# Wikipedia article to JSON: Solana facts by schema

**Use case:** 

Extract the name, original authors, first release year, consensus mechanism and native token of Solana from its Wikipedia article as one JSON object. Change the URL and the fields for any page. $0.02 per page.

## Input

```json
{
  "urls": [
    "https://en.wikipedia.org/wiki/Solana_(blockchain_platform)"
  ],
  "schema": {
    "name": "string",
    "original_author": "string",
    "initial_release_year": "number",
    "consensus_mechanism": "string",
    "native_token": "string"
  }
}
```

## Output

```json
{
  "url": {
    "label": "URL",
    "format": "string"
  },
  "kind": {
    "label": "Document type",
    "format": "string"
  },
  "data": {
    "label": "Extracted data",
    "format": "object"
  },
  "fields_found": {
    "label": "Fields found",
    "format": "number"
  },
  "fields_requested": {
    "label": "Fields requested",
    "format": "number"
  },
  "null_fields": {
    "label": "Fields not stated",
    "format": "array"
  },
  "truncated": {
    "label": "Truncated",
    "format": "boolean"
  },
  "fetched_at": {
    "label": "Fetched at",
    "format": "string"
  }
}
```

## How it works

### 1. Sign up on Apify or log in

The AI Data Extractor: web page or PDF to JSON by your schema Actor is ready to run with the inputs already set for "Wikipedia article to JSON: Solana facts by schema". [Sign up or log in](https://console.apify.com/create-task-from-example/xWeK7EvgUgFN5oU2x) and you'll land in Apify Console with a copy of this exact task.

### 2. Start the "Wikipedia article to JSON: Solana facts by schema" task

The AI Data Extractor: web page or PDF to JSON by your schema Actor will start running based on the input automatically. You can also change all the input fields, like page or pdf urls and fields to extract, to match your specific use case.

### 3. Receive the "Wikipedia article to JSON: Solana facts by schema" output

Monitor the progress in real time. You will be notified as soon as your dataset is complete and ready for review. Each result includes data such as URL, document type, extracted data, and more.

### 4. Integrate into your workflow

The final output is delivered in JSON, CSV, or Excel format, ready to be plugged into your workflow. You can also [run the "Wikipedia article to JSON: Solana facts by schema" task via API](https://apify.com/ochinimus/ai-data-extractor.md).

## About this Actor

This example demonstrates how to use [AI Data Extractor: web page or PDF to JSON by your schema](https://apify.com/ochinimus/ai-data-extractor.md) with a specific input configuration. Visit the [Actor detail page](https://apify.com/ochinimus/ai-data-extractor.md) to learn more, explore other use cases, and run it yourself.


## How to integrate an Actor?

This Task's input is already configured above. Use it as-is rather than inventing a new one.

Do not guess an integration path. Every one of them is in the agent quickstart at https://apify.com/agents.md: the Apify MCP server, Agent Skills with the Apify CLI, the JavaScript and Python clients, the REST API, and the account-free path for an agent with no human to sign in. It also carries the rule on stating cost before the first paid run.

For full API examples (JavaScript, Python, CLI, MCP, OpenAPI), see this Task's Actor page: https://apify.com/ochinimus/ai-data-extractor.md

Each client library has reference documentation the quickstart does not restate: [JavaScript/TypeScript](https://docs.apify.com/api/client/js/docs.md) (`npm install apify-client`) and [Python](https://docs.apify.com/api/client/python/docs.md) (`pip install apify-client`).