6/28/2023 0 Comments Beautifulsoup get plain textHtmlwords = ['https', 'http', 'display', 'button', 'hover', # Get text (clean html) using BeautifulSoup get_text method # Assign URL of the web page to be processed One can also create NLTK Text instance to use NLTK APIs such as FreqDist for creating frequency distribution.Once can then apply word filtering techniques to further filter different words meeting the criteria such as word length etc.NLTK.word_tokenize method can be used to retrieve words / punctuations once HTML text is obtained.Using NLTK.clean_html method throws exception message such as To remove HTML markup, use BeautifulSoup’s get_text() function. However, NLTK.clean_html method is deprecated in latest NLTK implementation. In some of the NLP books, NLTK.clean_html() method is suggested. Once the HTML is obtained using urlopen(html).read() method, the HTML text is obtained using get_text() method of BeautifulSoup.In this example, I have taken URL from CNN.com in relation to Trump returns from hospital to White house inspite of him suffering from Covid-19 and hospitalised for special care. URLLib request is used to read the html page associated with the given URL.Pay attention to some of the following in the code given below: Here is the Python code for extracting text from HTML pages and perform text analysis. Python Code for Extracting Text from HTML Pages Python Code for Extracting Text from HTML Pages._extract_blocks() function needs to be defined before to_plaintext(), as it is called from there.If the tag name matches one of our block elements, we will add it to the list.Inside the function, we recursively travel the element tree to find our block elements inside other elements (that are inside other elements and so on).The last thing is to define _extract_blocks() function that will take a root element and return all block elements that we are interested in: def _extract_blocks (parent_tag ) - > list : As _extract_blocks() will return a list of our block elements, we will take the text with get_text() function, strip them of left and right white space and concatenate together, separating them with a single new line.We called a helper function _extract_blocks(), passing it a root HTML element to work with – the HTML body.When initializing BeautifulSoup, we can choose which HTML parser will be used to parse the string, so we chose our installed lxml package.Soup = BeautifulSoup (html_text, features = "lxml" )Įxtracted_blocks = _extract_blocks (soup. Our main function to_plaintext(html_text: str) -> str will take a string with the HTML source and return a concatenated string of all texts from our selected blocks: def to_plaintext (html_text : str ) - > str : I have picked p for paragraphs, h1-h5 for headings and blockquote for quotes as an example: from bs4 import BeautifulSoupīlocks = Now we will import Beautiful Soup’s classes for working with HTML: BeautifulSoup for parsing the source and Tag which we are going to use for checking whether a particular element in the parsed BeautifulSoup tree represents an HTML tag.īesides the necessary imports, we will also define a list of block elements that we want to extract the text from. So to start off, let’s install beautifulsoup4 package and lxml parser (this is a fast parser that can be used together with BS): # install using pip We will do it with Python and Beautiful Soup 4, a Python library for scraping information from web pages. In this article I will demonstrate a simple way to grab all text content from the HTML source so that we end up with a concatenated string of all texts on the page. There are many different ways to extract plain text from HTML and some are better than others depending on what we want to extract and if we know where to find it. Articles About me How to extract plain text from an HTML page in Python
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