Exploring Pydantic: From Open Source to Performance Enhancements

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This chapter delves into a discussion about Pydantic, the popular data validation library for Python, covering topics such as transitioning from open source contributions to commercial development, the benefits of Pydantic in handling JSON data and nested JSON, its evolution from version 1 to version 2 with significant performance gains using Rust, maintenance strategies, Pydantic performance tips, and its impact on the Python ecosystem.

You're using Pydantic and it seems pretty straightforward, right? But could you adopt some simple changes to your code that would make it a lot faster and more efficient? Chances are, you'll find a couple of the tips from Sydney Runkle that will do just that. Join us to talk about Pydantic performance tips here on Talk Python.

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Links from the show

Sydney Runkle: linkedin.com
Pydantic: pydantic.dev
Performance docs: docs.pydantic.dev
Union tips: docs.pydantic.dev
Sydney's presentation slides: docs.google.com
JSON to Pydantic: jsontopydantic.com
Samuel talking FastUI: talkpython.fm

CodeFlash: codeflash.ai
Codspeed: codspeed.io
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm

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