This is a minimal working implementation of "code-caching" for dataclasses. It's heavily inspired by https://github.com/dabeaz/dataklasses, and works by reusing generated code objects for dataclasses that differ only in the names of their fields. "Template" code objects are lazily created with placeholder values (__field_0__, __field_1__) that are patched at method generation time using their replace method. Annotations and default arguments for __init__ methods are assigned manually, as well.

I thought I would stop here and gather feedback/review before going further. A bit more information:

For microbenchmarks on "simple" dataclasses with 1-10 elements and no "special" fields, this branch results in 2x-3x faster class generation time. The test_dataclasses suite, which contains lots of examples of advanced use-cases and actually does some real work with them, runs about 40% faster vs. main.

I've also included some counters for measuring cache stats. These indicate that when running test_dataclasses, 1,428 methods are generated, but only 112 don't have suitable templates in the code cache yet and need to be constructed using exec. So even for the wide range of dataclasses present in this program, we're still able to maintain a hit rate above 90% (__init__ methods are, predictably, the source of most of the misses).