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GKS schemas often include maturity model annotations on objects and properties to indicate some expectation of model stability. It'd be nice to access this somehow within VRS-Python.
Most naive solution: put it in the docstring. Not machine-readable, but simple to implement.
Maybe the next simplest solution: include it as part of the model_json_schema() output. This is computationally accessible, albeit somewhat indirectly so. It would most directly match the schema itself.
Implement as some kind of private or dunder field on each schema class, e.g. Allele.__maturity__ = <MaturityModel.TRIAL_USE>. Not sure of what the equivalent way to get property maturity would be, though.
Possible use cases/helper functions to implement
A function that takes a Ga4ghIdentifiableObject and tells you which components or properties are most immature, i.e. are most liable to change in structure in future releases
A function that takes a Ga4ghIdentifiableObject and tells you whether it contains any components or properties that are below a particular maturity model threshold and/or are deprecated
The text was updated successfully, but these errors were encountered:
GKS schemas often include maturity model annotations on objects and properties to indicate some expectation of model stability. It'd be nice to access this somehow within VRS-Python.
model_json_schema()
output. This is computationally accessible, albeit somewhat indirectly so. It would most directly match the schema itself.Allele.__maturity__ = <MaturityModel.TRIAL_USE>
. Not sure of what the equivalent way to get property maturity would be, though.Possible use cases/helper functions to implement
Ga4ghIdentifiableObject
and tells you which components or properties are most immature, i.e. are most liable to change in structure in future releasesGa4ghIdentifiableObject
and tells you whether it contains any components or properties that are below a particular maturity model threshold and/or are deprecatedThe text was updated successfully, but these errors were encountered: