NPR Scraper

Extract news articles, podcast transcripts, and audio story metadata from NPR across all program sections. Built on spider-browser .

Get started Docs

target
npr.org: success rate
99.9%: latency
~4ms

Quick start

Extract data in minutes.

npr-scraper.ts

import { SpiderBrowser } from "spider-browser";

const spider = new SpiderBrowser({
  apiKey: process.env.SPIDER_API_KEY!,
  stealth: 2,
});

await spider.connect();
const page = spider.page!;
await page.goto("https://www.npr.org/2024/01/12/ai-music-copyright");

const data = await page.extractFields({
  headline: "h1.storytitle, .story-text h1",
  author: ".byline__name a, .byline a",
  date: "time[datetime], .dateblock time",
  summary: ".storytext p:first-of-type",
  body: ".storytext, #storytext",
  audio: { selector: ".audio-module-listen a, .listen-button", attribute: "href" },
});

console.log(data);
await spider.close();

ready to run · spider-browser · TypeScript

Fetch API

One endpoint for npr.org.

Structured JSON from npr.org with a single POST. AI-resolved selectors, cached on the first call.

POST /fetch/npr.org/

HeadlineAuthorPublished dateProgramArticle bodyAudio URL

Try it Fetch docs

cURL

curl -X POST https://api.spider.cloud/fetch/npr.org/ \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"return_format": "json"}'

Python

import requests

resp = requests.post(
    "https://api.spider.cloud/fetch/npr.org/",
    headers={
        "Authorization": "Bearer YOUR_API_KEY",
        "Content-Type": "application/json",
    },
    json={"return_format": "json"},
)
print(resp.json())

Node.js

const resp = await fetch("https://api.spider.cloud/fetch/npr.org/", {
  method: "POST",
  headers: {
    "Authorization": "Bearer YOUR_API_KEY",
    "Content-Type": "application/json",
  },
  body: JSON.stringify({ return_format: "json" }),
});
const data = await resp.json();
console.log(data);

Extraction