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What is parsel?

Parsel is a Python library that is distributed under the BSD license, designed to simplify the process of extracting and manipulating data from HTML and XML documents by utilizing XPath and CSS selectors, with the added flexibility of incorporating regular expressions. To get started, one must create a selector object that targets the specific HTML or XML content for analysis. Once this is established, users can leverage either CSS or XPath expressions to pinpoint the desired elements. CSS acts as a styling language for HTML, offering selectors that connect styles to specific HTML elements, while XPath is employed to choose nodes within XML documents and can also be effectively used with HTML. While both CSS and XPath are viable options, CSS generally offers improved readability, whereas XPath possesses functionalities that may not be attainable through CSS alone. Built upon the lxml library, parsel selectors include certain EXSLT extensions and come equipped with pre-registered namespaces for use in XPath queries. Additionally, parsel selectors facilitate the chaining of selectors, allowing users to primarily select elements by class with CSS and seamlessly switch to XPath when necessary, thereby providing enhanced flexibility in data extraction tasks. This combination of features renders parsel an invaluable resource for developers engaged in web data manipulation. Moreover, the ability to toggle between two powerful selection methods ensures that users can optimize their data extraction strategies according to the complexity of their tasks.

What is Data Excavator?

Introducing our data scraper that guarantees complete support, eliminating the need for costly and complex web scrapers that function in only one window. Now, you can effortlessly extract any data for as little as $5 per month from any website you choose. Our solution features a user-friendly web scraper designed with CSS-selectors and XPath, ensuring seamless installation. Additionally, there are no limitations on usage or reliance on cloud APIs, making it a straightforward tool developed by data specialists. Your initial scraping project is complimentary, and we provide one pre-configured scraping job for any site upon request. To get started, simply purchase a license key, and remote assistance is available via TeamViewer or RDP, connecting directly to your computer. Data Excavator is a sleek, well-crafted application that is gaining traction among users worldwide. Despite being a small team of skilled programmers, we manage to operate effectively without a hefty marketing budget, enabling us to deliver an affordable yet highly supported product to our clients. With our commitment to quality and customer satisfaction, you can expect not only a functional tool but also dedicated assistance throughout your scraping journey.

Media

Media

Integrations Supported

Python
Travis CI

Integrations Supported

Python
Travis CI

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

$214 per year
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Python Software Foundation

Company Location

United States

Company Website

pypi.org/project/parsel/

Company Facts

Organization Name

Data Excavator

Date Founded

2019

Company Location

Georgia

Company Website

data-excavator.com

Categories and Features

Categories and Features

Data Extraction

Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction

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