Support encoding more dataclass-like things

[jcrist]

Previously we supported encoding dataclasses (determined as any object with a __dataclass_fields__ attribute), provided those objects were implemented in a way similar-enough to how they were implemented in the standard library. The intent was to support stdlib dataclasses, and if alternative implementations (e.g. pydantic.dataclasses) happened to work then all the better.

However, due to how we were detecting if an object was a dataclass, there was no way to override our builtin support if an alternative implementation (in this case edgedb.Object) didn't work.

To fix this, we now make fewer assumptions about how the backing dataclass object is implemented.

Pros:

• We can now natively encode objects implemented using dataclasses, pydantic.dataclasses, and edgedb.Object.
• We now only encode fields as declared on the dataclass object. Previously we encoded any attribute lacking a leading underscore, which was efficient and worked well in practice (it's also what orjson does). However, this can lead to weird behavior if some fields intentionally start with an _ (like _id in mongodb) or if the object makes use of functools.cached_property.

Cons:

• This flexibility and correctness comes at a performance cost. The fast path is the common case (dataclass uses __dict__, doesn't override __getattribute__), but encoding is now ~20% slower than before. Before we encoded __dict__ based dataclasses 20% faster than orjson; now we're faster for small classes and slower for larger numbers of fields (on my machine 12 fields is the crossover point). For __slots__ based classes we're still around 2x faster than orjson.

Fixes #495.

TODO:

• msgspec.json.encode
• msgspec.msgpack.encode
• msgspec.to_builtins
• tests
• update docs