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You can use static type analysers and runtime type profilers to add type annotations to a legacy codebase, but the interesting bit would be if you're built on top of a large untyped codebase you don't control like, say, Django, how far it can go.
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I would imagine that the LLM has a much easier time adding correct type annotations to old Python code than it does translating it to C.
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In my experiments with this, maybe, sorta, it'll do some AST stuff then it'll go "dang this shit is dynamic AF" then suggest a static type inference tool, then a runtime type profiler.

Which honestly, is the right approach.

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