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scrapydwebvsfirecrawl

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2.1 thousand (month) Sep 30 2018 1.6.0(2025-02-16 13:18:50 ago)
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Apr 01 2024 0.0.0(2025-03-15 00:00:00 ago)

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.

Firecrawl is an AI-powered web scraping API that converts web pages into clean Markdown or structured data, optimized for use with large language models (LLMs) and retrieval-augmented generation (RAG) pipelines. It handles JavaScript rendering, anti-bot bypass, and content extraction automatically.

Firecrawl offers multiple modes:

  • Scrape Convert a single URL into clean Markdown, HTML, or structured data. Handles JavaScript rendering and anti-bot protections automatically.
  • Crawl Crawl an entire website starting from a URL, with configurable depth, URL patterns, and page limits. Returns all pages as clean Markdown.
  • Map Quickly discover all URLs on a website without fully scraping each page. Useful for sitemap generation and crawl planning.
  • Extract Use LLMs to extract specific structured data from pages based on a schema definition.

Key features:

  • Clean Markdown output ideal for LLM context windows
  • Automatic JavaScript rendering with headless browsers
  • Built-in anti-bot bypass for protected websites
  • Structured extraction with JSON schemas
  • Batch crawling with webhook notifications
  • Python and JavaScript SDKs

Firecrawl is a commercial API service (requires API key, has a free tier) backed by Y Combinator. It has become one of the most popular tools for feeding web content into AI applications and is widely used in the LLM/RAG ecosystem.

Note: while the primary service is an API, the core is open source and can be self-hosted.

Highlights


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Example Use


```python from firecrawl import FirecrawlApp app = FirecrawlApp(api_key="YOUR_API_KEY") # Scrape a single page - get clean markdown result = app.scrape_url("https://example.com/blog/article") print(result["markdown"]) # clean markdown content # Extract structured data with a schema result = app.scrape_url( "https://example.com/product/123", params={ "formats": ["extract"], "extract": { "schema": { "type": "object", "properties": { "name": {"type": "string"}, "price": {"type": "number"}, "description": {"type": "string"}, }, } }, }, ) print(result["extract"]) # {"name": "...", "price": 29.99, ...} # Crawl an entire website crawl_result = app.crawl_url( "https://example.com", params={"limit": 100, "scrapeOptions": {"formats": ["markdown"]}}, ) for page in crawl_result["data"]: print(page["metadata"]["title"], page["markdown"][:100]) # Map all URLs on a site map_result = app.map_url("https://example.com") print(f"Found {len(map_result['links'])} URLs") ```

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