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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.
The examples in this documentation should work the same way in Python 2.7 and Python 3.2.
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 Beautiful Soup 4 is recommended for all new projects. If you want to learn about the differences between Beautiful Soup 3 and Beautiful Soup 4, see Porting code to BS4.
Note
It is not possible to install custom parsers in Pythonista, so the information about that has been removed from this documentation to avoid confusion.
If you have questions about Beautiful Soup, or run into problems, send mail to the discussion group.
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>
<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)
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="link2">
# 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.
To parse a document, pass it into the BeautifulSoup
constructor. You can pass in a string or an open filehandle:
from bs4 import BeautifulSoup
soup = BeautifulSoup(open("index.html"))
soup = BeautifulSoup("<html>data</html>")
First, the document is converted to Unicode, and HTML entities are converted to Unicode characters:
BeautifulSoup("Sacré bleu!")
<html><head></head><body>Sacré bleu!</body></html>
Beautiful Soup then parses the document using the best available parser.
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¶A Tag object corresponds to an XML or HTML tag in the original document:
soup = BeautifulSoup('<b class="boldest">Extremely bold</b>')
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.
Every tag has a name, accessible as .name:
tag.name
# u'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>
A tag may have any number of attributes. The tag <b
class="boldest"> has an attribute “class” whose value is
“boldest”. You can access a tag’s attributes by treating the tag like
a dictionary:
tag['class']
# u'boldest'
You can access that dictionary directly as .attrs:
tag.attrs
# {u'class': u'boldest'}
You can add, remove, and modify a tag’s attributes. Again, this is done by treating the tag as a dictionary:
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>
tag['class']
# KeyError: 'class'
print(tag.get('class'))
# None
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 strikeout"></p>')
css_soup.p['class']
# ["body", "strikeout"]
css_soup = BeautifulSoup('<p class="body"></p>')
css_soup.p['class']
# ["body"]
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>')
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>')
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>
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']
# u'body strikeout'
BeautifulSoup¶The BeautifulSoup object itself represents the 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.
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
# u'[document]'
Tag, NavigableString, and BeautifulSoup cover almost
everything you’ll see in an HTML or XML file, but there are a few
leftover bits. The only one you’ll probably ever need to worry about
is the comment:
markup = "<b><!--Hey, buddy. Want to buy a used parser?--></b>"
soup = BeautifulSoup(markup)
comment = soup.b.string
type(comment)
# <class 'bs4.element.Comment'>
The Comment object is just a special type of NavigableString:
comment
# u'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 defines classes for anything else that might show up in
an XML document: CData, ProcessingInstruction,
Declaration, and Doctype. Just 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>
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.
.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
# [u'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
# u'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
.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))
# 25
.string¶If a tag has only one child, and that child is a NavigableString,
the child is made available as .string:
title_tag.string
# u'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
# u'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))
# u"The Dormouse's story"
# u'\n\n'
# u"The Dormouse's story"
# u'\n\n'
# u'Once upon a time there were three little sisters; and their names were\n'
# u'Elsie'
# u',\n'
# u'Lacie'
# u' and\n'
# u'Tillie'
# u';\nand they lived at the bottom of a well.'
# u'\n\n'
# u'...'
# u'\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))
# u"The Dormouse's story"
# u"The Dormouse's story"
# u'Once upon a time there were three little sisters; and their names were'
# u'Elsie'
# u','
# u'Lacie'
# u'and'
# u'Tillie'
# u';\nand they lived at the bottom of a well.'
# u'...'
Here, strings consisting entirely of whitespace are ignored, and whitespace at the beginning and end of strings is removed.
