] = [attributes_so_far[key]]
attributes_so_far[key].append(value)
soup = BeautifulSoup(markup, 'html.parser', on_duplicate_attribute=accumulate)
soup.a['href']
# ["http://url1/", "http://url2/"]
(This is a new feature in Beautiful Soup 4.9.1.)
INSTANTIATING CUSTOM SUBCLASSES¶
When a parser tells Beautiful Soup about a tag or a string, Beautiful Soup will
instantiate a Tag or NavigableString object to contain that information. Instead
of that default behavior, you can tell Beautiful Soup to instantiate subclasses
of Tag or NavigableString, subclasses you define with custom behavior:
from bs4 import Tag, NavigableString
class MyTag(Tag):
pass
class MyString(NavigableString):
pass
markup = "<div>some text</div>"
soup = BeautifulSoup(markup, 'html.parser')
isinstance(soup.div, MyTag)
# False
isinstance(soup.div.string, MyString)
# False
my_classes = { Tag: MyTag, NavigableString: MyString }
soup = BeautifulSoup(markup, 'html.parser', element_classes=my_classes)
isinstance(soup.div, MyTag)
# True
isinstance(soup.div.string, MyString)
# True
This can be useful when incorporating Beautiful Soup into a test framework.
(This is a new feature in Beautiful Soup 4.8.1.)
TROUBLESHOOTING¶
DIAGNOSE()¶
If you’re having trouble understanding what Beautiful Soup does to a document,
pass the document into the diagnose() function. (New in Beautiful Soup 4.2.0.)
Beautiful Soup will print out a report showing you how different parsers handle
the document, and tell you if you’re missing a parser that Beautiful Soup could
be using:
from bs4.diagnose import diagnose
with open("bad.html") as fp:
data = fp.read()
diagnose(data)
# Diagnostic running on Beautiful Soup 4.2.0
# Python version 2.7.3 (default, Aug 1 2012, 05:16:07)
# I noticed that html5lib is not installed. Installing it may help.
# Found lxml version 2.3.2.0
#
# Trying to parse your data with html.parser
# Here's what html.parser did with the document:
# ...
Just looking at the output of diagnose() may show you how to solve the problem.
Even if not, you can paste the output of diagnose() when asking for help.
ERRORS WHEN PARSING A DOCUMENT¶
There are two different kinds of parse errors. There are crashes, where you feed
a document to Beautiful Soup and it raises an exception, usually an
HTMLParser.HTMLParseError. And there is unexpected behavior, where a Beautiful
Soup parse tree looks a lot different than the document used to create it.
Almost none of these problems turn out to be problems with Beautiful Soup. This
is not because Beautiful Soup is an amazingly well-written piece of software.
It’s because Beautiful Soup doesn’t include any parsing code. Instead, it relies
on external parsers. If one parser isn’t working on a certain document, the best
solution is to try a different parser. See Installing a parser for details and a
parser comparison.
The most common parse errors are HTMLParser.HTMLParseError: malformed start tag
and HTMLParser.HTMLParseError: bad end tag. These are both generated by Python’s
built-in HTML parser library, and the solution is to install lxml or html5lib.
The most common type of unexpected behavior is that you can’t find a tag that
you know is in the document. You saw it going in, but find_all() returns [] or
find() returns None. This is another common problem with Python’s built-in HTML
parser, which sometimes skips tags it doesn’t understand. Again, the best
solution is to install lxml or html5lib.
VERSION MISMATCH PROBLEMS¶
* SyntaxError: Invalid syntax (on the line ROOT_TAG_NAME = '[document]'):
Caused by running an old Python 2 version of Beautiful Soup under Python 3,
without converting the code.
* ImportError: No module named HTMLParser - Caused by running an old Python 2
version of Beautiful Soup under Python 3.
* ImportError: No module named html.parser - Caused by running the Python 3
version of Beautiful Soup under Python 2.
* ImportError: No module named BeautifulSoup - Caused by running Beautiful Soup
3 code on a system that doesn’t have BS3 installed. Or, by writing Beautiful
Soup 4 code without knowing that the package name has changed to bs4.
* ImportError: No module named bs4 - Caused by running Beautiful Soup 4 code on
a system that doesn’t have BS4 installed.
PARSING XML¶
By default, Beautiful Soup parses documents as HTML. To parse a document as XML,
pass in “xml” as the second argument to the BeautifulSoup constructor:
soup = BeautifulSoup(markup, "xml")
You’ll need to have lxml installed.
