Scrape podcast metadata from directories

Scraping podcast metadata from directories involves extracting structured information about podcasts—such as title, description, author, categories, episode titles, and release dates—from online podcast directories like Apple Podcasts, Spotify, Google Podcasts, or Podcast Index. Here’s a complete overview of how to scrape podcast metadata, tools you can use, best practices, and legal considerations.

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1. Common Podcast Metadata to Extract

When scraping from podcast directories, you can typically collect:

• Podcast Title

• Podcast Description

• Publisher/Author

• RSS Feed URL

• Language

• Categories/Genres

• Number of Episodes

• Episode Titles

• Episode Descriptions

• Release Dates

• Episode Duration

• Explicit Content Flag

• Cover Art URL

• Links to Hosting Platforms or Official Websites

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2. Target Podcast Directories

Some of the major podcast directories from which metadata can be extracted include:

• Apple Podcasts (via iTunes Search API or scraping)

• Spotify (official API for developers)

• Google Podcasts (scraping only; no public API)

• Podcast Index (public API available)

• Listen Notes (offers a powerful API)

• Podchaser (also provides an API)

• Player FM

• Pocket Casts

• Castbox

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3. Methods for Scraping Podcast Metadata

A. Using Public APIs

a. Apple Podcasts (iTunes Search API)

• Endpoint: https://itunes.apple.com/search?term=your_query&entity=podcast

• Sample Output: Podcast title, feed URL, genre, artwork, etc.

• Rate Limits: Generous for basic use

b. Spotify Web API

• Requires OAuth and developer registration

• Fetch podcast metadata and episodes

• Metadata includes popularity, publisher, episode list, etc.

c. Podcast Index

• Open-source, designed for developers

• Endpoint: https://api.podcastindex.org/api/1.0/search/byterm?q=your_query

• Returns full metadata including feeds, episodes, categories

d. Listen Notes API

• Freemium model with extensive metadata

• Supports advanced search, recommendations, and filters

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B. Web Scraping (When API is Not Available)

Tools:

• Python with BeautifulSoup and requests

• Browser automation via Selenium or Playwright

• Node.js with Puppeteer

Example (Python using BeautifulSoup):

python
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import requests
from bs4 import BeautifulSoup

url = 'https://podcasts.apple.com/us/podcast/example-podcast/id123456789'
headers = {'User-Agent': 'Mozilla/5.0'}
response = requests.get(url, headers=headers)
soup = BeautifulSoup(response.text, 'html.parser')

title = soup.find('h1').text.strip()
author = soup.find('span', class_='product-header__identity').text.strip()
description = soup.find('p', class_='product-header__description').text.strip()

print(f"Title: {title}nAuthor: {author}nDescription: {description}")

Challenges:

• Pages often use dynamic content (requires headless browsers)

• Rate limiting or IP blocking

• Parsing HTML structure changes

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4. RSS Feed Parsing

Each podcast usually has a unique RSS feed, which provides full metadata in XML format.

Example Tools:

• Python’s feedparser library

• Online RSS parsers and aggregators

Sample Code (Python):

python
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import feedparser

feed_url = 'https://rss.art19.com/example-podcast'
feed = feedparser.parse(feed_url)

print(f"Podcast: {feed.feed.title}")
for entry in feed.entries[:5]:
    print(f"Episode: {entry.title} - {entry.published}")

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5. Storage of Metadata

Collected metadata can be stored in:

• JSON or CSV files for analysis

• Relational databases like MySQL or PostgreSQL

• NoSQL databases like MongoDB

• Elasticsearch for fast querying

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6. Automation and Scaling

For large-scale operations:

• Use Scrapy framework in Python for scalable scraping

• Implement rotating proxies and user-agents to avoid bans

• Schedule scraping using cron jobs or task queues (Celery, Airflow)

• Cache results to reduce repeated requests

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7. Legal and Ethical Considerations

• Always check the Terms of Service of each directory

• APIs are usually the safest and most compliant method

• Respect robots.txt directives when scraping

• Use metadata for fair use cases (e.g., search engines, recommendation engines)

• Avoid overloading servers with aggressive scraping

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8. Use Cases for Scraped Metadata

• Podcast search engines

• Aggregators and directories

• Recommendation systems

• Market research

• Content indexing

• Sentiment analysis from episode descriptions or titles

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9. Rate Limits and API Pricing (as of 2025)

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Conclusion

Scraping podcast metadata can be effectively done using a mix of public APIs, RSS feed parsing, and web scraping techniques. For reliability and scalability, APIs like Podcast Index and Listen Notes are optimal, while RSS feeds provide detailed and up-to-date information on individual episodes. Web scraping should be your fallback when APIs are not available, and legal guidelines must always be respected. With proper planning, you can build powerful podcast applications, aggregators, or research tools.