Data transformation and manipulation library
Project description
- warning:
EasyData is in early stages of development; backwards incompatible changes are possible without deprecation warning until beta status is reached and therefore is not suitable to be used in production.
Overview
EasyData is data object pattern that provides transformation of item data from various sources (text, html, xml, json, dictionaries, lists and others) to a python dictionary with option to even combine different types of sources in order to transform to dictionary.
It uses component based mapping at the hearth and it’s concept is similar to ORM-like models.
Documentation
Documentation is available online at https://easydata.readthedocs.io/ and in the docs directory.
The benefits of using EasyData are:
focusing on the object-oriented business logic
uniform extraction logic between various sources
speeds up development process of creating a transformer/parser significantly
time reduction regarding maintenance since it offers clear readability and clarity regarding what each components does.
extraction and parsing logic re-usability
high and low level option for parsing so that we don’t hit any limitations
option to create custom components for specific needs if needed
defaults can be changed through configuration on various levels
creating test cases is a breeze since each component was created to be used independently if needed.
autocomplete works for all parameters on public classes or methods.
Applications:
Web scraping. It can easily be integrated with scrapy or any other python based solution or even your own.
Transforming API and FEED data from various formats.
Transforming/preparing data for API or FEED.
Transforming/preparing data for a database.
Requirements
Python 3.8+
Works on Linux, Windows, macOS, BSD
Install
The quick way:
pip install easydata
See the install section in the documentation at https://easydata.readthedocs.io/en/latest/installation.html for more details.
Example
Bellow we will give just a simple example, so you can get some presentation, how EasyData works. For more advanced examples or tutorials please refer to documentation.
Lets make transformation on a following HTML:
test_html = """
<html>
<body>
<h2 class="name">
<div class="brand">EasyData</div>
Test Product Item
</h2>
<div id="description">
<p>Basic product info. EasyData product is newest
addition to python <b>world</b></p>
<ul>
<li>Color: Black</li>
<li>Material: Aluminium</li>
</ul>
</div>
<div id="price">Was 99.9</div>
<div id="sale-price">49.9</div>
<div class="images">
<img src="http://demo.com/img1.jpg" />
<img src="http://demo.com/img2.jpg" />
<img src="http://demo.com/img2.jpg" />
</div>
<div class="stock" available="Yes">In Stock</div>
</body>
</html>
"""Now lets create an ItemModel which will process HTML above and parse it to item dict.
import easydata as ed
class ProductItemModel(ed.ItemModel):
item_name = ed.Text(
ed.pq('.name::text'),
)
item_brand = ed.Text(
ed.pq('.brand::text')
)
item_description = ed.Description(
ed.pq('#description::text')
)
item_price = ed.PriceFloat(
ed.pq('#price::text')
)
item_sale_price = ed.PriceFloat(
ed.pq('#sale-price::text')
)
item_color = ed.Feature(
ed.pq('#description::text'),
key='color'
)
item_stock = ed.Has(
ed.pq('.stock::attr(available)'),
contains=['yes']
)
item_images = ed.List(
ed.pq('.images img::items'),
parser=ed.UrlParser(
ed.pq('::src')
)
)
"""
Alternative with selecting src values in a first css query:
item_images = ed.ListParser(
ed.pq('.images img::src-items'),
parser=ed.UrlParser()
)
"""In example bellow we will demonstrate how newly created ProductItemModel will parse provided HTML data into dict object.
>>> item_model = ProductItemModel()
>>> item_model.parse_item(test_html)Output:
{
'brand': 'EasyData',
'description': 'Basic product info. EasyData product is newest addition \
to python world. Color: Black. Material: Aluminium.',
'color': 'Black',
'images': [
'http://demo.com/img1.jpg',
'http://demo.com/img2.jpg',
'http://demo.com/img3.jpg'
],
'name': 'EasyData Test Product Item',
'price': 99.9,
'sale_price': 49.9,
'stock': True
}Contributing
Yes please! We are always looking for contributions, additions and improvements.
See https://easydata.readthedocs.io/en/latest/contributing.html for more details.
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