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from __future__ import annotations import dataclasses from inspect import Parameter, Signature, signature from typing import TYPE_CHECKING, Any, Callable from pydantic_core import PydanticUndefined from ._config import ConfigWrapper from ._utils import is_valid_identifier if TYPE_CHECKING: from ..fields import FieldInfo def _field_name_for_signature(field_name: str, field_info: FieldInfo) -> str: """Extract the correct name to use for the field when generating a signature. Assuming the field has a valid alias, this will return the alias. Otherwise, it will return the field name. First priority is given to the validation_alias, then the alias, then the field name. Args: field_name: The name of the field field_info: The corresponding FieldInfo object. Returns: The correct name to use when generating a signature. """ def _alias_if_valid(x: Any) -> str | None: """Return the alias if it is a valid alias and identifier, else None.""" return x if isinstance(x, str) and is_valid_identifier(x) else None return _alias_if_valid(field_info.alias) or _alias_if_valid(field_info.validation_alias) or field_name def _process_param_defaults(param: Parameter) -> Parameter: """Modify the signature for a parameter in a dataclass where the default value is a FieldInfo instance. Args: param (Parameter): The parameter Returns: Parameter: The custom processed parameter """ from ..fields import FieldInfo param_default = param.default if isinstance(param_default, FieldInfo): annotation = param.annotation # Replace the annotation if appropriate # inspect does "clever" things to show annotations as strings because we have # `from __future__ import annotations` in main, we don't want that if annotation == 'Any': annotation = Any # Replace the field default default = param_default.default if default is PydanticUndefined: if param_default.default_factory is PydanticUndefined: default = Signature.empty else: # this is used by dataclasses to indicate a factory exists: default = dataclasses._HAS_DEFAULT_FACTORY # type: ignore return param.replace( annotation=annotation, name=_field_name_for_signature(param.name, param_default), default=default ) return param def _generate_signature_parameters( # noqa: C901 (ignore complexity, could use a refactor) init: Callable[..., None], fields: dict[str, FieldInfo], config_wrapper: ConfigWrapper, ) -> dict[str, Parameter]: """Generate a mapping of parameter names to Parameter objects for a pydantic BaseModel or dataclass.""" from itertools import islice present_params = signature(init).parameters.values() merged_params: dict[str, Parameter] = {} var_kw = None use_var_kw = False for param in islice(present_params, 1, None): # skip self arg # inspect does "clever" things to show annotations as strings because we have # `from __future__ import annotations` in main, we don't want that if fields.get(param.name): # exclude params with init=False if getattr(fields[param.name], 'init', True) is False: continue param = param.replace(name=_field_name_for_signature(param.name, fields[param.name])) if param.annotation == 'Any': param = param.replace(annotation=Any) if param.kind is param.VAR_KEYWORD: var_kw = param continue merged_params[param.name] = param if var_kw: # if custom init has no var_kw, fields which are not declared in it cannot be passed through allow_names = config_wrapper.populate_by_name for field_name, field in fields.items(): # when alias is a str it should be used for signature generation param_name = _field_name_for_signature(field_name, field) if field_name in merged_params or param_name in merged_params: continue if not is_valid_identifier(param_name): if allow_names: param_name = field_name else: use_var_kw = True continue kwargs = {} if field.is_required() else {'default': field.get_default(call_default_factory=False)} merged_params[param_name] = Parameter( param_name, Parameter.KEYWORD_ONLY, annotation=field.rebuild_annotation(), **kwargs ) if config_wrapper.extra == 'allow': use_var_kw = True if var_kw and use_var_kw: # Make sure the parameter for extra kwargs # does not have the same name as a field default_model_signature = [ ('self', Parameter.POSITIONAL_ONLY), ('data', Parameter.VAR_KEYWORD), ] if [(p.name, p.kind) for p in present_params] == default_model_signature: # if this is the standard model signature, use extra_data as the extra args name var_kw_name = 'extra_data' else: # else start from var_kw var_kw_name = var_kw.name # generate a name that's definitely unique while var_kw_name in fields: var_kw_name += '_' merged_params[var_kw_name] = var_kw.replace(name=var_kw_name) return merged_params def generate_pydantic_signature( init: Callable[..., None], fields: dict[str, FieldInfo], config_wrapper: ConfigWrapper, is_dataclass: bool = False ) -> Signature: """Generate signature for a pydantic BaseModel or dataclass. Args: init: The class init. fields: The model fields. config_wrapper: The config wrapper instance. is_dataclass: Whether the model is a dataclass. Returns: The dataclass/BaseModel subclass signature. """ merged_params = _generate_signature_parameters(init, fields, config_wrapper) if is_dataclass: merged_params = {k: _process_param_defaults(v) for k, v in merged_params.items()} return Signature(parameters=list(merged_params.values()), return_annotation=None)