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Add transform proposal #113
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The proposed `Transform` class is a thin, possibly stateful class mapping records to other records. It is generally assumed to be invertible, which is expressed by the addition of an `iapply()` method (name pending), which can be used to (approximately) revert records to their old form IF the given transform supports it. The added script showcases both proposals, with a barebones example of why it is useful: To serialize a given model into a set of digestible, unique identifiers, and doing the reverse in the inverse method. This way, even custom model classes can be written to JSON, where they are (very simply) saved via their chosen transform parametrization.
Contains the basic definitions for 1->1, N->1 and N->N record transforms. Right now, this comes without guarantees or enforcement of attributes (invertibility/length preservation), but this can be added in the future. Users have to mark transform capabilities on their own.
Thanks to the new base class, this is a no-brainer.
Covers the basic ideas, includes a usage example, and gives tips on what to consider when designing transforms.
maxmynter
approved these changes
Mar 15, 2024
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We could make the apply
method abstract and then infer the invertible
property based on whether iapply
is overridden.
Trim a leftover comment, adjusting the snippet line numbers in the process.
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Based on the changes contained in #110 (although mostly if not entirely orthogonal).
The proposed
Transform
class is a thin, possibly stateful class mappingrecords to other records.
It is generally assumed to be invertible, which is expressed by the
addition of an
iapply()
method (name pending), which can be used to(approximately) revert records to their old form IF the given transform
supports it.
The added script showcases both proposals, with a barebones example of
why it is useful: To serialize a given model into a set of digestible,
unique identifiers, and doing the reverse in the inverse method.
This way, even custom model classes can be written to JSON, where they
are (very simply) saved via their chosen transform parametrization.