NPR News Scraper by nexgendata

Extract NPR news articles including headlines, article text, author names, publication dates, categories, and associated audio/podcast links at scale. Built for media monitoring companies tracking public radio coverage and anyone who needs structured news data without the overhead of building a custom scraper.

What This Actor Does

The NPR News Scraper connects to NPR and extracts NPR news articles including headlines, article text, author names, publication dates, categories, and associated audio/podcast links. It handles pagination, rate limiting, and data normalization automatically so you get clean, structured JSON output ready for your database, dashboard, or analytics pipeline. No API keys to manage, no infrastructure to maintain.

Who Uses This

Media monitoring companies tracking public radio coverage, pr agencies measuring client mentions, content aggregators building comprehensive news feeds, and researchers analyzing public media content patterns. If you need news data at scale without building and maintaining your own extraction pipeline, this actor handles the heavy lifting.

What You Get Back

Each run produces a structured dataset in JSON format. Every record includes all available fields from the source, normalized into a consistent schema. The data is immediately available for export in JSON, CSV, or Excel format, or you can push it directly to your data warehouse via Apify integrations with Google Sheets, Slack, Webhooks, and 50+ other platforms.

How It Compares

NPR API was deprecated in 2020. RSS feeds provide limited metadata. NewsAPI charges $449/month for production access. Manual monitoring is impossible at scale. This actor delivers the same data at $3 per 1,000 articles with zero monthly commitment, no API key management, and results available in seconds. Pay only for what you use.

Sample Output

{
  "source": "npr-scraper",
  "data": "Structured news data fields",
  "timestamp": "2024-03-29T12:00:00Z",
  "url": "https://example.com/source"
}

Use Cases

Teams use the NPR News Scraper across a range of workflows. Analysts feed the output into business intelligence dashboards for real-time monitoring. Developers integrate it into automated data pipelines that run on daily or weekly schedules. Researchers use bulk exports for large-scale analysis projects. Marketing teams track competitive movements and industry trends. The structured output format means the data slots into virtually any downstream system with minimal transformation.

Pricing: $3 per 1,000 Articles

At $3/1K, processing 5,000 articles costs $15.00 total. A daily pipeline pulling 500 articles runs $1.50/day ($45/month). Compare that to building and maintaining your own scraping infrastructure, which typically costs $500-2,000/month in proxy fees, compute, and engineering time alone.

FAQ

How often can I run this? As often as you need. Schedule runs hourly, daily, or weekly through Apify's built-in scheduler, or trigger runs via API from your own systems.

What format is the output? JSON by default, with one-click export to CSV or Excel. You can also push results directly to Google Sheets, webhooks, or any HTTP endpoint via Apify integrations.

Do I need any API keys? No. The actor handles all authentication and access internally. Just configure your search parameters and run.

Can I integrate this with my existing tools? Yes. Apify supports integrations with Zapier, Make, Google Sheets, Slack, and direct webhook delivery. You can also use the Apify API to pull results programmatically into any system.