Universal RSS & Podcast XML Feed Normalizer avatar

Universal RSS & Podcast XML Feed Normalizer

Pricing

from $1.10 / 1,000 normalized feed channels

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Universal RSS & Podcast XML Feed Normalizer

Universal RSS & Podcast XML Feed Normalizer

Parses and normalizes any RSS, Atom, or Podcast XML feed into clean structured JSON. Extracts audio enclosures, durations, authors, episode notes, and full article contents.

Pricing

from $1.10 / 1,000 normalized feed channels

Rating

0.0

(0)

Developer

David Sandor

David Sandor

Maintained by Community

Actor stats

0

Bookmarked

2

Total users

1

Monthly active users

3 days ago

Last modified

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Universal RSS & Podcast XML Feed Normalizer 🚀

Parses and normalizes any RSS, Atom, or Podcast XML feed into clean structured JSON. Extracts audio enclosures, durations, authors, episode notes, and full article contents.

🌟 20+ Enterprise Enhancements (v2.0)

  • RAG & LLM Ready: Pre-computed OpenAI token counts and chunked embeddings.
  • Smart Keyword Filters: Include or exclude records by targeted keyword lists.
  • Sentiment Scoring: Built-in lexical sentiment rating on text contents.
  • Noise & Tracking Scrubber: Removes tracking query parameters and boilerplate banners.
  • Pay-Per-Event (PPE): Ultra-cost-effective pricing per extracted item.
  • Zero Cold Start: Sub-second execution with automated fallback guarantees.

💻 Integration Examples

Node.js (Apify Client)

import { ApifyClient } from 'apify-client';
const client = new ApifyClient({ token: 'YOUR_APIFY_TOKEN' });
const run = await client.actor('rss-podcast-feed-normalizer').call({
// Pass customized inputs here
enableRagEnrichment: true
});
const { items } = await client.dataset(run.defaultDatasetId).listItems();
console.log('Extracted Items:', items);

Python

from apify_client import ApifyClient
client = ApifyClient('YOUR_APIFY_TOKEN')
run = client.actor('rss-podcast-feed-normalizer').call(run_input={ 'enableRagEnrichment': True })
for item in client.dataset(run['defaultDatasetId']).iterate_items():
print(item)

📄 Output Schema

Returns structured JSON, token counts, and RAG vector chunks.