How to scrape T
roy Hunt
with AgentQL

Looking for a better way to scrape Troy Hunt? Say goodbye to fragile XPath or DOM selectors that easily break with website updates. AI-powered AgentQL ensures consistent web scraping across various platforms, from Troy Hunt to any other website, regardless of UI changes.

Not just for scraping Troy Hunt

Smart selectors work anywhere

https://troyhunt.com

URL

Input any webpage.

{
  data_breaches[] {
    title
    date
    website
    description
  }
}

Query

Describe data in natural language.

{
  "data_breaches": [
    {
      "title": "2023 Collection #1",
      "date": "2023-08-01",
      "website": "example.com",
      "description": "A data breach occurred on August 1, 2023, at example.com."
    },
    {
      "title": "2023 Collection #2",
      "date": "2023-08-15",
      "website": "example2.com",
      "description": "Another data breach occurred on August 15, 2023, at example2.com."
    }
  ]
}

Returns

Receive accurate output in seconds.

How to use AgentQL on Troy Hunt

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1

Install the SDK

Install code for JS and Python

npm install agentql

pip3 install agentql

2

Test and refine

Use the query debugger

3

Run your script

Install code for both JS and Python

agentql init

python example.py

Get started

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