Hyperbrowser 网页抓取工具
Hyperbrowser 是一个用于运行和扩展无头浏览器的平台。它允许您大规模启动和管理浏览器会话,并为任何网页抓取需求提供易于使用的解决方案,例如抓取单个页面或爬取整个网站。
主要特点:
- 即时可扩展性 - 无需基础设施方面的烦恼,即可在几秒钟内启动数百个浏览器会话
- 简 单集成 - 可与 Puppeteer 和 Playwright 等流行工具无缝协作
- 强大的 API - 易于使用的 API,可用于抓取/爬取任何网站,以及更多功能
- 绕过反机器人措施 - 内置隐身模式、广告拦截、自动验证码解决和代理轮换
本笔记提供了使用 Hyperbrowser 网页工具入门的快速概述。
有关 Hyperbrowser 的更多信息,请访问 Hyperbrowser 网站,或者如果您想查看文档,可以访问 Hyperbrowser 文档。
主要功能
抓取 (Scrape)
Hyperbrowser 提供强大的抓取功能,可让您从任何网页中提取数据。抓取工具可以将网页内容转换为 Markdown 或 HTML 等结构化格式,从而便于处理和分析数据。
爬取 (Crawl)
爬取功能使您能够自动浏览网站的多个页面。您可以设置页面限制等参数来控制爬虫对网站的探索程度,并从其访问的每个页面收集数据。
提取 (Extract)
Hyperbrowser 的提取功能利用人工智能根据您定义的模式从网页中提 取特定信息。这使您可以将非结构化的网页内容转换为符合您确切要求的数据。
概述
集成详情
| 工具 (Tool) | 包 (Package) | 本地 (Local) | 可序列化 (Serializable) | JS 支持 (JS support) |
|---|---|---|---|---|
| 爬取工具 (Crawl Tool) | langchain-hyperbrowser | ❌ | ❌ | ❌ |
| 抓取工具 (Scrape Tool) | langchain-hyperbrowser | ❌ | ❌ | ❌ |
| 提取工具 (Extract Tool) | langchain-hyperbrowser | ❌ | ❌ | ❌ |
设置
要访问 Hyperbrowser Web 工具,您需要安装 langchain-hyperbrowser 集成包,并创建一个 Hyperbrowser 账户并获取 API 密钥。
凭证
前往 Hyperbrowser 注册并生成 API 密钥。完成此操作后,设置 HYPERBROWSER_API_KEY 环境变量:
export HYPERBROWSER_API_KEY=<your-api-key>
安装
安装 langchain-hyperbrowser。
%pip install -qU langchain-hyperbrowser
实例化
爬虫工具
HyperbrowserCrawlTool 是一款强大的工具,可以从给定的 URL 开始爬取整个网站。它支持可配置的页面限制和抓取选项。
from langchain_hyperbrowser import HyperbrowserCrawlTool
tool = HyperbrowserCrawlTool()
抓取工具
HyperbrowserScrapeTool 是一款可以抓取网页内容的工具。它支持 Markdown 和 HTML 输出格式,并能提取元数据。
from langchain_hyperbrowser import HyperbrowserScrapeTool
tool = HyperbrowserScrapeTool()
提取工具
HyperbrowserExtractTool 是一款强大的工具,它利用 AI 从网页中提取结构化数据。它可以根据预定义的模式提取信息。
from langchain_hyperbrowser import HyperbrowserExtractTool
tool = HyperbrowserExtractTool()
调用
基本用法
爬虫工具
from langchain_hyperbrowser import HyperbrowserCrawlTool
result = HyperbrowserCrawlTool().invoke(
{
"url": "https://example.com",
"max_pages": 2,
"scrape_options": {"formats": ["markdown"]},
}
)
print(result)
{'data': [CrawledPage(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None, url='https://example.com', status='completed', error=None)], 'error': None}
Scrape Tool
from langchain_hyperbrowser import HyperbrowserScrapeTool
result = HyperbrowserScrapeTool().invoke(
{"url": "https://example.com", "scrape_options": {"formats": ["markdown"]}}
)
print(result)
{'data': ScrapeJobData(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None), 'error': None}
提取工具
from langchain_hyperbrowser import HyperbrowserExtractTool
from pydantic import BaseModel
class SimpleExtractionModel(BaseModel):
title: str
result = HyperbrowserExtractTool().invoke(
{
"url": "https://example.com",
"schema": SimpleExtractionModel,
}
)
print(result)
{'data': {'title': 'Example Domain'}, 'error': None}
自定义选项
爬虫工具(附带自定义选项)
result = HyperbrowserCrawlTool().run(
{
"url": "https://example.com",
"max_pages": 2,
"scrape_options": {
"formats": ["markdown", "html"],
},
"session_options": {"use_proxy": True, "solve_captchas": True},
}
)
print(result)
{'data': [CrawledPage(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html=None, markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None, url='https://example.com', status='completed', error=None)], 'error': None}
刮刀工具(Scrape Tool)及自定义选项
result = HyperbrowserScrapeTool().run(
{
"url": "https://example.com",
"scrape_options": {
"formats": ["markdown", "html"],
},
"session_options": {"use_proxy": True, "solve_captchas": True},
}
)
print(result)
