File size: 6,293 Bytes
9f7bac3 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 |
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)
|