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chompjsvshtml5-parser

MIT 6 1 198
22.7 thousand (month) Jul 30 2007 1.3.0(3 months ago)
682 1 1 Apache-2.0
Jun 03 2007 27.6 thousand (month) 0.4.12(1 year, 21 days ago)

chompjs can be used in web scrapping for turning JavaScript objects embedded in pages into valid Python dictionaries.

In web scraping this is particularly useful for parsing Javascript variables like:

import chompjs
js = """
  var myObj = {
    myMethod: function(params) {
    // ...
    },
    myValue: 100
  }
"""
chompjs.parse_js_object(js, json_params={'strict': False})
{'myMethod': 'function(params) {\n        // ...\n    }', 'myValue': 100}

In practice this can be used to extract hidden JSON data like data from <script id=__NEXT_DATA__> elements from nextjs (and similar) websites. Unlike json.loads command chompjs can ingest json documents that contain javascript natives like functions making it a super easy way to scrape hidden web data objects.

html5-parser is a Python library for parsing HTML and XML documents.

A fast implementation of the HTML 5 parsing spec for Python. Parsing is done in C using a variant of the gumbo parser. The gumbo parse tree is then transformed into an lxml tree, also in C, yielding parse times that can be a thirtieth of the html5lib parse times. That is a speedup of 30x. This differs, for instance, from the gumbo python bindings, where the initial parsing is done in C but the transformation into the final tree is done in python.

It is built on top of the popular lxml library and provides a simple and intuitive API for working with the document's structure.

html5-parser uses the HTML5 parsing algorithm, which is more lenient and forgiving than the traditional XML-based parsing algorithm. This means that it can parse HTML documents with malformed or missing tags and still produce a usable parse tree.

To use html5-parser, you first need to install it via pip by running pip install html5-parser. Once it is installed, you can use the html5_parser.parse() function to parse an HTML document and create a parse tree. For example:

from html5_parser import parse

html_string = "<html><body>Hello, World!</body></html>"
root = parse(html_string)
print(root.tag) # html
You can also use `html5_parser.parse()`` with file-like objects, bytes or file paths.

Once you have a parse tree, you can use the find() and findall() methods to search for elements in the document similar to BeautifulSoup.

html5-parser also supports searching using xpath, similar to lxml.

Example Use


# basic use
import chompjs
js = """
  var myObj = {
    myMethod: function(params) {
    // ...
    },
    myValue: 100
  }
"""
chompjs.parse_js_object(js, json_params={'strict': False})
{'myMethod': 'function(params) {\n        // ...\n    }', 'myValue': 100}

# example how to use with hidden data parsing:
import httpx
import chompjs
from parsel import Selector

response = httpx.get("http://example.com")
hidden_script = Selector(response.text).css("script#__NEXT_DATA__::text").get()
data = chompjs.parse_js_object(hidden_script)
print(data['props'])
from html5_parser import parse

html_string = "<html><body>Hello, World!</body></html>"
root = parse(html_string)
print(root.tag) # html
body = root.find("body")
# or find all
print(body.text) # "Hello, World!"
for el in root.findall("p"):
    print(el.text) # "Hello

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