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html5-parservsrvest

Apache 2.0 1 1 671
103.7 thousand (month) Jun 03 2007 0.4.12(6 months ago)
1,479 1 22 MIT
Nov 22 2014 612.5 thousand (month) 1.0.4(1 year, 9 months ago)

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.

rvest is a popular R library for web scraping and parsing HTML and XML documents. It is built on top of the xml2 and httr libraries and provides a simple and consistent API for interacting with web pages.

One of the main advantages of using rvest is its simplicity and ease of use. It provides a number of functions that make it easy to extract information from web pages, even for those who are not familiar with web scraping. The html_nodes and html_node functions allow you to select elements from an HTML document using CSS selectors, similar to how you would select elements in JavaScript.

rvest also provides functions for interacting with forms, including html_form, set_values, and submit_form functions. These functions make it easy to navigate through forms and submit data to the server, which can be useful when scraping sites that require authentication or when interacting with dynamic web pages.

rvest also provides functions for parsing XML documents. It includes xml_nodes and xml_node functions, which also use CSS selectors to select elements from an XML document, as well as xml_attrs and xml_attr functions to extract attributes from elements.

Another advantage of rvest is that it provides a way to handle cookies, so you can keep the session alive while scraping a website, and also you can handle redirections with handle_redirects

Example Use


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
library("rvest")

# Rvest can use basic HTTP client to download remote HTML:
tree <- read_html("http://webscraping.fyi/lib/r/rvest")
# or read from string:
tree <- read_html('
<div class="products">
  <a href="/product/1">Cat Food</a>
  <a href="/product/2">Dog Food</a>
</div>
')

# to parse HTML trees with rvest we use r pipes (the %>% symbol) and html_element function:
# we can use css selectors:
print(tree %>% html_element(".products>a") %>% html_text())
# "[1] "\nCat Food\nDog Food\n""

# or XPath:
print(tree %>% html_element(xpath="//div[@class='products']/a") %>% html_text())
# "[1] "\nCat Food\nDog Food\n""

# Additionally rvest offers many quality of life functions:
# html_text2 - removes trailing and leading spaces and joins values
print(tree %>% html_element("div") %>% html_text2())
# "[1] "Cat Food Dog Food""

# html_attr - selects element's attribute:
print(tree %>% html_element("div") %>% html_attr('class'))
# "products"

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