[REF-2089] Use dill instead of cloudpickle for serialization #2922
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* smaller size pickles * support dynamically defined states * avoid issues with unpickleable globals
Instead of converting the functions up front and assigning them to the instance, unbox the function from the EventHandler when it is requested via __getattribute__. This reduces the size of the per-instance pickle, because event handler bodies do not need to be included.
Because pydantic can be installed without cython, only use the workaround in the case where the BaseModel.validate function is NOT a FunctionType, indicating it's a cython function.
picklelo
approved these changes
Mar 27, 2024
martinxu9
approved these changes
Mar 27, 2024
| @@ -2159,6 +2187,25 @@ async def modify_state(self, token: str) -> AsyncIterator[BaseState]: | |||
| await self.set_state(token, state) | |||
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| # Workaround https://github.com/cloudpipe/cloudpickle/issues/408 for dynamic pydantic classes | |||
| if not isinstance(State.validate.__func__, FunctionType): | |||
| cython_function_or_method = type(State.validate.__func__) | |||
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so what type is a cython function?
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a cython function is compiled to C via the cython library. there's no importable name for it though, because it masquerades as a builtin, but it's not accessible as a builtin name.
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similar to the builtin function or method types, but those types are exposed via types.FunctionType and types.MethodType respectively
Lendemor
approved these changes
Mar 27, 2024
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Dynamically convert EventHandler to functools.partial
This gets us a step closer to EventHandler as descriptor without breaking any tests or existing functionality.