Parser (Pydantic) re-export Pydantic errors for data model validation

[kPOWz]

Use case

When writing validators and root validators it is useful to keep error formats consistent with the Pydantic TypeErrors and ValueErrors from the Pydantic errors module

Due to how Pydantic is packaged, these errors are not exported by https://github.com/awslabs/aws-lambda-powertools-python/blob/develop/aws_lambda_powertools/utilities/parser/pydantic.py#L5

https://awslabs.github.io/aws-lambda-powertools-python/2.1.0/utilities/parser/#data-model-validation

Solution/User Experience

re-export the LPT packaged Pydantic errors module under from aws_lambda_powertools.utilities.parser.pydantic.errors

ensure this will still work smoothly after switch to rust / pydantic core

Alternative solutions

No response

Acknowledgment

• This feature request meets Lambda Powertools Tenets
• Should this be considered in other Lambda Powertools languages? i.e. Java, TypeScript

[heitorlessa]

Hey @kPOWz, would this work?

Looking at Pydantic exported symbols, there doesn't seem to be any clash so I can export them directly too.

https://github.com/awslabs/aws-lambda-powertools-python/pull/1728/files#diff-802361d017af63e8fc18b5df568bbdfc17800ab8b90ef502a64a907ce4ef917bR9

[heitorlessa]

Just read Pydantic V2 plan and the only breaking change it seems to apply here is parse_raw that we use in Parser. I couldn't find a specific mention on errors packaging.

I'll go ahead and merge the errors exposing, since parser.pydantic.errors wouldn't work as it's not a package and doesn't seem to need to be.

Because it's a major version, we will come to that when we need to cross that bridge. I think there's a great chance in the future to make Pydantic built-in in Powertools to ease developing certain features like Feature Flags - the benchmarks and reduced package size look fantastic, but we need to apply due-diligence and weigh its pros/cons as usual.

[github-actions]

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[github-actions]

This is now released under 2.3.0 version!