).
The tag argument is the name of the tag converted to lower case. The attrs
argument is a list of (name, value) pairs containing the attributes found
inside the tag’s <> brackets. The name will be translated to lower case,
and quotes in the value have been removed, and character and entity references
have been replaced.
For instance, for the tag ‘)
Decl: DOCTYPE HTML PUBLIC “-//W3C//DTD HTML 4. 01//EN” ”
Parsing an element with a few attributes and a title:
>>> (‘‘)
Start tag: img
attr: (‘src’, ”)
attr: (‘alt’, ‘The Python logo’)
>>>
>>> (‘

Python

‘)
Start tag: h1
Data: Python
End tag: h1
The content of script and style elements is returned as is, without
further parsing:
>>> (‘

‘)
Start tag: style
attr: (‘type’, ‘text/css’)
Data: #python { color: green}
End tag: style
>>> (‘‘)
Start tag: script
attr: (‘type’, ‘text/javascript’)
Data: alert(“hello! “);
End tag: script
Parsing comments:
>>> (‘‘… ‘IE-specific content‘)
Comment: a comment
Comment: [if IE 9]>IE-specific content‘):
>>> (‘>>>’)
Named ent: >
Num ent: >
Feeding incomplete chunks to feed() works, but
handle_data() might be called more than once
(unless convert_charrefs is set to True):
>>> for chunk in [‘buff’, ‘ered ‘, ‘text‘]:… (chunk)…
Start tag: span
Data: buff
Data: ered
Data: text
End tag: span
Parsing invalid HTML (e. unquoted attributes) also works:
>>> (‘

tag soup

‘)
Start tag: p
Start tag: a
attr: (‘class’, ‘link’)
attr: (‘href’, ‘#main’)
Data: tag soup
End tag: p
End tag: a

HTMLParser in Python 3.x – AskPython

provides a very simple and efficient way for coders to read through HTML code. This library comes pre-installed in the stdlib. This simplifies our interfacing with the HTMLParser library as we do not need to install additional packages from the Python Package Index (PyPI) for the same is HTMLParser? Essentially, HTMLParser lets us understand HTML code in a nested fashion. The module has methods that are automatically called when specific HTML elements are met with. It simplifies HTML tags and data fed with HTML data, the tag reads through it one tag at a time, going from start tags to the tags within, then the end tags and so to Use HTMLParser? HTMLParser only identifies the tags or data for us but does not output any data when something is identified. We need to add functionality to the methods before they can output the information they if we need to add functionality, what’s the use of the HTMLParser? This module saves us the time of creating the functionality of identifying tags ’re not going to code how to identify the tags, only what to do once they’re identified. Understood? Great! Now let’s get into creating a parser for ourselves! Subclassing the HTMLParserHow can we add functionality to the HTMLParser methods? By subclassing. Also identified as Inheritance, we create a class that retains the behavior of HTMLParser, while adding more bclassing lets us override the default functionality of a method (which in our case, is to return nothing when tags are identified) and add some better functions instead. Let’s see how to work with the HTMLParser nding Names of The Called MethodsThere are many methods available within the module. We’ll go over the ones you’d need frequently and then learn how to make use of MLParser. handle_starttag(tag, attrs) – Called when start tags are found (example , , )HTMLParser. handle_endtag(tag) – Called when end tags are found (example , , )HTMLParser. handle_data(data) – Called when data is found (example data )HTMLParser. handle_comment(data) – Called when comments are found (example )HTMLParser. handle_decl(decl) – Called when declarations are found (example )Creating Your HTMLParserLet’s define basic print functionalities to the methods in the HTMLParser module. In the below example, all I’m doing is adding a print method whenever the method is last line in the code is where we feed data to the parser. I fed basic HTML code directly, but you can do the same by using the urllib module to directly import a website into python import HTMLParser
class Parse(HTMLParser):
def __init__(self):
#Since Python 3, we need to call the __init__() function
#of the parent class
super(). __init__()
()
#Defining what the methods should output when called by HTMLParser.
def handle_starttag(self, tag, attrs):
print(“Start tag: “, tag)
for a in attrs:
print(“Attributes of the tag: “, a)
def handle_data(self, data):
print(“Here’s the data: “, data)
def handle_endtag(self, tag):
print(“End tag: “, tag)
testParser = Parse()
(““)
HTMLParser OutputWhat Can HTMLParser Be Used For? Web data is what most people would need the HTMLParser module for. Not to say that it cannot be used for anything else, but when you need to read loads of websites and find specific information, this module will make the task a cakewalk for MLParser Real World ExampleI’m going to pull every single link from the Python Wikipedia page for this it manually, by right-clicking on a link, copying and pasting it in a word file, and then moving on to the next is possible too. But that would take hours if there are lots of links on the page which is a typical situation with Wikipedia we’ll be spending 5 minutes to code an HTMLParser and get the time needed to finish the task from hours to a few seconds. Let’s do it! from import HTMLParser
import quest
#Import HTML from a URL
url = quest. urlopen(“(programming_language)”)
html = ()()
#Since Python 3, we need to call the __init__() function of the parent class
#Defining what the method should output when called by HTMLParser.
# Only parse the ‘anchor’ tag.
if tag == “a”:
for name, link in attrs:
if name == “href” and artswith(“”):
print (link)
p = Parse()
(html)
Python HTMLParser Web ScaperThe Python programming page on Wikipedia has more than 300 links. I’m sure it would have taken me at least an hour to make sure we had all of them. But with this simple script, it took <5 seconds to output every single link without missing any of them! ConclusionThis module is really fun to play around with. We ended up scraping tons of data from the web using this simple module in the process of writing this there are other modules like BeautifulSoup which are more well known. But for quick and simple tasks, HTMLParser does a really amazing job!

