peacock-data-public-datasets-idc-cronscript
/
venv
/lib
/python3.10
/site-packages
/pydantic
/_internal
/_signature.py
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) | |