Introduce a schema variant to reuse Validators, Serializers and CoreSchema

[BoxyUwU]

Introduces a nested CoreSchema variant that reuses the specified model's schema/validator/serializer. As an example, the core schema for the following pydantic models:

class A(BaseModel):
    field3: 'B'

class B(BaseModel):
    field1: list[A]

class Wrapper(BaseModel):
    a: A
    b: B

{
    'type': 'model',
    'cls': <class '__main__.A'>,
    'schema': {
        'type': 'model-fields',
        'fields': {
            'field3': {
                'type': 'model-field',
                'schema': {
                    'type': 'nested',
                    'cls': <class '__main__.B'>,
                    'get_info': <function GenerateSchema._generate_schema_from_property.<locals>.get_model_info at 0x7f9ec650be20>
                }
            }
        },
        'model_name': 'A'
    },
    'ref': '__main__.A:20628480'
}
{
    'type': 'model',
    'cls': <class '__main__.B'>,
    'schema': {
        'type': 'model-fields',
        'fields': {
            'field1': {
                'type': 'model-field',
                'schema': {
                    'type': 'list',
                    'items_schema': {
                        'type': 'nested',
                        'cls': <class '__main__.A'>,
                        'get_info': <function GenerateSchema._generate_schema_from_property.<locals>.get_model_info at 0x7f9ec650ba60>
                    }
                }
            }
        },
        'model_name': 'B'
    },
    'ref': '__main__.B:20632592'
}
{
    'type': 'model',
    'cls': <class '__main__.Wrapper'>,
    'schema': {
        'type': 'model-fields',
        'fields': {
            'a': {
                'type': 'model-field',
                'schema': {
                    'type': 'nested',
                    'cls': <class '__main__.A'>,
                    'get_info': <function GenerateSchema._generate_schema_from_property.<locals>.get_model_info at 0x7f9ec650bec0>
                }
            },
            'b': {
                'type': 'model-field',
                'schema': {
                    'type': 'nested',
                    'cls': <class '__main__.B'>,
                    'get_info': <function GenerateSchema._generate_schema_from_property.<locals>.get_model_info at 0x7f9ec65c8040>
                }
            }
        },
        'model_name': 'Wrapper'
    },
    'ref': '__main__.Wrapper:20635728'
}

Compare to the schema generated on main

{
    'type': 'definitions',
    'schema': {'type': 'definition-ref', 'schema_ref': '__main__.A:37460656'},
    'definitions': [
        {
            'type': 'model',
            'cls': <class '__main__.A'>,
            'schema': {
                'type': 'model-fields',
                'fields': {'field3': {'type': 'model-field', 'schema': {'type': 'definition-ref', 'schema_ref': '__main__.B:37433488'}}},
                'model_name': 'A'
            },
            'ref': '__main__.A:37460656'
        },
        {
            'type': 'model',
            'cls': <class '__main__.B'>,
            'schema': {
                'type': 'model-fields',
                'fields': {'field1': {'type': 'model-field', 'schema': {'type': 'list', 'items_schema': {'type': 'definition-ref', 'schema_ref': '__main__.A:37460656'}}}},
                'model_name': 'B'
            },
            'ref': '__main__.B:37433488'
        }
    ]
}
{
    'type': 'definitions',
    'schema': {'type': 'definition-ref', 'schema_ref': '__main__.B:37433488'},
    'definitions': [
        {
            'type': 'model',
            'cls': <class '__main__.A'>,
            'schema': {
                'type': 'model-fields',
                'fields': {'field3': {'type': 'model-field', 'schema': {'type': 'definition-ref', 'schema_ref': '__main__.B:37433488'}}},
                'model_name': 'A'
            },
            'ref': '__main__.A:37460656'
        },
        {
            'type': 'model',
            'cls': <class '__main__.B'>,
            'schema': {
                'type': 'model-fields',
                'fields': {'field1': {'type': 'model-field', 'schema': {'type': 'list', 'items_schema': {'type': 'definition-ref', 'schema_ref': '__main__.A:37460656'}}}},
                'model_name': 'B'
            },
            'ref': '__main__.B:37433488'
        }
    ]
}
{
    'type': 'definitions',
    'schema': {
        'type': 'model',
        'cls': <class '__main__.Wrapper'>,
        'schema': {
            'type': 'model-fields',
            'fields': {
                'a': {'type': 'model-field', 'schema': {'type': 'definition-ref', 'schema_ref': '__main__.A:37460656'}},
                'b': {'type': 'model-field', 'schema': {'type': 'definition-ref', 'schema_ref': '__main__.B:37433488'}}
            },
            'model_name': 'Wrapper'
        },
        'ref': '__main__.Wrapper:37440960'
    },
    'definitions': [
        {
            'type': 'model',
            'cls': <class '__main__.A'>,
            'schema': {
                'type': 'model-fields',
                'fields': {'field3': {'type': 'model-field', 'schema': {'type': 'definition-ref', 'schema_ref': '__main__.B:37433488'}}},
                'model_name': 'A'
            },
            'ref': '__main__.A:37460656'
        },
        {
            'type': 'model',
            'cls': <class '__main__.B'>,
            'schema': {
                'type': 'model-fields',
                'fields': {'field1': {'type': 'model-field', 'schema': {'type': 'list', 'items_schema': {'type': 'definition-ref', 'schema_ref': '__main__.A:37460656'}}}},
                'model_name': 'B'
            },
            'ref': '__main__.B:37433488'
        }
    ]
}

