Accidentally Building A Business With Python At Listen Notes

Summary Podcasts are one of the few mediums in the internet era that are still distributed through an open ecosystem. This has a number of benefits, but it also brings the challenge of making it difficult to find the content that you are looking for. Frustrated by the inability to pick and choose single episodes across various shows for his listening Wenbin Fang started the Listen Notes project to fulfill his own needs. He ended up turning that project into his full time business which has grown into the most full featured podcast search engine on the market. In this episode he explains how he build the Listen Notes application using Python and Django, his work to turn it into a sustainable business, and the various ways that you can build other applications and experiences on top of his API. Announcements Hello and welcome to Podcast.__init__, the podcast about Python’s role in data and science. When you’re ready to launch your next app or want to try a project you hear about on the show, you’ll need somewhere to deploy it, so take a look at our friends over at Linode. With the launch of their managed Kubernetes platform it’s easy to get started with the next generation of deployment and scaling, powered by the battle tested Linode platform, including simple pricing, node balancers, 40Gbit networking, dedicated CPU and GPU instances, and worldwide data centers. Go to pythonpodcast.com/linode and get a $100 credit to try out a Kubernetes cluster of your own. And don’t forget to thank them for their continued support of this show! Your host as usual is Tobias Macey and today I’m interviewing Wenbin Fang about the technology powering the Listen Notes podcast discovery platform Interview Introductions How did you get introduced to Python? Can you describe what Listen Notes is and the story behind it? What are some of the main goals that listeners have when searching for a podcast? What are the challenges that they commonly encounter when looking for information in a podcast? What are the different sources of information that you can use to extract useful details about a podcast? How do you identify and prioritize new features or product enhancements? Can you describe how the Listen Notes platform is architected? How has it changed or evolved since you first began working on it? How did you approach the technology selection for the initial version of Listen Notes? If you were to start over today, what might you do differently? What are the technical challenges that are posed by the ecosystem around podcasts? What are the biggest changes that have happened in the methods of production and consumption for podcasts since you first became involved in the space? How do you approach the design and contracts of the Listen Notes web API given how core that is to your platform? What are the most complex or complicated engineering projects that you have done for Listen Notes? What are the pieces of the infrastructure for podcasts that you would like to see improved, changed, or replaced? What are some of the kinds of projects that developers can build with the Listen Notes API? What, if any, impact have the introduction of podcasts to closed platforms such as Spotify, Amazon Music, etc. had on your business? What are some of the most surprising things that you have learned about podcasts and their consumption while building Listen Notes? What are the most interesting, innovative, or unexpected ways that you have seen Listen Notes used? What are the most interesting, unexpected, or challenging lessons that you have learned while working on Listen Notes? What do you have planned for the future of Listen Notes? Keep In Touch Website LinkedIn wenbinf on GitHub @wenbinf on Twitter Picks Tobias Wheel of Time TV Series Wenbin Superhuman email client Links Listen Notes Graphviz NextDoor PostgreSQL Elasticsearch Redis RabbitMQ Celery ReactJS Django Bootstrap CSS Digital Ocean Tailwind CSS Entity Resolution Clickhouse Data Engineering Podcast Episode The intro and outro music is from Requiem for a Fish The Freak Fandango Orchestra / CC BY-SA