Podcasts are everywhere…
We were contacted by the team at PodcastWise to build a scraping and aggregation platform for over 2.6 million podcasts and their episodes. Using Python, we created a distributed scraping system that updates all 2.6 million podcasts daily, checking for new episodes, reviews, and social content.
To manage the scraping process efficiently, we implemented RabbitMQ as a scraping queue. This allows us to dynamically scale the number of queue-working servers based on the queue size, ensuring optimal performance and resource utilization. The system can scale up during peak times to handle larger loads and scale down when demand is lower, maintaining efficiency and cost-effectiveness.
The collected data is then fed into AI models that generate recommendations for podcast marketers, helping them identify the best matches for their marketing dollars. By leveraging advanced Python capabilities and RabbitMQ for queue management, we have developed a robust and scalable solution that meets the needs of PodcastWise.
This platform not only keeps pace with the dynamic nature of podcast content but also offers valuable insights for marketers looking to maximize their reach and effectiveness. Our innovative approach has enabled PodcastWise to stay ahead in the competitive podcasting industry, ensuring they provide top-tier services to their users.