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:
if parent is None:
print(parent)
else:
print(parent.name)
# p
# body
# html
# [document]
# None
Consider a simple document like this:
sibling_soup = BeautifulSoup("<a><b>text1</b><c>text2</c></b></a>")
print(sibling_soup.prettify())
# <html>
# <body>
# <a>
# <b>
# text1
# </b>
# <c>
# text2
# </c>
# </a>
# </body>
# </html>
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
# u'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
# u',\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))
# u',\n'
# <a class="sister" href="http://example.com/lacie" id="link2">Lacie</a>
# u' and\n'
# <a class="sister" href="http://example.com/tillie" id="link3">Tillie</a>
# u'; and they lived at the bottom of a well.'
# None
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>
# u',\n'
# <a class="sister" href="http://example.com/elsie" id="link1">Elsie</a>
# u'Once upon a time there were three little sisters; and their names were\n'
# None
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
# '; and 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
# u'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
# u' 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))
# u'Tillie'
# u';\nand they lived at the bottom of a well.'
# u'\n\n'
# <p class="story">...</p>
# u'...'
# u'\n'
# None
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 explain
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>
<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)
By passing in a filter to an argument like find_all(), you can
isolate whatever parts of the document you’re interested.
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.
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.
If you pass in a regular expression object, Beautiful Soup will filter
against that regular expression using its match() 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
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
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_key('class') and not tag.has_key('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...</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”.
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
# p
# a
# a
# a
# p
Now we’re ready to look at the search methods in detail.
find_all()¶Signature: find_all(name, attrs, recursive, text, 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(text=re.compile("sisters"))
# u'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 text, 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().
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.
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 that have an id attribute, 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">three</a>]
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>')
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")
# []
There’s a shortcut for class_ present in all versions of Beautiful
Soup. The second argument to any find()-type method is called
attrs, and passing in a string for attrs will search for that
string as a CSS class:
soup.find_all("a", "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>]
You can also pass in a regular expression, a function or
True—anything except a dictionary. Whatever you pass in will be
used to search against the CSS class, the same as if you’d passed it
in for the class_ keyword argument:
soup.find_all("p", re.compile("itl"))
# [<p class="title"><b>The Dormouse's story</b></p>]
By passing in a dictionary to attrs, you can search many HTML
attributes at once, not just the CSS class. These two lines of code
are equivalent:
soup.find_all(href=re.compile("elsie"), id='link1')
soup.find_all(attrs={'href' : re.compile("elsie"), 'id': 'link1'})
This isn’t a very useful feature, since it’s usually easier to use the keyword arguments.
text argument¶With text 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(text="Elsie")
# [u'Elsie']
soup.find_all(text=["Tillie", "Elsie", "Lacie"])
# [u'Elsie', u'Lacie', u'Tillie']
soup.find_all(text=re.compile("Dormouse"))
[u"The Dormouse's story", u"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(text=is_the_only_string_within_a_tag)
# [u"The Dormouse's story", u"The Dormouse's story", u'Elsie', u'Lacie', u'Tillie', u'...']
Although text 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 text. This code finds the <a>
tags whose .string is “Elsie”:
soup.find_all("a", text="Elsie")
# [<a href="http://example.com/elsie" class="sister" id="link1">Elsie</a>]
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>]
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, text, 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.
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(text=True)
soup.title(text=True)
find()¶Signature: find(name, attrs, recursive, text, **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()¶Signature: find_parents(name, attrs, text, limit, **kwargs)
Signature: find_parent(name, attrs, text, **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(text="Lacie")
a_string
# u'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()¶Signature: find_next_siblings(name, attrs, text, limit, **kwargs)
Signature: find_next_sibling(name, attrs, text, **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()¶Signature: find_previous_siblings(name, attrs, text, limit, **kwargs)
Signature: find_previous_sibling(name, attrs, text, **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()¶Signature: find_all_next(name, attrs, text, limit, **kwargs)
Signature: find_next(name, attrs, text, **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(text=True)
# [u'Elsie', u',\n', u'Lacie', u' and\n', u'Tillie',
# u';\nand they lived at the bottom of a well.', u'\n\n', u'...', u'\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()¶Signature: find_all_previous(name, attrs, text, limit, **kwargs)
Signature: find_previous(name, attrs, text, **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.
