better handling in deduperreload for patching functions with freevars #14960
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This looks good to me, thank you @smacke. I have one question before merging regarding the pickle vs deepcopy usage.
| ) | ||
| func_asts = [ast.parse(func_code)] | ||
| if len(cast(ast.FunctionDef, func_asts[0].body[0]).decorator_list) > 0: | ||
| without_decorator_list = pickle.loads(pickle.dumps(func_asts[0])) |
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Is it preferred over copy.deepcopy? It feels like deepcopy would be faster?
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Hey @krassowski thanks for the review and sorry I missed this! It turns out that when it is applicable, composing pickle.loads and pickle.dumps should always be faster than copy.deepcopy, because the former uses a fast C implementation while the latter uses a slower Python implementation for recursively traversing objects. The drawback of pickle / unpickle is that it only works for pickle-able objects, but fortunately Python ASTs happen to be one such type of object.
This is coming from my memory so let me know if you'd prefer to see it for yourself via some benchmarks ;)
This PR should fix #14958. When patching a decorated function, rather than giving it the union of the old version's and new version's freevars, we give it the old version's for anything callable, and the new version's for everything else. This ensure we use the old
__class__attribute and avoid errors such as "TypeError: super(type, obj): obj must be an instance or subtype of type". Using old versions of other callables is also better since these references are the ones we maintain in deduperreload, rather than the new references. It does, however, mean that we need to reload changed decorated functions twice: once without decorators (to ensure the old version gets patched), and once with. This PR handles that as well.Test plan: all the other unit tests pass + additionally added a new one which exercises this case.