Ruff handles black, flake8 and isort in one package, and is way faster.
The isort rules had not been enforced, so this commit includes a lot
of import resorting changes.
I switched to flake8-bugbear and the standard black-compatible line
length of 80 + 10% (so max 88 characters), so some line reflowing is
included too.
Finally, because bugbear rightly points out that `setattr()` is less
performant, I've switched the `__signature__` assigment back to using
a direct assignment with type ignore comment.
- Compatibility with older Python versions
- use `Optional` and `Union` instead of `... | None` and `a | b`
- use `typing_extensions.Protocol` instead of `typing.Protocol`
- use `typing.Dict`, `typing.List`, etc. instead of the concrete types.
- Fix backend `.get()` annotations; not all were marked as `Optional[str]`
- Don't return anything from `Backend.set()` methods.
- The `Coder.decode_as_type()` type parameter must be a type to be
compatible with `ModelField(..., type_=...)`.
- Clean up `Optional[]` use, remove where it is not needed.
- Clean up variable use in decorator, keeping the raw cached value
separate from the return value from the wrapped endpoint.
- Annotate the wrapper as returning either the original type _or_ a
Response (returning a 304 Not Modified response).
- Clean up small edge-case where `response` could be `None`.
- Correct type annotation on `JsonCoder.decode()` to match `Coder.decode()`.
This is, for the majority of backends, the native format anyway, and so
we save encoding and decoding when using the PickleCodec or if (in future)
a orjson Coder was to be added.
For the JsonCodec, the only thing that changed is the location where the
JSON data is encoded to bytes and decoded back again to a string.
In `timeit` tests, 10.000 calls to `ModelField()` could take up to half
a second on my Macbook Pro M1, depending on the type annotation used.
Given that the method is called for every cache hit, this can really add
up. The number of different return types for endpoints is very much
finite however, so caching is a definite win here.
Use the return annotation to decode cached data to the correct type.
This follows the same logic FastAPI uses to JSON request bodies.
For the PickleCoder, this is a no-op as pickle already stores type
information in the serialised data.
