scrapydwebvsscrapegraphai
ScrapydWeb is a web-based management tool for the Scrapyd service. It is built using the Python Flask framework and allows you to easily manage and monitor your Scrapy spider projects through a web interface.
ScrapydWeb allows you to view the status of your running spiders, view the logs of completed spiders, schedule new spider runs, and manage spider settings and configurations.
ScrapydWeb provides a simple way to manage your scraping tasks and allows you to schedule and run multiple spiders simultaneously. It also provides a user-friendly web interface that makes it easy to view the status of your spiders and monitor their progress.
You can install the package via pip by running pip install scrapydweb and then you can run the package by
running scrapydweb command in your command prompt.
It will start a web server that you can access through your web browser at http://localhost:6800/
You will need to have Scrapyd running in order to use ScrapydWeb,
Scrapyd is a service for running Scrapy spiders, it allows you to schedule spiders to run at regular intervals
and also allows you to run spiders on remote machines.
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.