Beautiful Soup supports a subset of the CSS selector standard. Just construct the
selector as a string and pass it into the .select() method of a
Tag or the BeautifulSoup object itself.
You can find tags:
soup.select("title")
# [<title>The Dormouse's story</title>]
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("body > 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>]
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>]
Match language codes:
multilingual_markup = """
<p lang="en">Hello</p>
<p lang="en-us">Howdy, y'all</p>
<p lang="en-gb">Pip-pip, old fruit</p>
<p lang="fr">Bonjour mes amis</p>
"""
multilingual_soup = BeautifulSoup(multilingual_markup)
multilingual_soup.select('p[lang|=en]')
# [<p lang="en">Hello</p>,
# <p lang="en-us">Howdy, y'all</p>,
# <p lang="en-gb">Pip-pip, old fruit</p>]
This is a convenience for users who know the CSS selector syntax. You can do all this stuff with the Beautiful Soup API. And if CSS selectors are all you need, you might as well use lxml directly, because it’s faster. But this lets you combine simple CSS selectors with the Beautiful Soup API.
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.
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>')
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>
.string¶If you set a tag’s .string attribute, the tag’s contents are
replaced with the string you give:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup)
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>")
soup.a.append("Bar")
soup
# <html><head></head><body><a>FooBar</a></body></html>
soup.a.contents
# [u'Foo', u'Bar']
BeautifulSoup.new_string() 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 factory method
BeautifulSoup.new_string():
soup = BeautifulSoup("<b></b>")
tag = soup.b
tag.append("Hello")
new_string = soup.new_string(" there")
tag.append(new_string)
tag
# <b>Hello there.</b>
tag.contents
# [u'Hello', u' there']
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>")
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)
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
# [u'I linked to ', u'but did not endorse', <i>example.com</i>]
insert_before() and insert_after()¶The insert_before() method inserts a tag or string immediately
before something else in the parse tree:
soup = BeautifulSoup("<b>stop</b>")
tag = soup.new_tag("i")
tag.string = "Don't"
soup.b.string.insert_before(tag)
soup.b
# <b><i>Don't</i>stop</b>
The insert_after() method moves a tag or string so that it
immediately follows something else in the parse tree:
soup.b.i.insert_after(soup.new_string(" ever "))
soup.b
# <b><i>Don't</i> ever stop</b>
soup.b.contents
# [<i>Don't</i>, u' ever ', u'stop']
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)
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)
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
# u'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)
a_tag = soup.a
soup.i.decompose()
a_tag
# <a href="http://example.com/">I linked to</a>
replace_with()¶PageElement.replace_with() removes a tag or string from the tree,
and replaces it with the tag or string of your choice:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup)
a_tag = soup.a
new_tag = soup.new_tag("b")
new_tag.string = "example.net"
a_tag.i.replace_with(new_tag)
a_tag
# <a href="http://example.com/">I linked to <b>example.net</b></a>
replace_with() returns the tag or string that was replaced, so
that you can examine it or add it back to another part of the tree.
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>")
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)
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.
(In earlier versions of Beautiful Soup, unwrap() was called
replace_with_children(), and that name will still work.)
The prettify() method will turn a Beautiful Soup parse tree into a
nicely formatted Unicode string, with each HTML/XML tag on its own line:
markup = '<a href="http://example.com/">I linked to <i>example.com</i></a>'
soup = BeautifulSoup(markup)
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>
If you just want a string, with no fancy formatting, you can call
unicode() or str() on a BeautifulSoup object, or 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>'
unicode(soup.a)
# u'<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.
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.")
