Metadata-Version: 2.1
Name: itemloaders
Version: 1.0.4
Summary: Base library for scrapy's ItemLoader
Home-page: https://github.com/scrapy/itemloaders
Author: Scrapinghub
Author-email: info@scrapinghub.com
License: BSD
Project-URL: Documentation, https://itemloaders.readthedocs.io/
Project-URL: Source, https://github.com/scrapy/itemloaders
Platform: UNKNOWN
Classifier: Development Status :: 5 - Production/Stable
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: BSD License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6
Description-Content-Type: text/x-rst
License-File: LICENSE
Requires-Dist: w3lib (>=1.17.0)
Requires-Dist: parsel (>=1.5.0)
Requires-Dist: jmespath (>=0.9.5)
Requires-Dist: itemadapter (>=0.1.0)
===========
itemloaders
===========
.. image:: https://img.shields.io/pypi/v/itemloaders.svg
:target: https://pypi.python.org/pypi/itemloaders
:alt: PyPI Version
.. image:: https://img.shields.io/pypi/pyversions/itemloaders.svg
:target: https://pypi.python.org/pypi/itemloaders
:alt: Supported Python Versions
.. image:: https://travis-ci.com/scrapy/itemloaders.svg?branch=master
:target: https://travis-ci.com/scrapy/itemloaders
:alt: Build Status
.. image:: https://codecov.io/github/scrapy/itemloaders/coverage.svg?branch=master
:target: https://codecov.io/gh/scrapy/itemloaders
:alt: Coverage report
.. image:: https://readthedocs.org/projects/itemloaders/badge/?version=latest
:target: https://itemloaders.readthedocs.io/en/latest/?badge=latest
:alt: Documentation Status
``itemloaders`` is a library that helps you collect data from HTML and XML sources.
It comes in handy to extract data from web pages, as it supports
data extraction using CSS and XPath Selectors.
It's specially useful when you need to standardize the data from many sources.
For example, it allows you to have all your casting and parsing rules in a
single place.
Here is an example to get you started::
from itemloaders import ItemLoader
from parsel import Selector
html_data = '''
Some random product page
Some random product page
$ 100.12
'''
loader = ItemLoader(selector=Selector(html_data))
loader.add_xpath('name', '//div[@class="product_name"]/text()')
loader.add_xpath('name', '//div[@class="product_title"]/text()')
loader.add_css('price', '#price::text')
loader.add_value('last_updated', 'today') # you can also use literal values
item = loader.load_item()
item
# {'name': ['Some random product page'], 'price': ['$ 100.12'], 'last_updated': ['today']}
For more information, check out the `documentation `_.
Contributing
============
All contributions are welcome!
* If you want to review some code, check open
`Pull Requests here `_
* If you want to submit a code change
* File an `issue here `_, if there isn't one yet
* Fork this repository
* Create a branch to work on your changes
* Push your local branch and submit a Pull Request