This is similar to the current definitions-ref setup but it has a number of benefits:

• The nested model does not need to have its schema built already in order to reuse it. Currently sometimes (I think) we build the core schema for a model twice if it has not been built by the first time it is referenced in another model.
• The nested models schema is not inlined so the built CoreSchema is smaller which means walking it can be significantly faster in cases with lots of nested models when we do not need to recurse into `nested-model
• There is no "flattening" step after generating the schema like with definitions schemas where we walk the built schema and ensure that any nested models' schemas does not have a definitions schema. This is what I believe is a significant portion of the performance wins since we now have to do significantly less complex tree traversals over python datastructures in python.
• We can reuse validators and serializers with this setup which in theory should result in less memory overhead in cases with deeply recursive model definitions where the innermost model may have its validator constructed significantly
  more times than once

See pydantic/pydantic#10246 for the implementation of generating this new schema variant and also the benchmak results.

Before Merging

• We don't propagate errors out of serde_serialize
• The PyGcTraversible implementation for Result ignores the error variant as PyErr is not traversible
• Make sure that the nested schema variant is defined flexibly enough to be useable for more than just models.
• Make sure that Pydantic side of reusing validators and serializers pydantic#10246 can be merged with positive perf wins otherwise there's no point :3

---

There is an issue pydantic/pydantic#10394 tracking future work on the pydantic side to use this schema more

[sydney-runkle]

@adriangb, would love to get your feedback on this as well!

[sydney-runkle]

Interesting concepts here. I have some reservations about application for things like schemas with forward refs, but this looks like a promising start.

A few questions:

• What type of benchmarking have you been able to do to in order to look at both time / memory comparisons against main?
• This strikes me as pretty similar to our current pattern used here, at least conceptually. Why should we go about it in this way, instead? Perhaps the memory usage is better because we're not actually rebuilding the schema validator / serializer itself?
• I feel like integration with pydantic here would be a bit of a challenge, especially in the namespace realm. Have you thought about how we might handle refs to other models (schemas) in different modules, functions, etc? Definitely ok if not, just wanted to gauge progress here.

I think some helpful next steps would be:

1. Get some feedback from @samuelcolvin, @davidhewitt, and @adriangb.
2. Post folks familiarizing themselves with said changes, we could set aside some time to chat about this in our next oss sync 🚀.

[codspeed-hq]

CodSpeed Performance Report

Merging #1414 will not alter performance

_{Comparing boxy/validator_serializer_reuse (f6508d2) with main (ba8eab4)}

Summary

✅ 155 untouched benchmarks

[sydney-runkle]

Closing in favor of #1616 :) will add you as a co-author there cc @BoxyUwU