============ HTML to Text

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Extract text from HTML

• Free software: MIT license

How is html_text different from .xpath('//text()') from LXML or .get_text() from Beautiful Soup?

• Text extracted with html_text does not contain inline styles, javascript, comments and other text that is not normally visible to users;
• html_text normalizes whitespace, but in a way smarter than .xpath('normalize-space()), adding spaces around inline elements (which are often used as block elements in html markup), and trying to avoid adding extra spaces for punctuation;
• html-text can add newlines (e.g. after headers or paragraphs), so that the output text looks more like how it is rendered in browsers.

Install

Install with pip::

pip install html-text

The package depends on lxml, so you might need to install additional packages: http://lxml.de/installation.html

Usage

Extract text from HTML::

>>> import html_text
>>> html_text.extract_text('<h1>Hello</h1> world!')
'Hello\n\nworld!'

>>> html_text.extract_text('<h1>Hello</h1> world!', guess_layout=False)
'Hello world!'

Passed html is first cleaned from invisible non-text content such as styles, and then text is extracted.

You can also pass an already parsed lxml.html.HtmlElement:

>>> import html_text
>>> tree = html_text.parse_html('<h1>Hello</h1> world!')
>>> html_text.extract_text(tree)
'Hello\n\nworld!'

If you want, you can handle cleaning manually; use lower-level html_text.etree_to_text in this case:

>>> import html_text
>>> tree = html_text.parse_html('<h1>Hello<style>.foo{}</style>!</h1>')
>>> cleaned_tree = html_text.cleaner.clean_html(tree)
>>> html_text.etree_to_text(cleaned_tree)
'Hello!'

parsel.Selector objects are also supported; you can define a parsel.Selector to extract text only from specific elements:

>>> import html_text
>>> sel = html_text.cleaned_selector('<h1>Hello</h1> world!')
>>> subsel = sel.xpath('//h1')
>>> html_text.selector_to_text(subsel)
'Hello'

NB parsel.Selector objects are not cleaned automatically, you need to call html_text.cleaned_selector first.

Main functions and objects:

• html_text.extract_text accepts html and returns extracted text.
• html_text.etree_to_text accepts parsed lxml Element and returns extracted text; it is a lower-level function, cleaning is not handled here.
• html_text.cleaner is an lxml.html.clean.Cleaner instance which can be used with html_text.etree_to_text; its options are tuned for speed and text extraction quality.
• html_text.cleaned_selector accepts html as text or as lxml.html.HtmlElement, and returns cleaned parsel.Selector.
• html_text.selector_to_text accepts parsel.Selector and returns extracted text.

If guess_layout is True (default), a newline is added before and after newline_tags, and two newlines are added before and after double_newline_tags. This heuristic makes the extracted text more similar to how it is rendered in the browser. Default newline and double newline tags can be found in html_text.NEWLINE_TAGS and html_text.DOUBLE_NEWLINE_TAGS.

It is possible to customize how newlines are added, using newline_tags and double_newline_tags arguments (which are html_text.NEWLINE_TAGS and html_text.DOUBLE_NEWLINE_TAGS by default). For example, don't add a newline after <div> tags:

>>> newline_tags = html_text.NEWLINE_TAGS - {'div'}
>>> html_text.extract_text('<div>Hello</div> world!',
...                        newline_tags=newline_tags)
'Hello world!'

Apart from just getting text from the page (e.g. for display or search), one intended usage of this library is for machine learning (feature extraction). If you want to use the text of the html page as a feature (e.g. for classification), this library gives you plain text that you can later feed into a standard text classification pipeline. If you feel that you need html structure as well, check out webstruct <http://webstruct.readthedocs.io/en/latest/>_ library.