[Feature Request] Add support for clipping values during type enforcement

[svengiegerich]

Is your feature request related to a problem? Please describe.

Currently, when enforcing a schema where data exceeds the range of the target dtype (e.g., a value of 260 for a uint8 column), the operation may fail or lead to silent overflows. In production environments, it is often preferable to bound these values rather than allowing the pipeline to crash or produce corrupted data.

Describe the solution you'd like

I would like to see an option—perhaps a parameter like out_of_bounds="clip"—within the schema enforcement logic. When enabled, any value exceeding the maximum or minimum of the target numeric type would be clipped to that type's limit.

Example Scenario

Target Dtype: uint8 (Range: 0 to 255)

Input Value: 260

Expected Result (with clipping): 255

Describe alternatives you've considered

The current alternative is to manually call .clip() on the DataFrame before validation, but this duplicates logic that could be handled more efficiently during the schema enforcement/casting phase.

[AndreasAlbertQC]

hey @svengiegerich!

In production environments, it is often preferable to bound these values rather than allowing the pipeline to crash or produce corrupted data.

I'm not sure I follow entirely: silently clipping values that don't fit a dtype sounds exactly like data corruption, leading to hard-to-predict downstream behavior. I'd be a little apprehensive about exposing this as a standard option because I would have a hard time recommending this approach to anyone. Why would you prefer to accept possible clipping instead of just increasing the size of your dtype?