OTHER PARSER PROBLEMS¶
* If your script works on one computer but not another, or in one virtual
environment but not another, or outside the virtual environment but not
inside, it’s probably because the two environments have different parser
libraries available. For example, you may have developed the script on a
computer that has lxml installed, and then tried to run it on a computer that
only has html5lib installed. See Differences between parsers for why this
matters, and fix the problem by mentioning a specific parser library in the
BeautifulSoup constructor.
* Because HTML tags and attributes are case-insensitive, all three HTML parsers
convert tag and attribute names to lowercase. That is, the markup <TAG></TAG>
is converted to <tag></tag>. If you want to preserve mixed-case or uppercase
tags and attributes, you’ll need to parse the document as XML.
MISCELLANEOUS¶
* UnicodeEncodeError: 'charmap' codec can't encode character '\xfoo' in
position bar (or just about any other UnicodeEncodeError) - This problem
shows up in two main situations. First, when you try to print a Unicode
character that your console doesn’t know how to display. (See this page on
the Python wiki for help.) Second, when you’re writing to a file and you pass
in a Unicode character that’s not supported by your default encoding. In this
case, the simplest solution is to explicitly encode the Unicode string into
UTF-8 with u.encode("utf8").
* KeyError: [attr] - Caused by accessing tag['attr'] when the tag in question
doesn’t define the attr attribute. The most common errors are KeyError:
'href' and KeyError: 'class'. Use tag.get('attr') if you’re not sure attr is
defined, just as you would with a Python dictionary.
* AttributeError: 'ResultSet' object has no attribute 'foo' - This usually
happens because you expected find_all() to return a single tag or string. But
find_all() returns a _list_ of tags and strings–a ResultSet object. You need
to iterate over the list and look at the .foo of each one. Or, if you really
only want one result, you need to use find() instead of find_all().
* AttributeError: 'NoneType' object has no attribute 'foo' - This usually
happens because you called find() and then tried to access the .foo`
attribute of the result. But in your case, find() didn’t find anything, so it
returned None, instead of returning a tag or a string. You need to figure out
why your find() call isn’t returning anything.
* AttributeError: 'NavigableString' object has no attribute 'foo' - This
usually happens because you’re treating a string as though it were a tag. You
may be iterating over a list, expecting that it contains nothing but tags,
when it actually contains both tags and strings.
IMPROVING PERFORMANCE¶
Beautiful Soup will never be as fast as the parsers it sits on top of. If
response time is critical, if you’re paying for computer time by the hour, or if
there’s any other reason why computer time is more valuable than programmer
time, you should forget about Beautiful Soup and work directly atop lxml.
That said, there are things you can do to speed up Beautiful Soup. If you’re not
using lxml as the underlying parser, my advice is to start. Beautiful Soup
parses documents significantly faster using lxml than using html.parser or
html5lib.
You can speed up encoding detection significantly by installing the cchardet
library.
Parsing only part of a document won’t save you much time parsing the document,
but it can save a lot of memory, and it’ll make searching the document much
faster.
TRANSLATING THIS DOCUMENTATION¶
New translations of the Beautiful Soup documentation are greatly appreciated.
Translations should be licensed under the MIT license, just like Beautiful Soup
and its English documentation are.
There are two ways of getting your translation into the main code base and onto
the Beautiful Soup website:
1. Create a branch of the Beautiful Soup repository, add your translation, and
propose a merge with the main branch, the same as you would do with a
proposed change to the source code.
2. Send a message to the Beautiful Soup discussion group with a link to your
translation, or attach your translation to the message.
Use the Chinese or Brazilian Portuguese translations as your model. In
particular, please translate the source file doc/source/index.rst, rather than
the HTML version of the documentation. This makes it possible to publish the
documentation in a variety of formats, not just HTML.
BEAUTIFUL SOUP 3¶
Beautiful Soup 3 is the previous release series, and is no longer being actively
developed. It’s currently packaged with all major Linux distributions:
$ apt-get install python-beautifulsoup
It’s also published through PyPi as BeautifulSoup.:
$ easy_install BeautifulSoup
$ pip install BeautifulSoup
You can also download a tarball of Beautiful Soup 3.2.0.
If you ran easy_install beautifulsoup or easy_install BeautifulSoup, but your
code doesn’t work, you installed Beautiful Soup 3 by mistake. You need to run
easy_install beautifulsoup4.
The documentation for Beautiful Soup 3 is archived online.
