# Nobel Prize Laureates & Discoveries Scraper (`litezero/nobel-prize-laureates-scraper`) Actor

Extract Nobel Prize laureates, award years, scientific categories (Physics, Chemistry, Medicine, Literature, Peace, Economic Sciences), motivations, affiliations, and Wikipedia citations in bulk.

- **URL**: https://apify.com/litezero/nobel-prize-laureates-scraper.md
- **Developed by:** [LiteZero](https://apify.com/litezero) (community)
- **Categories:** AI, Automation, Developer tools
- **Stats:** 2 total users, 1 monthly users, 100.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet

## Pricing

from $0.70 / 1,000 item scrapeds

This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.

Learn more: https://docs.apify.com/actors/running/actors-in-store.md#pay-per-event

## What's an Apify Actor?

An Actor is a serverless cloud program that runs on the Apify platform. It has two run modes.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.

Apify vocabulary and the platform model are defined once, in the agent quickstart at https://apify.com/agents.md.

## How to integrate an Actor?

If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.

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 examples already wired to this Actor's own input schema, see the [API](#api) section below.

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`).

# README

## 🏅 Nobel Prize Laureates & Discoveries Scraper

Extract official **Nobel Prize** laureates, award years, scientific and literary categories, discovery motivations, university affiliations, birthplaces, and historical citations in bulk.

Engineered for academic researchers, science communicators, educational platforms, AI RAG knowledge graphs, and university ranking analytics.

***

### 🥊 Why This Actor Beats the Competition

| Feature | 🏅 This Actor (`litezero`) | 🐢 Web Scraping NobelPrize.org | 🔒 Academic Graph Paywalls |
|---|---|---|---|
| **Speed** | ⚡ **< 1.0 second / query** | 🐌 15–20s headless browser scraping | ⏳ Complex multi-table joins |
| **Pricing** | 💰 **$1.00 / 1,000 laureates** (Free Platform Usage) | 💸 High RAM/CPU cost ($5+/run) | 💳 $100+/month academic licenses |
| **Data Completeness** | 📦 Full citations, affiliations, Wikipedia links | ⚠️ Missing biographical details | 🔒 Truncated summaries |
| **Anti-Bot Resiliency** | 🛡️ Official Nobel Foundation API, 0% blocks | 🚫 Cloudflare & rate limits | 🔑 Strict institutional IP limits |
| **Setup Friction** | 🚀 **Zero API keys required** | 🛠️ Proxy rotation & DOM parsing | 📝 Academic application approvals |

***

### 🛠️ Step-by-Step: How to Use

#### Method 1: Apify Web Console (No-Code)

1. Optional: Search by laureate name (e.g. `Curie`, `Einstein`, `Feynman`, `Kahneman`).
2. Optional: Filter by Nobel category (`Physics`, `Chemistry`, `Medicine`, `Literature`, `Peace`, `Economic Sciences`).
3. Optional: Filter by specific award year (e.g. `2023`, `2020`).
4. Click **Start** and export results to JSON, CSV, or Excel.

#### Method 2: Python SDK

```python
from apify_client import ApifyClient

client = ApifyClient("YOUR_APIFY_TOKEN")
run_input = {
    "name": "Einstein",
    "category": "phy"
}

run = client.actor("litezero/nobel-prize-laureates-scraper").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(f"{item['name']} ({item['primary_award_year']} {item['primary_category']}): {item['primary_motivation']}")
```

#### Method 3: Node.js SDK

```javascript
import { ApifyClient } from 'apify-client';

const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('litezero/nobel-prize-laureates-scraper').call({
    category: 'med',
    year: '2023'
});

const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log(`Retrieved ${items.length} Nobel laureates.`);
```

#### Method 4: REST API / cURL

```bash
curl "https://api.apify.com/v2/acts/litezero~nobel-prize-laureates-scraper/runs?token=YOUR_APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"category": "che", "maxResults": 10}'
```

***

### 📥 Input Parameters

| Parameter | Type | Required | Default | Description |
|---|:---:|:---:|:---:|---|
| `name` | `string` | No | `"Curie"` | Laureate name or keyword to search. |
| `category` | `string` | No | `"all"` | Category: `all`, `phy`, `che`, `med`, `lit`, `pea`, `eco`. |
| `year` | `string` | No | `""` | Filter by specific award year (e.g. `2023`). |
| `maxResults` | `integer`| No | `20` | Max laureates to return (1–100). |

