ayakashivsfirecrawl

AGPL-3.0-only 8 1 217

166 (month) Apr 18 2019 1.0.0-beta8.4(2023-06-29 12:37:12 ago)

- - - None

Apr 01 2024 0.0.0(2025-03-15 00:00:00 ago)

Ayakashi is a web scraping library for Node.js that allows developers to easily extract structured data from websites. It is built on top of the popular "puppeteer" library and provides a simple and intuitive API for defining and querying the structure of a website.

Features:

Powerful querying and data models
Ayakashi's way of finding things in the page and using them is done with props and domQL. Directly inspired by the relational database world (and SQL), domQL makes DOM access easy and readable no matter how obscure the page's structure is. Props are the way to package domQL expressions as re-usable structures which can then be passed around to actions or to be used as models for data extraction.
High level builtin actions
Ready made actions so you can focus on what matters. Easily handle infinite scrolling, single page navigation, events and more. Plus, you can always build your own actions, either from scratch or by composing other actions.
Preload code on pages
Need to include a bunch of code, a library you made or a 3rd party module and make it available on a page? Preloaders have you covered.

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

ai-poweredpopularasync

Example Use

```javascript const ayakashi = require("ayakashi"); const myAyakashi = ayakashi.init(); // navigate the browser await myAyakashi.goTo("https://example.com/product"); // parsing HTML // first by defnining a selector myAyakashi .select("productList") .where({class: {eq: "product-item"}}); // then executing selector on current HTML: const productList = await myAyakashi.extract("productList"); console.log(productList); ```

```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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