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This Python project is a schema scraper that retrieves structured data (schema.org) from a webpage using requests and BeautifulSoup. It fetches the page content, parses it, and extracts schema data in JSON-LD and Microdata formats, helping to analyze the structured data of any webpage.

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schema-scraper

This Python project is a schema scraper that retrieves structured data (schema.org) from a webpage using requests and BeautifulSoup. It fetches the page content, parses it, and extracts schema data in JSON-LD and Microdata formats, helping to analyze the structured data of any webpage.

Key Features:

JSON-LD Schema: Extracted by looking for <script type="application/ld+json">. Microdata Schema: Identified by HTML attributes like itemscope, itemprop.

How It Works:

The script fetches the HTML content from the provided URL. It uses BeautifulSoup to parse the page. It looks for schema data in two formats: JSON-LD and Microdata. Extracted schema information is returned in a structured format for easy reading or further processing.

How to Use:

Run the script and pass any webpage URL containing structured data (schema) as input. The script will print the JSON-LD and Microdata schema extracted from the page. This approach can be expanded by adding more error handling, output formatting, or even saving the schema data to a file for analysis later.

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This Python project is a schema scraper that retrieves structured data (schema.org) from a webpage using requests and BeautifulSoup. It fetches the page content, parses it, and extracts schema data in JSON-LD and Microdata formats, helping to analyze the structured data of any webpage.

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