unicode(soup)
# u'<html><head></head><body>\u201cDammit!\u201d he said.</body></html>'
If you then convert the document to a string, the Unicode characters will be encoded as UTF-8. You won’t get the HTML entities back:
str(soup)
# '<html><head></head><body>\xe2\x80\x9cDammit!\xe2\x80\x9d he said.</body></html>'
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>")
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>')
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 four 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)
print(soup.prettify(formatter="minimal"))
# <html>
# <body>
# <p>
# Il a dit <<Sacré bleu!>>
# </p>
# </body>
# </html>
If you pass in formatter="html", Beautiful Soup will convert
Unicode characters to HTML entities whenever possible:
print(soup.prettify(formatter="html"))
# <html>
# <body>
# <p>
# Il a dit <<Sacré bleu!>>
# </p>
# </body>
# </html>
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))
# <html>
# <body>
# <p>
# Il a dit <<Sacré bleu!>>
# </p>
# </body>
# </html>
link_soup = BeautifulSoup('<a href="http://example.com/?foo=val1&bar=val2">A link</a>')
print(link_soup.a.encode(formatter=None))
# <a href="http://example.com/?foo=val1&bar=val2">A link</a>
Finally, if you pass in a function for formatter, Beautiful Soup
will call that function once for every string and attribute value in
the document. You can do whatever you want in this function. Here’s a
formatter that converts strings to uppercase and does absolutely
nothing else:
def uppercase(str):
return str.upper()
print(soup.prettify(formatter=uppercase))
# <html>
# <body>
# <p>
# IL A DIT <<SACRÉ BLEU!>>
# </p>
# </body>
# </html>
print(link_soup.a.prettify(formatter=uppercase))
# <a href="HTTP://EXAMPLE.COM/?FOO=VAL1&BAR=VAL2">
# A LINK
# </a>
If you’re writing your own function, you should know about the
EntitySubstitution class in the bs4.dammit module. This class
implements Beautiful Soup’s standard formatters as class methods: the
“html” formatter is EntitySubstitution.substitute_html, and the
“minimal” formatter is EntitySubstitution.substitute_xml. You can
use these functions to simulate formatter=html or
formatter==minimal, but then do something extra.
Here’s an example that replaces Unicode characters with HTML entities whenever possible, but also converts all strings to uppercase:
from bs4.dammit import EntitySubstitution
def uppercase_and_substitute_html_entities(str):
return EntitySubstitution.substitute_html(str.upper())
print(soup.prettify(formatter=uppercase_and_substitute_html_entities))
# <html>
# <body>
# <p>
# IL A DIT <<SACRÉ BLEU!>>
# </p>
# </body>
# </html>
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 the formatter method, just in
case you’ve written a custom method 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>”) soup.a.string = CData(“one < three”) print(soup.a.prettify(formatter=”xml”)) # <a> # <![CDATA[one < three]]> # </a>
get_text()¶If you only want the text part of 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)
soup.get_text()
u'\nI linked to example.com\n'
soup.i.get_text()
u'example.com'
You can specify a string to be used to join the bits of text together:
# soup.get_text("|")
u'\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)
u'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]
# [u'I linked to', u'example.com']
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:
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.
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:
BeautifulSoup("<a><b /></a>")
# <html><head></head><body><a><b></b></a></body></html>
Since an empty <b /> tag is not valid HTML, the 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 empty <b /> tag is left alone, and that the document is given an XML declaration instead of being put into an <html> tag.:
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 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. This parser also adds an empty <head> tag to the document.
Here’s the same document parsed with Python’s built-in HTML parser:
BeautifulSoup("<a></p>", "html.parser")
# <a></a>
Like html5lib, this parser ignores the closing </p> tag. Unlike html5lib, this parser makes no attempt to create a well-formed HTML document by adding a <body> tag. Unlike lxml, it doesn’t even bother to add an <html> tag.
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.
