Search Results for "data extraction"

...It handles many low-level tasks involved in web data extraction, including parsing responses, managing platform-specific logic, and handling errors, allowing developers to focus on implementing application features rather than scraping mechanics. Each supported service is implemented through its own extractor components that conform to a common interface, enabling consistent access to data across different platforms.

spider_collection is a collection of Python web crawler scripts created primarily for experimentation, learning, and practical scraping tasks. spider_collection gathers multiple independent spiders designed to collect data from different platforms and services, demonstrating a variety of scraping techniques and workflows. These crawlers make use of common Python scraping tools such as requests, parsel, BeautifulSoup, and the Scrapy framework to extract structured information from web pages....

DotnetSpider is a web crawling and data extraction framework built on the .NET Standard platform. It is designed to help developers create efficient and scalable crawlers for collecting structured data from websites. It provides a high-level API that simplifies the process of defining spiders, managing requests, and extracting content from web pages. Developers can create custom spiders by extending base classes and configuring pipelines that handle downloading, parsing, and storing collected data. ...

MBR Bulk WP Detector is a free WordPress plugin that lets you check unlimited URLs right from your own dashboard. No subscriptions, no URL limits, and your data stays completely private on your server. What Can You Do With It? The basics are simple: Paste a list of URLs (or upload a CSV file), click a button, and boom—you’ve got a clear breakdown of which sites are running WordPress and which aren’t. But it gets better… Turn on Deep Scan mode, and you’ll also discover what...

The Cornell Web Lab Collaboration Server is a suite of tools and services for GUI-based extraction, analysis and sharing of archived web data. See http://weblab.infosci.cornell.edu/ and http://www.cs.cornell.edu/~weigel for details about the project.

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