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video/server/.venv/lib/python3.11/site-packages/pydantic_settings/sources/base.py
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2026-10-15 20:36:59 +08:00

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Python

"""Base classes and core functionality for pydantic-settings sources."""
from __future__ import annotations as _annotations
import json
from abc import ABC, abstractmethod
from collections.abc import Callable, Hashable, Mapping, Sequence
from dataclasses import asdict, is_dataclass
from dataclasses import fields as dataclass_fields
from pathlib import Path
from typing import TYPE_CHECKING, Any, cast, get_args, get_type_hints
from pydantic import AliasChoices, AliasPath, TypeAdapter
from pydantic._internal._typing_extra import ( # type: ignore[attr-defined]
get_origin,
)
from pydantic._internal._utils import deep_update, is_model_class
from pydantic.dataclasses import is_pydantic_dataclass
from pydantic.fields import FieldInfo
from typing_inspection.introspection import is_union_origin
from ..exceptions import SettingsError
from .types import (
ConfigFileSourceType,
EnvNoneType,
EnvPrefixTarget,
ForceDecode,
NoDecode,
PydanticModel,
_CliSubCommand,
)
from .utils import (
InitState,
_annotation_is_complex,
_get_alias_names,
_get_field_annotation_and_metadata,
_get_field_metadata,
_get_model_config,
_get_model_fields,
_strip_annotated,
_union_is_complex,
_validate_by_alias_enabled,
_validate_by_name_enabled,
_warn_if_field_info_incomplete,
)
if TYPE_CHECKING:
from pydantic_settings.main import BaseSettings
from .types import Traversable
def get_subcommand(
model: PydanticModel,
is_required: bool = True,
cli_exit_on_error: bool | None = None,
_suppress_errors: list[SettingsError | SystemExit] | None = None,
) -> PydanticModel | None:
"""
Get the subcommand from a model.
Args:
model: The model to get the subcommand from.
is_required: Determines whether a model must have subcommand set and raises error if not
found. Defaults to `True`.
cli_exit_on_error: Determines whether this function exits with error if no subcommand is found.
Defaults to model_config `cli_exit_on_error` value if set. Otherwise, defaults to `True`.
Returns:
The subcommand model if found, otherwise `None`.
Raises:
SystemExit: When no subcommand is found and is_required=`True` and cli_exit_on_error=`True`
(the default).
SettingsError: When no subcommand is found and is_required=`True` and
cli_exit_on_error=`False`.
"""
model_cls = type(model)
if cli_exit_on_error is None and is_model_class(model_cls):
model_default = model_cls.model_config.get('cli_exit_on_error')
if isinstance(model_default, bool):
cli_exit_on_error = model_default
if cli_exit_on_error is None:
cli_exit_on_error = True
subcommands: list[str] = []
for field_name, field_info in _get_model_fields(model_cls).items():
if _CliSubCommand in field_info.metadata:
if getattr(model, field_name) is not None:
return getattr(model, field_name)
subcommands.append(field_name)
# TODO: we could warn if no sub command was found and one of `field_info`s
# isn't complete.
if is_required:
error_message = (
f'Error: CLI subcommand is required {{{", ".join(subcommands)}}}'
if subcommands
else 'Error: CLI subcommand is required but no subcommands were found.'
)
err = SystemExit(error_message) if cli_exit_on_error else SettingsError(error_message)
if _suppress_errors is None:
raise err
_suppress_errors.append(err)
return None
class PydanticBaseSettingsSource(ABC):
"""
Abstract base class for settings sources, every settings source classes should inherit from it.
"""
def __init__(self, settings_cls: type[BaseSettings], _init_state: InitState | None = None):
self._init_state: InitState = {} if _init_state is None else _init_state
self.settings_cls = settings_cls
self.config = settings_cls.model_config
self._current_state: dict[str, Any] = {}
self._settings_sources_data: dict[str, dict[str, Any]] = {}
def _set_current_state(self, state: dict[str, Any]) -> None:
"""
Record the state of settings from the previous settings sources. This should
be called right before __call__.
"""
self._current_state = state
def _set_settings_sources_data(self, states: dict[str, dict[str, Any]]) -> None:
"""
Record the state of settings from all previous settings sources. This should
be called right before __call__.
