🎙️ Podcast Index Scraper

🚀 Export Podcast Index records in seconds. Title, author, description, feed URL, categories, episode count, language.

🕒 Last updated: 2026-05-29 · 📊 11 fields per record · Structured records · Ready for CSV, Excel, JSON, XML

The Podcast Index Scraper turns a public data source into a clean, structured dataset. Every record is normalized, numeric fields cast, and rate-limit notices surfaced as a clean error row instead of crashing the run.

🎯 Target Audience	💡 Primary Use Cases
📊 Analysts	Build datasets for reporting and BI
🏢 B2B teams	Enrich CRM and prospecting workflows
🤖 ML engineers	Construct training and evaluation sets
📰 Journalists	Verify facts with one click
👩‍💻 Developers	Mirror upstream data into your own database
🧪 Researchers	Snapshot a domain for longitudinal study

📋 What the Podcast Index Scraper does

• Queries the upstream source with the parameters you supply.
• Parses each record and flattens it into a single row.
• Casts numeric and date fields where appropriate.
• Surfaces upstream errors and rate limits as a clean error record.
• Exports as CSV, Excel, JSON, JSONL, XML, RSS, or HTML.

💡 Why it matters: raw upstream responses are rarely ready for analysis. This actor produces a flat, typed dataset you can drop straight into pandas, BigQuery, or a spreadsheet.

🎬 Full Demo

🚧 Coming soon.

⚙️ Input

Field	Type	Required	Description
query	string	No	Search term (podcast title, author, keyword).
maxItems	integer	No	Free users: Limited to 10 items (preview). Paid users: Optional, max 1,000,000

Example input:

{
  "maxItems": 10
}

⚠️ Good to Know: free Apify accounts are capped at 10 records per run. Upgrade for full datasets.

📊 Output

Field	Type	Description
image	mixed	Parsed field.
podcast_id	mixed	Parsed field.
title	mixed	Parsed field.
author	mixed	Parsed field.
description	mixed	Parsed field.
feed_url	mixed	Parsed field.
categories	mixed	Parsed field.
episode_count	mixed	Parsed field.
latest_pub_date	mixed	Parsed field.
language	mixed	Parsed field.
itunes_id	mixed	Parsed field.
scrapedAt	mixed	Parsed field.
error	mixed	Set if the upstream returned an error.

✨ Why choose this Actor

| 🆓 | Works on the free Apify plan up to 10 records per run. | | 🧹 | Clean snake_case keys ready for BI. | | 🔢 | Numeric casting baked in. | | 🛟 | Errors surfaced as data, never crashes. | | 💾 | One-click CSV, Excel, JSON, XML export. |

📈 How it compares to alternatives

Approach	Setup time	Clean keys	Error handling
Roll your own fetch	30 min +	❌	❌
Python wrapper lib	1 hr install + script	✅	partial
This Actor	5 sec, no install	✅	✅

🚀 How to use

1. Click Try for free.
2. Tweak the input fields or accept the defaults.
3. Click Start. Within seconds your dataset is ready, download as CSV, Excel, JSON, or XML.

💼 Business use cases

📊 Analytics. Pull a full snapshot into your warehouse and run aggregations.

🏢 B2B enrichment. Match upstream records against your CRM, score and prioritize.

📰 Newsroom. Verify a fact or source for a story in 30 seconds.

🤖 ML feature engineering. Build a typed, deduplicated training set in one run.

🔌 Automating Podcast Index Scraper

• Make / Zapier: trigger on schedule, push results to Airtable, Sheets, or Slack.
• Cron: native Apify scheduler.
• Webhooks: POST notification when a run finishes.
• Warehouse: ship rows straight to BigQuery, Snowflake, or Postgres.

🌟 Beyond business use cases

🎓 Education. Spin up a dataset for a classroom exercise in seconds.

🧪 Personal research. Track a topic over time, build a personal archive.

🤝 Non-profit & open data. Publish public dashboards without writing client code.

🧰 Tinkering. Prototype an app against real data without writing a scraper.

🤖 Ask an AI assistant about this scraper

Drop this README into ChatGPT, Claude, or any LLM and ask it to map your specific workflow to the actor's inputs. The schema, examples, and field list above contain everything an assistant needs to design a working pipeline.

❓ Frequently Asked Questions

❓ Do I need an API key? No setup needed. The operator pre-configures upstream access for paid runs.

❓ Is there a rate limit? Yes, the upstream source enforces its own limits. We surface rate-limit notices as a clean error record.

❓ Can I schedule runs? Yes, use Apify's native scheduler or hook into Make, Zapier, or cron.

❓ What format can I download? CSV, Excel, JSON, JSONL, XML, RSS, or HTML, straight from the dataset UI.

❓ Will the schema change? Core fields are stable. Optional fields may be added over time.

❓ Is this scraping or API? Whichever method is most reliable for the source. Both produce the same normalized output.

❓ How do you handle errors? Each error is pushed as a single-row record with an error field populated.

❓ Can I filter results? Yes, see the input schema above for every supported filter.

❓ Do you respect robots.txt? Yes, and only public endpoints are accessed.

❓ Where can I see sample output? Run the actor with the default inputs, the dataset preview shows live records.

🔌 Integrate with any app

Apify ships native integrations with Make, Zapier, Slack, Discord, Google Drive, Google Sheets, Gmail, Airbyte, Keboola, Telegram, GitHub, and any REST API or webhook endpoint.

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💡 Pro Tip: browse the complete ParseForge collection for 900+ production-grade scrapers across business intelligence, real estate, e-commerce, sports, finance, and public records.

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