PORTING CODE TO BS4¶
Most code written against Beautiful Soup 3 will work against Beautiful Soup 4
with one simple change. All you should have to do is change the package name
from BeautifulSoup to bs4. So this:
from BeautifulSoup import BeautifulSoup
becomes this:
from bs4 import BeautifulSoup
* If you get the ImportError “No module named BeautifulSoup”, your problem is
that you’re trying to run Beautiful Soup 3 code, but you only have Beautiful
Soup 4 installed.
* If you get the ImportError “No module named bs4”, your problem is that you’re
trying to run Beautiful Soup 4 code, but you only have Beautiful Soup 3
installed.
Although BS4 is mostly backwards-compatible with BS3, most of its methods have
been deprecated and given new names for PEP 8 compliance. There are numerous
other renames and changes, and a few of them break backwards compatibility.
Here’s what you’ll need to know to convert your BS3 code and habits to BS4:
YOU NEED A PARSER¶
Beautiful Soup 3 used Python’s SGMLParser, a module that was deprecated and
removed in Python 3.0. Beautiful Soup 4 uses html.parser by default, but you can
plug in lxml or html5lib and use that instead. See Installing a parser for a
comparison.
Since html.parser is not the same parser as SGMLParser, you may find that
Beautiful Soup 4 gives you a different parse tree than Beautiful Soup 3 for the
same markup. If you swap out html.parser for lxml or html5lib, you may find that
the parse tree changes yet again. If this happens, you’ll need to update your
scraping code to deal with the new tree.
METHOD NAMES¶
* renderContents -> encode_contents
* replaceWith -> replace_with
* replaceWithChildren -> unwrap
* findAll -> find_all
* findAllNext -> find_all_next
* findAllPrevious -> find_all_previous
* findNext -> find_next
* findNextSibling -> find_next_sibling
* findNextSiblings -> find_next_siblings
* findParent -> find_parent
* findParents -> find_parents
* findPrevious -> find_previous
* findPreviousSibling -> find_previous_sibling
* findPreviousSiblings -> find_previous_siblings
* getText -> get_text
* nextSibling -> next_sibling
* previousSibling -> previous_sibling
Some arguments to the Beautiful Soup constructor were renamed for the same
reasons:
* BeautifulSoup(parseOnlyThese=...) -> BeautifulSoup(parse_only=...)
* BeautifulSoup(fromEncoding=...) -> BeautifulSoup(from_encoding=...)
I renamed one method for compatibility with Python 3:
* Tag.has_key() -> Tag.has_attr()
I renamed one attribute to use more accurate terminology:
* Tag.isSelfClosing -> Tag.is_empty_element
I renamed three attributes to avoid using words that have special meaning to
Python. Unlike the others, these changes are not backwards compatible. If you
used these attributes in BS3, your code will break on BS4 until you change them.
* UnicodeDammit.unicode -> UnicodeDammit.unicode_markup
* Tag.next -> Tag.next_element
* Tag.previous -> Tag.previous_element
These methods are left over from the Beautiful Soup 2 API. They’ve been
deprecated since 2006, and should not be used at all:
* Tag.fetchNextSiblings
* Tag.fetchPreviousSiblings
* Tag.fetchPrevious
* Tag.fetchPreviousSiblings
* Tag.fetchParents
* Tag.findChild
* Tag.findChildren
GENERATORS¶
I gave the generators PEP 8-compliant names, and transformed them into
properties:
* childGenerator() -> children
* nextGenerator() -> next_elements
* nextSiblingGenerator() -> next_siblings
* previousGenerator() -> previous_elements
* previousSiblingGenerator() -> previous_siblings
* recursiveChildGenerator() -> descendants
* parentGenerator() -> parents
So instead of this:
for parent in tag.parentGenerator():
...
You can write this:
for parent in tag.parents:
...
(But the old code will still work.)
Some of the generators used to yield None after they were done, and then stop.
That was a bug. Now the generators just stop.
There are two new generators, .strings and .stripped_strings. .strings yields
NavigableString objects, and .stripped_strings yields Python strings that have
had whitespace stripped.
XML¶
There is no longer a BeautifulStoneSoup class for parsing XML. To parse XML you
pass in “xml” as the second argument to the BeautifulSoup constructor. For the
same reason, the BeautifulSoup constructor no longer recognizes the isHTML
argument.
Beautiful Soup’s handling of empty-element XML tags has been improved.
Previously when you parsed XML you had to explicitly say which tags were
considered empty-element tags. The selfClosingTags argument to the constructor
is no longer recognized. Instead, Beautiful Soup considers any empty tag to be
an empty-element tag. If you add a child to an empty-element tag, it stops being
an empty-element tag.