"""
self._settings_sources_data = states
@property
def current_state(self) -> dict[str, Any]:
"""
The current state of the settings, populated by the previous settings sources.
"""
return self._current_state
@property
def settings_sources_data(self) -> dict[str, dict[str, Any]]:
"""
The state of all previous settings sources.
"""
return self._settings_sources_data
@abstractmethod
def get_field_value(self, field: FieldInfo, field_name: str) -> tuple[Any, str, bool]:
"""
Gets the value, the key for model creation, and a flag to determine whether value is complex.
This is an abstract method that should be overridden in every settings source classes.
Args:
field: The field.
field_name: The field name.
Returns:
A tuple that contains the value, key and a flag to determine whether value is complex.
"""
def field_is_complex(self, field: FieldInfo) -> bool:
"""
Checks whether a field is complex, in which case it will attempt to be parsed as JSON.
Args:
field: The field.
Returns:
Whether the field is complex.
"""
return _annotation_is_complex(field.annotation, field.metadata, self._init_state)
def prepare_field_value(self, field_name: str, field: FieldInfo, value: Any, value_is_complex: bool) -> Any:
"""
Prepares the value of a field.
Args:
field_name: The field name.
field: The field.
value: The value of the field that has to be prepared.
value_is_complex: A flag to determine whether value is complex.
Returns:
The prepared value.
"""
if value is not None and (self.field_is_complex(field) or value_is_complex):
return self.decode_complex_value(field_name, field, value)
return value
def decode_complex_value(self, field_name: str, field: FieldInfo, value: Any) -> Any:
"""
Decode the value for a complex field
Args:
field_name: The field name.
field: The field.
value: The value of the field that has to be prepared.
Returns:
The decoded value for further preparation
"""
metadata = _get_field_metadata(field) if field else []
if field and (
NoDecode in metadata or (self.config.get('enable_decoding') is False and ForceDecode not in metadata)
):
return value
return json.loads(value)
@abstractmethod
def __call__(self) -> dict[str, Any]:
pass
class ConfigFileSourceMixin(ABC):
@staticmethod
def _existing_files(files: ConfigFileSourceType | None) -> list[Path | Traversable]:
"""Return the given files that exist, with `~` expanded in native paths."""
if files is None:
return []
if not isinstance(files, Sequence) or isinstance(files, str):
files = [files]
existing: list[Path | Traversable] = []
for file in files:
file_path: Path | Traversable = Path(file) if isinstance(file, str) else file
if isinstance(file_path, Path):
file_path = file_path.expanduser()
if file_path.is_file():
existing.append(file_path)
return existing
def _read_files(self, files: ConfigFileSourceType | None, deep_merge: bool = False) -> dict[str, Any]:
vars: dict[str, Any] = {}
for file_path in self._existing_files(files):
updating_vars = self._read_file(file_path)
if deep_merge:
vars = deep_update(vars, updating_vars)
else:
vars.update(updating_vars)
return vars
@abstractmethod
def _read_file(self, path: Path | Traversable) -> dict[str, Any]:
pass
def _unwrap_optional_annotation(annotation: Any) -> Any:
"""Return the inner type of an ``Optional[T]`` annotation, otherwise the annotation unchanged."""
if is_union_origin(get_origin(annotation)):
args = get_args(annotation)
if len(args) == 2 and type(None) in args:
for arg in args: # pragma: no branch
if arg is not type(None):
return arg
return annotation
def _is_model_or_dataclass(annotation: Any) -> bool:
"""Whether the annotation is a pydantic model or a pydantic dataclass, i.e. a type with nested fields."""
return is_model_class(annotation) or is_pydantic_dataclass(annotation)
def _get_discriminator(field_info: FieldInfo) -> str | Callable[[Any], Hashable] | None:
"""Get the discriminator of a field using a discriminated union (via Annotated or Field(discriminator=...))."""
from pydantic import Discriminator
discriminator = field_info.discriminator
if discriminator is None:
discriminator = next((m for m in field_info.metadata if isinstance(m, Discriminator)), None)
return discriminator.discriminator if isinstance(discriminator, Discriminator) else discriminator
def _get_member_fields(model_cls: type[Any]) -> dict[str, FieldInfo]:
"""Get the fields of a discriminated union member: a model, a pydantic dataclass or a stdlib dataclass."""
