scrapegraphaivsspidr
ScrapeGraphAI is a Python library that uses large language models (LLMs) to create web scraping pipelines automatically. Instead of writing CSS selectors or XPath expressions, you describe what data you want in natural language and provide a Pydantic schema — the library handles the rest.
Key features include:
- Natural language extraction Describe what you want to extract in plain English (e.g., "Extract all product names and prices") and the LLM figures out how to find and extract the data.
- Pydantic schema output Define the expected output structure using Pydantic models for type-safe, validated extraction results.
- Graph-based pipeline Built on a directed graph architecture where each node performs a specific task (fetching, parsing, extracting, merging). This makes pipelines modular and debuggable.
- Multiple graph types SmartScraperGraph (single page), SearchGraph (search + scrape), SpeechGraph (audio output), and more specialized pipelines.
- Multiple LLM providers Works with OpenAI, Anthropic, Google, Groq, local models via Ollama, and more.
- HTML and JSON support Can extract data from both HTML pages and JSON API responses.
ScrapeGraphAI is particularly useful for rapid prototyping of scrapers and for extracting data from pages with complex or frequently changing layouts where traditional selectors would be brittle.
Spidr is a Ruby gem that provides a simple and flexible way to spider and scrape websites. It allows you to easily navigate through a website, following links and scraping data as you go. It is built on top of Nokogiri, a popular Ruby gem for parsing and searching HTML and XML documents, and it provides a simple and intuitive API for defining and running web scraping operations.
One of the main features of Spidr is its ability to spider a website, following all the links on a page and visiting all the pages of a website. This allows you to easily and quickly scrape large amounts of data from a website, without having to manually specify which pages to visit.
In addition to its spidering capabilities, Spidr also provides a variety of other features that can simplify the web scraping process. It can automatically filter which links to follow and which pages to visit, it can handle cookies and authentication, and it can automatically store the scraped data in a database or file. It also provides a built-in support for parallelism and queueing to speed up the scraping process.