Insights from my Software Engineering Radio interview with Samuel Colvin
Introduction
In a recent episode of the Software Engineering Radio podcast, I interviewed Samuel Colvin, the CEO and founder of the Pydantic company. Our conversation focused on Pydantic, a popular data validation library for Python, and its ecosystem, including Pydantic AI and Logfire. During our interview, Samuel offers many insights into how these tools can help Python developers build more robust and reliable applications.
Insights
I’m thankful for this thought-provoking discussion with Samuel Colvin! Before you listen to the full episode, please checkout some of its insights:
What is Pydantic and how does it help with data validation?
“So Pydantic, to all intents and purposes, is a data validation library for Python. But it does a bunch more stuff above and beyond simple data validation — like controlling serialization, coercion when you’re validating and generating JSON schema.”
What were the motivations for rewriting Pydantic V2 in Rust?
“Initially the internals of Pydantic were all Python. I wasn’t particularly proud of the internals. And so at the beginning of 2022, I started working full-time on Pydantic, rebuilding the core in Rust. There’s an amazing library called Py03 that allows you to write Python extensions in Rust, which gives you an enormous performance improvement. But it’s actually, it goes beyond simply the performance. It allows you to write fundamentally more robust and scalable and maintainable code when you’re building these big, performance- critical complex applications.”
How does Pydantic AI help developers interact with large language models (LLMs)?
“So the number one piece of value I think that Pydantic AI brings is this model agnosticism. You can switch in and out of OpenAI, Anthropic, Gemini, Grok, DeepSeek, et cetera, et cetera, Mistral, Cohere, with one line of code.”
What is Logfire and how does it help with observability?
“Logfire is an observability platform. We do logs, traces and metrics that let you understand and monitor your application. It is very useful when you’re building applications in Python in general, but particularly AI applications.”
Listen
If you’re interested in learning more about Pydantic and its ecosystem, I highly recommend listening to my interview with Samuel Colvin on Software Engineering Radio! You can find it on your favorite podcast player, Apple Podcasts, Spotify, YouTube, or you can listen to it with this handy podcast player.