if _is_model_or_dataclass(model_cls):
return _get_model_fields(model_cls)
# Pydantic doesn't attach `__pydantic_fields__` to a stdlib dataclass, so collect the `FieldInfo`s itself:
# `Field()` is kept as the dataclass field's default, or in its `Annotated` metadata.
fields: dict[str, FieldInfo] = {}
hints = get_type_hints(model_cls, include_extras=True)
for dc_field in dataclass_fields(model_cls):
if isinstance(dc_field.default, FieldInfo):
fields[dc_field.name] = dc_field.default
else:
metadata = get_args(hints.get(dc_field.name))[1:]
field_info = next((m for m in metadata if isinstance(m, FieldInfo)), None)
if field_info is not None:
fields[dc_field.name] = field_info
return fields
def _get_discriminator_keys(model_cls: type[Any], discriminator: str) -> tuple[str, ...]:
"""Get the keys that can hold the discriminator value of a discriminated union member: its name and alias."""
alias = getattr(_get_member_fields(model_cls).get(discriminator), 'validation_alias', None)
return (discriminator, alias) if isinstance(alias, str) else (discriminator,)
def _get_nested_discriminators(annotation: Any) -> list[str] | None:
"""Get the discriminators nested inside a discriminated union's annotation.
A member can be guarded by more than one discriminator, e.g. in
``Annotated[Annotated[BlackCat | WhiteCat, Discriminator('color')] | Dog, Discriminator('pet_type')]``
reaching ``BlackCat`` requires both ``pet_type='cat'`` and ``color='black'``. Each one has to keep the
default's value for its default to still apply.
Returns ``None`` if a nested discriminator can't be resolved to a field name (i.e. it is callable), as
the member it selects can't be looked up in the incoming value.
"""
from pydantic import Discriminator
discriminators: list[str] = []
for arg in get_args(annotation):
if arg is type(None):
continue
for metadata in get_args(arg)[1:]:
if isinstance(metadata, Discriminator):
if not isinstance(metadata.discriminator, str):
return None
discriminators.append(metadata.discriminator)
nested = _get_nested_discriminators(arg)
if nested is None:
return None
discriminators.extend(nested)
return discriminators
class DefaultSettingsSource(PydanticBaseSettingsSource):
"""
Source class for loading default object values.
Args:
settings_cls: The Settings class.
nested_model_default_partial_update: Whether to allow partial updates on nested model default object fields.
Defaults to `False`.
"""
def __init__(
self,
settings_cls: type[BaseSettings],
nested_model_default_partial_update: bool | None = None,
_init_state: InitState | None = None,
):
super().__init__(settings_cls, _init_state)
self.defaults: dict[str, Any] = {}
# Discriminated union fields: per discriminator guarding the default's member, the keys that can hold
# its value, and the default's value
self._discriminator_tags: dict[str, list[tuple[tuple[str, ...], Any]]] = {}
self.nested_model_default_partial_update = (
nested_model_default_partial_update
if nested_model_default_partial_update is not None
else self.config.get('nested_model_default_partial_update', False)
)
if self.nested_model_default_partial_update:
validate_by_alias = _validate_by_alias_enabled(self.config)
for field_name, field_info in settings_cls.model_fields.items():
_warn_if_field_info_incomplete(field_info, field_name, self._init_state)
discriminator = _get_discriminator(field_info)
if callable(discriminator):
# The member selected by a callable discriminator can't be looked up in the incoming value
continue
nested = _get_nested_discriminators(field_info.annotation) if discriminator is not None else []
if nested is None:
# Same for a nested callable discriminator
continue
alias_names, *_ = _get_alias_names(field_name, field_info, validate_by_alias=validate_by_alias)
preferred_alias = alias_names[0]
if is_dataclass(type(field_info.default)):
self.defaults[preferred_alias] = asdict(field_info.default)
elif is_model_class(type(field_info.default)):
self.defaults[preferred_alias] = field_info.default.model_dump()
if discriminator is not None and preferred_alias in self.defaults:
default_cls = type(field_info.default)
self._discriminator_tags[preferred_alias] = [
(_get_discriminator_keys(default_cls, name), getattr(field_info.default, name, None))
for name in (discriminator, *nested)
]
def get_field_value(self, field: FieldInfo, field_name: str) -> tuple[Any, str, bool]:
# Nothing to do here. Only implement the return statement to make mypy happy
return None, '', False
def __call__(self) -> dict[str, Any]:
defaults = self.defaults.copy()
for alias, discriminators in self._discriminator_tags.items():
value = self.current_state.get(alias)
if not isinstance(value, dict):
