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"""Provides partial support for compatibility with Pydantic v1."""
from __future__ import annotations
import json
from functools import lru_cache
from inspect import signature
from operator import attrgetter
from typing import TYPE_CHECKING, Any, Callable, ClassVar, Literal, overload
import pydantic
from .utils import IS_PYDANTIC_V2, to_json
if TYPE_CHECKING:
from typing import Protocol
class V1Model(Protocol):
# ------------------------------------------------------------------------------
# NOTE: These aren't part of the original v1 BaseModel spec, but were added as
# internal helpers and are (re-)declared here to satisfy mypy checks.
@classmethod
def _dump_json_vals(cls, values: dict, by_alias: bool) -> dict: ...
# ------------------------------------------------------------------------------
# These methods are part of the original v1 BaseModel spec.
__config__: ClassVar[type]
__fields__: ClassVar[dict[str, Any]]
__fields_set__: set[str]
@classmethod
def update_forward_refs(cls, *args: Any, **kwargs: Any) -> None: ...
@classmethod
def construct(cls, *args: Any, **kwargs: Any) -> V1Model: ...
@classmethod
def parse_obj(cls, *args: Any, **kwargs: Any) -> V1Model: ...
@classmethod
def parse_raw(cls, *args: Any, **kwargs: Any) -> V1Model: ...
def dict(self, **kwargs: Any) -> dict[str, Any]: ...
def json(self, **kwargs: Any) -> str: ...
def copy(self, **kwargs: Any) -> V1Model: ...
# Maps {v2 -> v1} model config keys that were renamed in v2.
# See: https://docs.pydantic.dev/latest/migration/#changes-to-config
_V1_CONFIG_KEYS = {
"populate_by_name": "allow_population_by_field_name",
"str_to_lower": "anystr_lower",
"str_strip_whitespace": "anystr_strip_whitespace",
"str_to_upper": "anystr_upper",
"ignored_types": "keep_untouched",
"str_max_length": "max_anystr_length",
"str_min_length": "min_anystr_length",
"from_attributes": "orm_mode",
"json_schema_extra": "schema_extra",
"validate_default": "validate_all",
}
def convert_v2_config(v2_config: dict[str, Any]) -> dict[str, Any]:
"""Internal helper: Return a copy of the v2 ConfigDict with renamed v1 keys."""
return {_V1_CONFIG_KEYS.get(k, k): v for k, v in v2_config.items()}
@lru_cache(maxsize=None) # Reduce repeat introspection via `signature()`
def allowed_arg_names(func: Callable) -> set[str]:
"""Internal helper: Return the names of args accepted by the given function."""
return set(signature(func).parameters)
# Pydantic BaseModels are defined with a custom metaclass, but its namespace
# has changed between pydantic versions.
#
# In v1, it can be imported as `from pydantic.main import ModelMetaclass`
# In v2, it's defined in an internal module so we avoid directly importing it.
PydanticModelMetaclass: type = type(pydantic.BaseModel)
class V1MixinMetaclass(PydanticModelMetaclass):
def __new__(
cls,
name: str,
bases: tuple[type, ...],
namespace: dict[str, Any],
**kwargs: Any,
):
# In the class definition, convert the model config, if any:
# # BEFORE
# class MyModel(BaseModel): # v2 model with `ConfigDict`
# model_config = ConfigDict(populate_by_name=True)
#
# # AFTER
# class MyModel(BaseModel): # v1 model with inner `Config` class
# class Config:
# allow_population_by_field_name = True
if config_dict := namespace.pop("model_config", None):
namespace["Config"] = type("Config", (), convert_v2_config(config_dict))
return super().__new__(cls, name, bases, namespace, **kwargs)
@property
def model_fields(self) -> dict[str, Any]:
return self.__fields__ # type: ignore[deprecated]
# Mixin to ensure compatibility of Pydantic models if Pydantic v1 is detected.
# These are "best effort" implementations and cannot guarantee complete
# compatibility in v1 environments.
#
# Whenever possible, users should strongly prefer upgrading to Pydantic v2 to
# ensure full compatibility.
class V1Mixin(metaclass=V1MixinMetaclass):
# Internal compat helpers
@classmethod
def _dump_json_vals(cls, values: dict[str, Any], by_alias: bool) -> dict[str, Any]:
"""Reserialize values from `Json`-typed fields after dumping the model to dict."""
# Get the expected keys (after `.model_dump()`) for `Json`-typed fields.
# Note: In v1, `Json` fields have `ModelField.parse_json == True`
json_fields = (f for f in cls.__fields__.values() if f.parse_json) # type: ignore[deprecated]
get_key = attrgetter("alias" if by_alias else "name")
json_field_keys = set(map(get_key, json_fields))