***

### 📤 Output Data Dictionary & Sample JSON

```json
{
  "id": "194",
  "name": "Irène Joliot-Curie",
  "full_name": "Irène Joliot-Curie",
  "gender": "female",
  "birth_date": "1897-09-12",
  "birth_place": "Paris, France",
  "death_date": "1956-03-17",
  "prizes_count": 1,
  "primary_category": "Chemistry",
  "primary_award_year": 1935,
  "primary_motivation": "in recognition of their synthesis of new radioactive elements",
  "prizes": [
    {
      "category": "Chemistry",
      "award_year": 1935,
      "motivation": "in recognition of their synthesis of new radioactive elements",
      "prize_status": "received",
      "prize_amount": 159917,
      "affiliations": [
        "Institut du Radium"
      ]
    }
  ],
  "wikipedia_url": "https://en.wikipedia.org/wiki/Ir%C3%A8ne_Joliot-Curie",
  "nobel_prize_url": "https://www.nobelprize.org/laureate/194",
  "scraped_at": "2026-10-04T06:30:00.000Z"
}
```

***

### 💡 Top Commercial Use Cases

1. **Academic Knowledge Graphs & LLM Grounding:** Inject verified Nobel Prize citations, discoveries, and university affiliations into scientific RAG applications.
2. **University & Research Institutional Benchmarking:** Quantify historical faculty Nobel achievements and research impact across global universities.
3. **Science Communication & History Portals:** Build rich interactive visual timelines, educational discovery encyclopedias, and museum exhibitions.

# Actor input Schema

## `name` (type: `string`):

Search by laureate name or keyword (e.g., 'Curie', 'Einstein', 'Feynman', 'Turing').

## `category` (type: `string`):

Filter by Nobel Prize scientific or literary category.

## `year` (type: `string`):

Filter by award year (e.g., '2023', '2020', or leave empty for all years).

## `maxResults` (type: `integer`):

Maximum number of laureates to retrieve (1 to 100).

## Actor input object example

```json
{
  "name": "Curie",
  "category": "all",
  "year": "",
  "maxResults": 20
}
```

# Actor output Schema

## `results` (type: `string`):

No description

# API

You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.

## JavaScript example

```javascript
import { ApifyClient } from 'apify-client';

// Initialize the ApifyClient with your Apify API token
// Replace the '<YOUR_API_TOKEN>' with your token
const client = new ApifyClient({
    token: '<YOUR_API_TOKEN>',
});

// Prepare Actor input
const input = {
    "name": "Curie",
    "category": "all",
    "year": "",
    "maxResults": 20
};

// Run the Actor and wait for it to finish
const run = await client.actor("litezero/nobel-prize-laureates-scraper").call(input);

// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
    console.dir(item);
});

// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs

```

## Python example

```python
from apify_client import ApifyClient

# Initialize the ApifyClient with your Apify API token
# Replace '<YOUR_API_TOKEN>' with your token.
client = ApifyClient("<YOUR_API_TOKEN>")

# Prepare the Actor input
run_input = {
    "name": "Curie",
    "category": "all",
    "year": "",
    "maxResults": 20,
}

# Run the Actor and wait for it to finish
run = client.actor("litezero/nobel-prize-laureates-scraper").call(run_input=run_input)

# Fetch and print Actor results from the run's dataset (if there are any)
print(f"💾 Check your data here: https://console.apify.com/storage/datasets/{run.default_dataset_id}")
for item in client.dataset(run.default_dataset_id).iterate_items():
    print(item)

# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

```

## CLI example

```bash
echo '{
  "name": "Curie",
  "category": "all",
  "year": "",
  "maxResults": 20
}' |
apify call litezero/nobel-prize-laureates-scraper --silent --output-dataset

```

## MCP server setup

```json
{
    "mcpServers": {
        "apify": {
            "type": "http",
            "url": "https://mcp.apify.com/?tools=fetch-actor-details,litezero/nobel-prize-laureates-scraper"
        }
    }
}
```

The hosted server signs you in with OAuth on first connect, so no API token belongs in this config. Clients without OAuth support can send an `Authorization: Bearer <APIFY_API_TOKEN>` header instead, using a token from API & Integrations in Apify Console (https://console.apify.com/settings/integrations).

## OpenAPI specification

Download the OpenAPI definition: https://api.apify.com/v2/actors/39qsdcpckC8ffNnII/builds/uWpvcO8ZNj4UoMdbY/openapi.json