HTML Parser: How to scrape HTML content | Python Central

”
This article is part of in the series
Published: Tuesday 25th July 2017
Last Updated: Monday 6th April 2020
Prerequisites
Knowledge of the following is required:
Python 3
Basic HTML
Urllib2 (not mandatory but recommended)
Basic OOP concepts
Python data structures – Lists, Tuples
Why parse HTML?
Python is one of the languages that is extensively used to scrape data from web pages. This is a very easy way to gather information. For instance, it can be very helpful for quickly extracting all the links in a web page and checking for their validity. This is only one example of many potential uses… so read on!
The next question is: where is this information extracted from? To answer this, let’s use an example. Go to the website NYTimes and right click on the page. Select View page source or simply press the keys Ctrl + u on your keyboard. A new page opens containing a number of links, HTML tags, and content. This is the source from which the HTML Parser scrapes content for NYTimes!
What is HTML Parser?
HTML Parser, as the name suggests, simply parses a web page’s HTML/XHTML content and provides the information we are looking for. This is a class that is defined with various methods that can be overridden to suit our requirements. Note that to use HTML Parser, the web page must be fetched. For this reason, HTML Parser is often used with urllib2.
To use the HTML Parser, you have to import this module:
from import HTMLParser
Methods in HTML Parser
(data) – It is through this method that the HTML Parser reads data. This method accepts data in both unicode and string formats. It keeps processing data as it gets and waits for incomplete data to be buffered. Only after the data is fed using this method can other methods of the HTML Parser be called.
() – This method is called to mark the end of the input feed to the HTML Parser.
() – This method resets the instance and all unprocessed data is lost.
HTMLParser. handle_starttag(tag, attrs) – This method deals with the start tags only, like ‘)
Print one output at a time to avoid crashing as you are dealing with a lot of data!
NOTE: In case you get the error: IDLE cannot start the process, start your Python IDLE in administrator mode. This should solve the problem.
Exceptions
MLParseError – This exception is raised when the HTML Parser encounters corrupt data. This exception gives information in the form of three attributes. The msg attribute tells you the reason for the error, the lineno attribute specifies the line number where the error occurred and the offset attribute gives the exact character where the construct starts.
Conclusion
That brings us to the end of this article on HTML Parser. Be sure to try out more examples on your own to improve your understanding! Should you have the need for an out of the box email parser or a pdf table parsing solution, our sister sites have that for you until you get your python mojo in order. Do read about BeautifulSoup which is another amazing module in Python that helps in HTML scraping. However, to use this module, you will have to install it. Keep learning and happy Pythoning!
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Frequently Asked Questions about python 3 html parser

How do I parse HTML in Python?

Examplefrom html. parser import HTMLParser.class Parser(HTMLParser):# method to append the start tag to the list start_tags.def handle_starttag(self, tag, attrs):global start_tags.start_tags. append(tag)# method to append the end tag to the list end_tags.def handle_endtag(self, tag):More items…

Which Python library did we use to parse HTML?

Beautiful Soup (bs4) is a Python library that is used to parse information out of HTML or XML files. It parses its input into an object on which you can run a variety of searches. To start parsing an HTML file, import the Beautiful Soup library and create a Beautiful Soup object as shown in the following code example.Jan 7, 2021

What does an HTML parser do?

HTML parsing involves tokenization and tree construction. HTML tokens include start and end tags, as well as attribute names and values. If the document is well-formed, parsing it is straightforward and faster. The parser parses tokenized input into the document, building up the document tree.Oct 7, 2021