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gazpachovsfeedparser

MIT 14 1 724
10.3 thousand (month) Dec 28 2012 1.1(3 years ago)
1,797 8 81 BSD-2-Clause
6.0.11(2 months ago) Jun 15 2007 2.7 million (month)

gazpacho is a Python library for scraping web pages. It is designed to make it easy to extract information from a web page by providing a simple and intuitive API for working with the page's structure.

gazpacho uses the requests library to download the page and the lxml library to parse the HTML or XML code. It provides a way to search for elements in the page using CSS selectors, similar to BeautifulSoup.

To use gazpacho, you first need to install it via pip by running pip install gazpacho. Once it is installed, you can use the gazpacho.get() function to download a web page and create a gazpacho object. For example:

from gazpacho import get, Soup

url = "https://en.wikipedia.org/wiki/Web_scraping"
html = get(url)
soup = Soup(html)
print(soup.find('title').text)
You can also use gazpacho.get() with file-like objects, bytes or file paths.

Once you have a gazpacho object, you can use the find() and find_all() methods to search for elements in the page using CSS selectors, similar to BeautifulSoup.

gazpacho also supports searching using the select() method, which returns the first matching element, and the select_all() method, which returns all matching elements.

feedparser is a Python module for downloading and parsing syndicated feeds. It can handle RSS 0.90, Netscape RSS 0.91, Userland RSS 0.91, RSS 0.92, RSS 0.93, RSS 0.94, RSS 1.0, RSS 2.0, Atom 0.3, Atom 1.0, and CDF feeds. It also parses several popular extension modules, including Dublin Core and Appleā€™s iTunes extensions.

To use Universal Feed Parser, you will need Python 3.6 or later. Universal Feed Parser is not meant to run standalone; it is a module for you to use as part of a larger Python program.

feedparser can be used to scrape data feeds as it can download them and parse the XML structured data.

Example Use


from gazpacho import get, Soup

# gazpacho can retrieve web pages
url = "https://webscraping.fyi/"
html = get(url)
# and parse them:
soup = Soup(html)
print(soup.find('title').text)

# search for elements like beautifulsoup:
body = soup.find("div", {"class":"item"})
print(body.text)
import feedparser

# the feed can be loaded from a remote URL
data = feedparser.parse('http://feedparser.org/docs/examples/atom10.xml')
# local path
data = feedparser.parse('/home/user/data.xml')
# or raw string
data = feedparser.parse('<xml>...</xml>')

# the result dataset is a nested python dictionary containing feed data:
data['feed']['title']

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