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)
soup.h1
# <h1>Sacré bleu!</h1>
soup.h1.string
# u'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 good lock on it, and misidentifies it as ISO-8859-7:
markup = b"<h1>\xed\xe5\xec\xf9</h1>"
soup = BeautifulSoup(markup)
soup.h1
<h1>νεμω</h1>
soup.original_encoding
'ISO-8859-7'
We can fix this by passing in the correct from_encoding:
soup = BeautifulSoup(markup, from_encoding="iso-8859-8")
soup.h1
<h1>םולש</h1>
soup.original_encoding
'iso8859-8'
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.
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)
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")
# '<p>Sacr\xe9 bleu!</p>'
soup.p.encode("utf-8")
# '<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)
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>
print tag.encode("latin-1")
# <b>☃</b>
print tag.encode("ascii")
# <b>☃</b>
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'
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.
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
# u'<p>I just “love” Microsoft Word’s smart quotes</p>'
UnicodeDammit(markup, ["windows-1252"], smart_quotes_to="xml").unicode_markup
# u'<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
# u'<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
# u'<p>I just \u201clove\u201d Microsoft Word\u2019s smart quotes</p>'
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.
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, text, 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 len(string) < 10
only_short_strings = SoupStrainer(text=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>
<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)
soup.find_all(only_short_strings)
# [u'\n\n', u'\n\n', u'Elsie', u',\n', u'Lacie', u' and\n', u'Tillie',
# u'\n\n', u'...', u'\n']
SyntaxError: Invalid syntax (on the line ROOT_TAG_NAME =
u'[document]'): Caused by running the Python 2 version of
Beautiful Soup under Python 3, without converting the code.ImportError: No module named HTMLParser - Caused by running the
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.BeautifulSoup constructor.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.UnicodeEncodeError: 'charmap' codec can't encode character
u'\xfoo' in position bar (or just about any other
UnicodeEncodeError) - This is not a problem with Beautiful Soup.
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").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.
You can speed up encoding detection significantly by installing the cchardet library.
Sometimes Unicode, Dammit can only detect the encoding of a file by
doing a byte-by-byte examination of the file. This slows Beautiful
Soup to a crawl. My tests indicate that this only happened on 2.x
versions of Python, and that it happened most often with documents
using Russian or Chinese encodings. If this is happening to you, you
can fix it by installing cchardet, or by using Python 3 for your
script. If you happen to know a document’s encoding, you can pass
it into the BeautifulSoup constructor as from_encoding, and
bypass encoding detection altogether.
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.
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. If your first language is Chinese, it might be easier for you to read the Chinese translation of the Beautiful Soup 3 documentation, then read this document to find out about the changes made in Beautiful Soup 4.
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
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.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:
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.
Since html.parser is not the same parser as SGMLParser, it
will treat invalid markup differently. Usually the “difference” is
that html.parser crashes. In that case, you’ll need to install
another parser. But sometimes html.parser just creates a different
parse tree than SGMLParser would. If this happens, you may need to
update your BS3 scraping code to deal with the new tree.
renderContents -> encode_contentsreplaceWith -> replace_withreplaceWithChildren -> unwrapfindAll -> find_allfindAllNext -> find_all_nextfindAllPrevious -> find_all_previousfindNext -> find_nextfindNextSibling -> find_next_siblingfindNextSiblings -> find_next_siblingsfindParent -> find_parentfindParents -> find_parentsfindPrevious -> find_previousfindPreviousSibling -> find_previous_siblingfindPreviousSiblings -> find_previous_siblingsnextSibling -> next_siblingpreviousSibling -> previous_siblingSome 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_elementI 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_markupTag.next -> Tag.next_elementTag.previous -> Tag.previous_elementI gave the generators PEP 8-compliant names, and transformed them into properties:
childGenerator() -> childrennextGenerator() -> next_elementsnextSiblingGenerator() -> next_siblingspreviousGenerator() -> previous_elementspreviousSiblingGenerator() -> previous_siblingsrecursiveChildGenerator() -> descendantsparentGenerator() -> parentsSo 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.
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.
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.
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.
If you pass one of the find* methods both text 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 text. 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.