Scrapeghost

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scrapeghost is an experimental library for scraping websites using OpenAI's GPT API. It provides a convenient interface for exploring web scraping with GPT, offering features like Python-based schema definition and HTML preprocessing.

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At a glance

Pricing

Open Source

Free tier

Yes

API

Yes

Skill level

Technical

About

What is scrapeghost?

scrapeghost was an experimental Python library designed for web scraping using OpenAI's GPT API. While the project is no longer maintained or recommended by its author, it offered a unique approach to data extraction. Key features included Python-based schema definition for specifying data shapes, HTML cleaning to reduce API request costs, and the ability to pre-filter HTML using CSS and XPath selectors. It also supported auto-splitting for larger pages, JSON and schema validation for postprocessing, and a hallucination check to ensure data accuracy. The library incorporated cost controls, allowing users to track token usage, set budgets, and implement automatic fallbacks between GPT models to manage expenses.

Best used for

Ideal for developers who need to programmatically scrape websites, extract structured data, and manage the costs associated with large language model API calls. Especially valuable for experimental projects exploring AI-driven web scraping and data validation.

Common actions

scrape websites

extract data

automate web tasks

define data schemas

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Capabilities

Key features

Python schema definition
HTML cleaning
CSS/XPath selectors
Auto-splitting HTML
JSON validation
Schema validation
Cost tracking

Target Audience

developer

Integrations

Not yet documented

Pricing & Plans

Open Source

Free

FAQs

Is scrapeghost actively maintained?

No, the author has explicitly stated that this project, from 2023, is no longer maintained or recommended. Users should be aware that it will not receive further updates or support.

What are the primary costs associated with using scrapeghost?

While scrapeghost itself is open source, its operation relies on OpenAI's GPT API. Users will incur costs based on their OpenAI API usage, particularly for token consumption, which can be significant for large scraping tasks.

Can scrapeghost handle very large web pages?

Yes, scrapeghost includes an auto-splitting feature that can divide large HTML content into multiple calls to the GPT model. This allows for the processing of extensive web pages that might otherwise exceed API input limits.

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Also listed in

This tool also appears in

AI Agents & Automation › Browser & Web Agents Data & Analytics › Web Scraping & Extraction

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