DRY DataFrameModel fields #1497
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lundybernard
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Given many data fields from various sources (raw input, computed, normalized, etc),
I need to create many DataFrameModels, composed of different sets of these fields.
I want to re-use field/column/DataFrameModel definitions to DRYup the code as much as possible.
I have had some success re-using DataFrameModels:
Config
sub-classesHowever, this approach breaks down if I try to build intermediate collections of fields
This breaks down due to the classic diamond-shaped MRO problem
I have attempted to refactor the code using Mixin classes, the standard solution to this problem, but that approach breaks the
.to_schema()
method.This breaks at this point, even before we get to nested collections of fields.
Before delving any deeper into the inner-workings of
_collect_fields
I wanted to stop and ask for advice.What is the best, most pythonic, most Pandera'ic, way to create DRY, structured, DataFrameModels like this?
Primary concerns:
.strategy()
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