{'data': ScrapeJobData(metadata={'url': 'https://www.example.com/', 'title': 'Example Domain', 'viewport': 'width=device-width, initial-scale=1', 'sourceURL': 'https://example.com'}, html='<html><head>\n <title>Example Domain</title>\n\n <meta charset="utf-8">\n <meta http-equiv="Content-type" content="text/html; charset=utf-8">\n <meta name="viewport" content="width=device-width, initial-scale=1">\n \n</head>\n\n<body>\n<div>\n <h1>Example Domain</h1>\n <p>This domain is for use in illustrative examples in documents. You may use this\n domain in literature without prior coordination or asking for permission.</p>\n <p><a href="https://www.iana.org/domains/example">More information...</a></p>\n</div>\n\n\n</body></html>', markdown='Example Domain\n\n# Example Domain\n\nThis domain is for use in illustrative examples in documents. You may use this\ndomain in literature without prior coordination or asking for permission.\n\n[More information...](https://www.iana.org/domains/example)', links=None, screenshot=None), 'error': None}
提取工具与自定义模式
from typing import List
from pydantic import BaseModel
class ProductSchema(BaseModel):
title: str
price: float
class ProductsSchema(BaseModel):
products: List[ProductSchema]
result = HyperbrowserExtractTool().run(
{
"url": "https://dummyjson.com/products?limit=10",
"schema": ProductsSchema,
"session_options": {"session_options": {"use_proxy": True}},
}
)
print(result)
{'data': {'products': [{'price': 9.99, 'title': 'Essence Mascara Lash Princess'}, {'price': 19.99, 'title': 'Eyeshadow Palette with Mirror'}, {'price': 14.99, 'title': 'Powder Canister'}, {'price': 12.99, 'title': 'Red Lipstick'}, {'price': 8.99, 'title': 'Red Nail Polish'}, {'price': 49.99, 'title': 'Calvin Klein CK One'}, {'price': 129.99, 'title': 'Chanel Coco Noir Eau De'}, {'price': 89.99, 'title': "Dior J'adore"}, {'price': 69.99, 'title': 'Dolce Shine Eau de'}, {'price': 79.99, 'title': 'Gucci Bloom Eau de'}]}, 'error': None}
异步用法
所有工具都支持异步用法:
from typing import List
from langchain_hyperbrowser import (
HyperbrowserCrawlTool,
HyperbrowserExtractTool,
HyperbrowserScrapeTool,
)
from pydantic import BaseModel
class ExtractionSchema(BaseModel):
popular_library_name: List[str]
async def web_operations():
# Crawl
crawl_tool = HyperbrowserCrawlTool()
crawl_result = await crawl_tool.arun(
{
"url": "https://example.com",
"max_pages": 5,
"scrape_options": {"formats": ["markdown"]},
}
)
# Scrape
scrape_tool = HyperbrowserScrapeTool()
scrape_result = await scrape_tool.arun(
{"url": "https://example.com", "scrape_options": {"formats": ["markdown"]}}
)
# Extract
extract_tool = HyperbrowserExtractTool()
extract_result = await extract_tool.arun(
{
"url": "https://npmjs.com",
"schema": ExtractionSchema,
}
)
return crawl_result, scrape_result, extract_result
results = await web_operations()
print(results)
---------------------------------------------------------------------------
``````output
NameError Traceback (most recent call last)
``````output
Cell In[6], line 10
1 from langchain_hyperbrowser import (
2 HyperbrowserCrawlTool,
3 HyperbrowserExtractTool,
4 HyperbrowserScrapeTool,
5 )
7 from pydantic import BaseModel
---> 10 class ExtractionSchema(BaseModel):
11 popular_library_name: List[str]
14 async def web_operations():
15 # Crawl
``````output
Cell In[6], line 11, in ExtractionSchema()
10 class ExtractionSchema(BaseModel):
---> 11 popular_library_name: List[str]
``````output
NameError: name 'List' is not defined