return {
# Only serialize `Json` fields with non-null values.
k: to_json(v) if ((v is not None) and (k in json_field_keys)) else v
for k, v in values.items()
}
# ------------------------------------------------------------------------------
@classmethod
def __try_update_forward_refs__(cls: type[V1Model], **localns: Any) -> None:
if hasattr(sup := super(), "__try_update_forward_refs__"):
sup.__try_update_forward_refs__(**localns)
@classmethod
def model_rebuild(cls, *args: Any, **kwargs: Any) -> None:
return cls.update_forward_refs(*args, **kwargs)
@classmethod
def model_construct(cls, *args: Any, **kwargs: Any) -> V1Model:
return cls.construct(*args, **kwargs)
@classmethod
def model_validate(cls, *args: Any, **kwargs: Any) -> V1Model:
return cls.parse_obj(*args, **kwargs)
@classmethod
def model_validate_json(cls, *args: Any, **kwargs: Any) -> V1Model:
return cls.parse_raw(*args, **kwargs)
def model_dump(self: V1Model, **kwargs: Any) -> dict[str, Any]:
# Pass only kwargs that are allowed in the V1 method.
allowed_keys = allowed_arg_names(self.dict) & kwargs.keys()
dict_ = self.dict(**{k: kwargs[k] for k in allowed_keys})
# Ugly hack: Try to serialize `Json` fields correctly when `round_trip=True` in pydantic v1
if kwargs.get("round_trip", False):
by_alias: bool = kwargs.get("by_alias", False)
return self._dump_json_vals(dict_, by_alias=by_alias)
return dict_
def model_dump_json(self: V1Model, **kwargs: Any) -> str:
# Pass only kwargs that are allowed in the V1 method.
allowed_keys = allowed_arg_names(self.json) & kwargs.keys()
json_ = self.json(**{k: kwargs[k] for k in allowed_keys})
# Ugly hack: Try to serialize `Json` fields correctly when `round_trip=True` in pydantic v1
if kwargs.get("round_trip", False):
by_alias: bool = kwargs.get("by_alias", False)
dict_ = json.loads(json_)
return json.dumps(self._dump_json_vals(dict_, by_alias=by_alias))
return json_
def model_copy(self: V1Model, **kwargs: Any) -> V1Model:
# Pass only kwargs that are allowed in the V1 method.
allowed_keys = allowed_arg_names(self.copy) & kwargs.keys()
return self.copy(**{k: kwargs[k] for k in allowed_keys})
@property
def model_fields_set(self: V1Model) -> set[str]:
return self.__fields_set__
# Placeholder. Pydantic v2 is already compatible with itself, so no need for extra mixins.
class V2Mixin:
pass
# Pick the mixin type based on the detected Pydantic version.
PydanticCompatMixin: type = V2Mixin if IS_PYDANTIC_V2 else V1Mixin
# ----------------------------------------------------------------------------
# Decorators and other pydantic helpers
# ----------------------------------------------------------------------------
if IS_PYDANTIC_V2:
field_validator = pydantic.field_validator
model_validator = pydantic.model_validator
AliasChoices = pydantic.AliasChoices
computed_field = pydantic.computed_field
else:
# Redefines `@field_validator` with a v2-like signature
# to call `@validator` from v1 instead.
def field_validator(
field: str,
/,
*fields: str,
mode: Literal["before", "after", "wrap", "plain"] = "after",
check_fields: bool | None = None,
**_: Any,
) -> Callable:
return pydantic.validator( # type: ignore[deprecated]
field,
*fields,
pre=(mode == "before"),
always=True,
check_fields=bool(check_fields),
allow_reuse=True,
)
# Redefines `@model_validator` with a v2-like signature
# to call `@root_validator` from v1 instead.
def model_validator(
*,
mode: Literal["before", "after", "wrap", "plain"],
**_: Any,
) -> Callable:
if mode == "after":
# Patch the behavior for `@model_validator(mode="after")` in v1. This is
# necessarily complicated because:
# - `@model_validator(mode="after")` decorates an instance method in pydantic v2
# - `@root_validator(pre=False)` always decorates a classmethod in pydantic v1
def _decorator(v2_method: Callable) -> Any:
def v1_method(
cls: type[V1Model], values: dict[str, Any]
) -> dict[str, Any]:
# Note: Since this is an "after" validator, the values should already be
# validated, so `.construct()` in v1 (`.model_construct()` in v2)
# should create a valid object to pass to the **original** decorated instance method.
validated = v2_method(cls.construct(**values))
# Pydantic v1 expects the validator to return a dict of {field_name -> value}
return {
name: getattr(validated, name) for name in validated.__fields__
}
return pydantic.root_validator(pre=False, allow_reuse=True)( # type: ignore[call-overload]
classmethod(v1_method)
)
return _decorator
else:
return pydantic.root_validator(pre=(mode == "before"), allow_reuse=True) # type: ignore[call-overload]
@overload # type: ignore[no-redef]
def computed_field(func: Callable | property, /) -> property: ...
@overload
def computed_field(
func: None, /, **_: Any
) -> Callable[[Callable | property], property]: ...
def computed_field(
func: Callable | property | None = None, /, **_: Any
) -> property | Callable[[Callable | property], property]:
"""Compatibility wrapper for Pydantic v2's `computed_field` in v1."""
def always_property(f: Callable | property) -> property:
# Convert the method to a property only if needed
return f if isinstance(f, property) else property(f)
# Handle both decorator styles
return always_property if (func is None) else always_property(func)
class AliasChoices: # type: ignore [no-redef]
"""Placeholder class for Pydantic v2's AliasChoices for partial v1 compatibility."""
aliases: list[str]
def __init__(self, *aliases: str):
self.aliases = list(aliases)
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