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⚡ Feature: 优化依赖注入在 pydantic v2 下的性能 (#2870)
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@ -8,17 +8,20 @@ FrontMatter:
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"""
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from collections.abc import Generator
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from functools import cached_property
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from dataclasses import dataclass, is_dataclass
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from typing_extensions import Self, get_args, get_origin, is_typeddict
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from typing import (
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TYPE_CHECKING,
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Any,
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Union,
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Generic,
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TypeVar,
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Callable,
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Optional,
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Protocol,
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Annotated,
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overload,
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)
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from pydantic import VERSION, BaseModel
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@ -46,8 +49,8 @@ __all__ = (
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"DEFAULT_CONFIG",
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"FieldInfo",
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"ModelField",
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"TypeAdapter",
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"extract_field_info",
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"model_field_validate",
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"model_fields",
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"model_config",
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"model_dump",
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@ -63,9 +66,10 @@ __autodoc__ = {
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if PYDANTIC_V2: # pragma: pydantic-v2
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from pydantic import GetCoreSchemaHandler
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from pydantic import TypeAdapter as TypeAdapter
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from pydantic_core import CoreSchema, core_schema
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from pydantic._internal._repr import display_as_type
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from pydantic import TypeAdapter, GetCoreSchemaHandler
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from pydantic.fields import FieldInfo as BaseFieldInfo
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Required = Ellipsis
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@ -125,6 +129,25 @@ if PYDANTIC_V2: # pragma: pydantic-v2
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"""Construct a ModelField from given infos."""
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return cls._construct(name, annotation, field_info or FieldInfo())
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def __hash__(self) -> int:
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# Each ModelField is unique for our purposes,
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# to allow store them in a set.
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return id(self)
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@cached_property
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def type_adapter(self) -> TypeAdapter:
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"""TypeAdapter of the field.
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Cache the TypeAdapter to avoid creating it multiple times.
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Pydantic v2 uses too much cpu time to create TypeAdapter.
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See: https://github.com/pydantic/pydantic/issues/9834
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"""
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return TypeAdapter(
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Annotated[self.annotation, self.field_info],
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config=None if self._annotation_has_config() else DEFAULT_CONFIG,
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)
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def _annotation_has_config(self) -> bool:
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"""Check if the annotation has config.
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@ -152,10 +175,9 @@ if PYDANTIC_V2: # pragma: pydantic-v2
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"""Get the display of the type of the field."""
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return display_as_type(self.annotation)
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def __hash__(self) -> int:
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# Each ModelField is unique for our purposes,
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# to allow store them in a set.
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return id(self)
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def validate_value(self, value: Any) -> Any:
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"""Validate the value pass to the field."""
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return self.type_adapter.validate_python(value)
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def extract_field_info(field_info: BaseFieldInfo) -> dict[str, Any]:
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"""Get FieldInfo init kwargs from a FieldInfo instance."""
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@ -164,15 +186,6 @@ if PYDANTIC_V2: # pragma: pydantic-v2
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kwargs["annotation"] = field_info.rebuild_annotation()
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return kwargs
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def model_field_validate(
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model_field: ModelField, value: Any, config: Optional[ConfigDict] = None
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) -> Any:
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"""Validate the value pass to the field."""
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type: Any = Annotated[model_field.annotation, model_field.field_info]
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return TypeAdapter(
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type, config=None if model_field._annotation_has_config() else config
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).validate_python(value)
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def model_fields(model: type[BaseModel]) -> list[ModelField]:
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"""Get field list of a model."""
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@ -305,6 +318,45 @@ else: # pragma: pydantic-v1
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)
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return cls._construct(name, annotation, field_info or FieldInfo())
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def validate_value(self, value: Any) -> Any:
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"""Validate the value pass to the field."""
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v, errs_ = self.validate(value, {}, loc=())
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if errs_:
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raise ValueError(value, self)
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return v
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class TypeAdapter(Generic[T]):
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@overload
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def __init__(
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self,
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type: type[T],
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*,
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config: Optional[ConfigDict] = ...,
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) -> None: ...
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@overload
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def __init__(
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self,
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type: Any,
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*,
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config: Optional[ConfigDict] = ...,
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) -> None: ...
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def __init__(
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self,
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type: Any,
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*,
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config: Optional[ConfigDict] = None,
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) -> None:
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self.type = type
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self.config = config
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def validate_python(self, value: Any) -> T:
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return type_validate_python(self.type, value)
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def validate_json(self, value: Union[str, bytes]) -> T:
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return type_validate_json(self.type, value)
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def extract_field_info(field_info: BaseFieldInfo) -> dict[str, Any]:
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"""Get FieldInfo init kwargs from a FieldInfo instance."""
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@ -314,22 +366,6 @@ else: # pragma: pydantic-v1
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kwargs.update(field_info.extra)
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return kwargs
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def model_field_validate(
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model_field: ModelField, value: Any, config: Optional[type[ConfigDict]] = None
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) -> Any:
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"""Validate the value pass to the field.
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Set config before validate to ensure validate correctly.
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"""
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if model_field.model_config is not config:
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model_field.set_config(config or ConfigDict)
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v, errs_ = model_field.validate(value, {}, loc=())
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if errs_:
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raise ValueError(value, model_field)
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return v
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def model_fields(model: type[BaseModel]) -> list[ModelField]:
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"""Get field list of a model."""
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@ -9,9 +9,9 @@ from typing import Any, Callable, ForwardRef
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from loguru import logger
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from nonebot.compat import ModelField
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from nonebot.exception import TypeMisMatch
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from nonebot.typing import evaluate_forwardref
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from nonebot.compat import DEFAULT_CONFIG, ModelField, model_field_validate
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def get_typed_signature(call: Callable[..., Any]) -> inspect.Signature:
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@ -51,6 +51,6 @@ def check_field_type(field: ModelField, value: Any) -> Any:
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"""检查字段类型是否匹配"""
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try:
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return model_field_validate(field, value, DEFAULT_CONFIG)
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return field.validate_value(value)
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except ValueError:
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raise TypeMisMatch(field, value)
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@ -1,13 +1,14 @@
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from typing import Any, Optional
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from dataclasses import dataclass
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from typing import Any, Optional, Annotated
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import pytest
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from pydantic import BaseModel
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from pydantic import BaseModel, ValidationError
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from nonebot.compat import (
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DEFAULT_CONFIG,
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Required,
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FieldInfo,
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TypeAdapter,
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PydanticUndefined,
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model_dump,
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custom_validation,
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@ -31,6 +32,21 @@ async def test_field_info():
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assert FieldInfo(test="test").extra["test"] == "test"
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@pytest.mark.asyncio
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async def test_type_adapter():
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t = TypeAdapter(Annotated[int, FieldInfo(ge=1)])
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assert t.validate_python(2) == 2
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with pytest.raises(ValidationError):
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t.validate_python(0)
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assert t.validate_json("2") == 2
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with pytest.raises(ValidationError):
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t.validate_json("0")
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@pytest.mark.asyncio
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async def test_model_dump():
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class TestModel(BaseModel):
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