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from __future__ import annotations
from typing import TYPE_CHECKING, Any
if TYPE_CHECKING:
from pydantic_core import core_schema as cs
N = 5 # arbitrary number that takes ~0.05s per run
class MyModel:
# __slots__ is not required, but it avoids __pydantic_fields_set__ falling into __dict__
__slots__ = '__dict__', '__pydantic_fields_set__', '__pydantic_extra__', '__pydantic_private__'
def schema_using_defs() -> cs.CoreSchema:
definitions: list[cs.CoreSchema] = [
{'type': 'int', 'ref': 'int'},
{
'type': 'model',
'cls': MyModel,
'schema': {
'type': 'model-fields',
'fields': {
str(c): {'type': 'model-field', 'schema': {'type': 'definition-ref', 'schema_ref': 'int'}}
for c in range(N)
},
},
'ref': f'model_{N}',
},
]
level = N
for level in reversed(range(N)):
definitions.append(
{
'type': 'model',
'cls': MyModel,
'schema': {
'type': 'model-fields',
'fields': {
str(c): {
'type': 'model-field',
'schema': {'type': 'definition-ref', 'schema_ref': f'model_{level+1}'},
}
for c in range(N)
},
},
'ref': f'model_{level}',
}
)
return {
'type': 'definitions',
'definitions': definitions,
'schema': {'type': 'definition-ref', 'schema_ref': 'model_0'},
}
def inlined_schema() -> cs.CoreSchema:
level = N
schema: cs.CoreSchema = {
'type': 'model',
'cls': MyModel,
'schema': {
'type': 'model-fields',
'fields': {str(c): {'type': 'model-field', 'schema': {'type': 'int'}} for c in range(N)},
},
'ref': f'model_{N}',
}
for level in reversed(range(N)):
schema = {
'type': 'model',
'cls': MyModel,
'schema': {
'type': 'model-fields',
'fields': {str(c): {'type': 'model-field', 'schema': schema} for c in range(N)},
},
'ref': f'model_{level}',
}
return schema
def input_data_valid(levels: int = N) -> Any:
data = {str(c): 1 for c in range(N)}
for _ in range(levels):
data = {str(c): data for c in range(N)}
return data
if __name__ == '__main__':
from pydantic_core import SchemaValidator
SchemaValidator(schema_using_defs()).validate_python(input_data_valid())
SchemaValidator(inlined_schema()).validate_python(input_data_valid())
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