fix: skip redundant isinstance dispatch for homogeneous model unions - #1487
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When a property is a union of schemas that are all object/model types (e.g. `oneOf: [ModelA, ModelB]`), `union_property.py.jinja`'s `transform` macro generated a per-member `isinstance` dispatch in `to_dict()`, even though every branch does the exact same thing (`.to_dict()`). The check never affects the outcome, since every generated model class converts identically. Detect when every union member is model-shaped and skip the per-member dispatch: - required: unconditional `dest = source.to_dict()`, no isinstance at all - optional: `else: dest = source.to_dict()` after the existing Unset guard - optional request bodies (`skip_unset=True`, no Unset guard emitted yet): guard with `if not isinstance(source, Unset)` instead of the previous single-member `isinstance(source, ModelX)` check Mixed unions (model + primitive/enum/None/Any members) are unaffected and keep their existing per-member dispatch, since those branches genuinely differ in behavior. Discussion: openapi-generators#1486
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When a property is a union of schemas that are all object/model types (e.g.
oneOf: [ModelA, ModelB]),union_property.py.jinja'stransformmacro generated a per-memberisinstancedispatch into_dict(), even though every branch does the exact same thing (.to_dict()). The check never affects the outcome, since every generated model class converts identically.Detect when every union member is model-shaped and skip the per-member dispatch:
dest = source.to_dict(), no isinstance at allelse: dest = source.to_dict()after the existing Unset guardskip_unset=True, no Unset guard emitted yet): guard withif not isinstance(source, Unset)instead of the previous single-memberisinstance(source, ModelX)checkMixed unions (model + primitive/enum/None/Any members) are unaffected and keep their existing per-member dispatch, since those branches genuinely differ in behavior.
pdm run checkrun succesfully.Discussion: #1486
Full disclosure: I used Claude Sonnet to help with the development. Feel free to point our any AI slop, happy to fix it