Data validation and conversion is one of the truly tricky part of getting external data into your app. This might come from a REST API, a file on disk, or somewhere else. This includes checking for required fields, correct data types, converting from compatible types (for example, strings to numbers), and much more. Pydantic is one of the best ways to do this in modern Python using dataclass-like constructs and type annotations to make it all seamless and automatic.
We welcome Samuel Colvin, creator of Pydantic, to the show. We'll dive into the history of Pydantic and it's many uses and benefits.
Links from the showSamuel on Twitter: @samuel_colvin
pydantic: pydantic-docs.helpmanual.io
Contributing / help wanted @ pydantic: github.com
python-devtools package: python-devtools.helpmanual.io
IMPORTANT: PEP 563, PEP 649 and the future of pydantic #2678
GitHub issue on Typing: github.com
YouTube live stream video: youtube.com
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