ENTITIES¶
An incoming HTML or XML entity is always converted into the corresponding
Unicode character. Beautiful Soup 3 had a number of overlapping ways of dealing
with entities, which have been removed. The BeautifulSoup constructor no longer
recognizes the smartQuotesTo or convertEntities arguments. (Unicode, Dammit
still has smart_quotes_to, but its default is now to turn smart quotes into
Unicode.) The constants HTML_ENTITIES, XML_ENTITIES, and XHTML_ENTITIES have
been removed, since they configure a feature (transforming some but not all
entities into Unicode characters) that no longer exists.
If you want to turn Unicode characters back into HTML entities on output, rather
than turning them into UTF-8 characters, you need to use an output formatter.
MISCELLANEOUS¶
Tag.string now operates recursively. If tag A contains a single tag B and
nothing else, then A.string is the same as B.string. (Previously, it was None.)
Multi-valued attributes like class have lists of strings as their values, not
strings. This may affect the way you search by CSS class.
Tag objects now implement the __hash__ method, such that two Tag objects are
considered equal if they generate the same markup. This may change your script’s
behavior if you put Tag objects into a dictionary or set.
If you pass one of the find* methods both string and a tag-specific argument
like name, Beautiful Soup will search for tags that match your tag-specific
criteria and whose Tag.string matches your value for string. It will not find
the strings themselves. Previously, Beautiful Soup ignored the tag-specific
arguments and looked for strings.
The BeautifulSoup constructor no longer recognizes the markupMassage argument.
It’s now the parser’s responsibility to handle markup correctly.
The rarely-used alternate parser classes like ICantBelieveItsBeautifulSoup and
BeautifulSOAP have been removed. It’s now the parser’s decision how to handle
ambiguous markup.
The prettify() method now returns a Unicode string, not a bytestring.
TABLE OF CONTENTS
* Beautiful Soup Documentation
* Getting help
* Quick Start
* Installing Beautiful Soup
* Installing a parser
* Making the soup
* Kinds of objects
* Tag
* Name
* Attributes
* Multi-valued attributes
* NavigableString
* BeautifulSoup
* Comments and other special strings
* Navigating the tree
* Going down
* Navigating using tag names
* .contents and .children
* .descendants
* .string
* .strings and stripped_strings
* Going up
* .parent
* .parents
* Going sideways
* .next_sibling and .previous_sibling
* .next_siblings and .previous_siblings
* Going back and forth
* .next_element and .previous_element
* .next_elements and .previous_elements
* Searching the tree
* Kinds of filters
* A string
* A regular expression
* A list
* True
* A function
* find_all()
* The name argument
* The keyword arguments
* Searching by CSS class
* The string argument
* The limit argument
* The recursive argument
* Calling a tag is like calling find_all()
* find()
* find_parents() and find_parent()
* find_next_siblings() and find_next_sibling()
* find_previous_siblings() and find_previous_sibling()
* find_all_next() and find_next()
* find_all_previous() and find_previous()
* CSS selectors
* Modifying the tree
* Changing tag names and attributes
* Modifying .string
* append()
* extend()
* NavigableString() and .new_tag()
* insert()
* insert_before() and insert_after()
* clear()
* extract()
* decompose()
* replace_with()
* wrap()
* unwrap()
* smooth()
* Output
* Pretty-printing
* Non-pretty printing
* Output formatters
* get_text()
* Specifying the parser to use
* Differences between parsers
* Encodings
* Output encoding
* Unicode, Dammit
* Smart quotes
* Inconsistent encodings
* Line numbers
* Comparing objects for equality
* Copying Beautiful Soup objects
* Advanced parser customization
* Parsing only part of a document
* SoupStrainer
* Customizing multi-valued attributes
* Handling duplicate attributes
* Instantiating custom subclasses
* Troubleshooting
* diagnose()
* Errors when parsing a document
* Version mismatch problems
* Parsing XML
* Other parser problems
* Miscellaneous
* Improving Performance
* Translating this documentation
* Beautiful Soup 3
* Porting code to BS4
* You need a parser
* Method names
* Generators
* XML
* Entities
* Miscellaneous
THIS PAGE
* Show Source
QUICK SEARCH
NAVIGATION
* index
* Beautiful Soup 4.9.0 documentation »
* Beautiful Soup Documentation
© Copyright 2004-2020, Leonard Richardson. Created using Sphinx 3.1.2.