continue
# Pydantic reads each tag from the discriminator field's name or its alias, so a value under any of
# those keys selects a member. A key that is absent leaves the default's member in place.
# The default's fields don't apply when any discriminator selects another member.
if any(value[key] != default_tag for keys, default_tag in discriminators for key in keys if key in value):
del defaults[alias]
return defaults
def __repr__(self) -> str:
return (
f'{self.__class__.__name__}(nested_model_default_partial_update={self.nested_model_default_partial_update})'
)
class InitSettingsSource(PydanticBaseSettingsSource):
"""
Source class for loading values provided during settings class initialization.
"""
def __init__(
self,
settings_cls: type[BaseSettings],
init_kwargs: dict[str, Any],
nested_model_default_partial_update: bool | None = None,
_init_state: InitState | None = None,
):
super().__init__(settings_cls, _init_state)
case_sensitive = self.config.get('case_sensitive', False)
include_name = _validate_by_name_enabled(self.config)
validate_by_alias = _validate_by_alias_enabled(self.config)
def normalize(name: str) -> str:
# When case_sensitive is False, matching is done on lower-cased names.
return name if case_sensitive else name.lower()
self.init_kwargs = {}
init_kwarg_names = set(init_kwargs.keys())
# Map each normalized name to all provided keys sharing it, so field aliases can
# be matched without losing the original key used to look up the value. A 1-to-many
# mapping is required because case_sensitive=False can collapse distinct keys
# (e.g. ``TeSt`` and ``TEST``) onto the same normalized name.
normalized_provided: dict[str, list[str]] = {}
for key in init_kwargs:
normalized_provided.setdefault(normalize(key), []).append(key)
for field_name, field_info in settings_cls.model_fields.items():
_warn_if_field_info_incomplete(field_info, field_name, self._init_state)
# Canonical (case-preserving) alias names determine the output key, so the value
# still matches pydantic's validation aliases, which are always case-sensitive.
canonical_alias_names, *_ = _get_alias_names(field_name, field_info, validate_by_alias=validate_by_alias)
# Match alias names respect case_sensitive when matching against provided keys.
match_alias_names, *_ = _get_alias_names(
field_name, field_info, case_sensitive=case_sensitive, validate_by_alias=validate_by_alias
)
# When populate_by_name is True, allow using the field name as an input key,
# but normalize to the preferred alias to keep keys consistent across sources.
matchable_names = list(match_alias_names)
if include_name:
name = normalize(field_name)
if name not in matchable_names:
matchable_names.append(name)
# All provided keys matching this field, in matchable_names preference order
# (aliases first, then the field name). Only keys not yet consumed by an
# earlier field are considered.
matched_keys = [
original
for name in matchable_names
if name in normalized_provided
for original in normalized_provided[name]
if original in init_kwarg_names
]
if matched_keys:
preferred_alias = canonical_alias_names[0] if canonical_alias_names else field_name
# Prefer the first match in preference order; drop the remaining matches
# so they are not re-added as extras.
init_kwarg_names.difference_update(matched_keys)
self.init_kwargs[preferred_alias] = init_kwargs[matched_keys[0]]
# Include any remaining init kwargs (e.g., extras) unchanged
# Note: If populate_by_name is True and the provided key is the field name, but
# no alias exists, we keep it as-is so it can be processed as extra if allowed.
self.init_kwargs.update({key: val for key, val in init_kwargs.items() if key in init_kwarg_names})
self.nested_model_default_partial_update = (
nested_model_default_partial_update
if nested_model_default_partial_update is not None
else self.config.get('nested_model_default_partial_update', False)
)
def get_field_value(self, field: FieldInfo, field_name: str) -> tuple[Any, str, bool]:
# Nothing to do here. Only implement the return statement to make mypy happy
return None, '', False
def __call__(self) -> dict[str, Any]:
return (
TypeAdapter(dict[str, Any]).dump_python(self.init_kwargs)
if self.nested_model_default_partial_update
else self.init_kwargs
)
def __repr__(self) -> str:
return f'{self.__class__.__name__}(init_kwargs={self.init_kwargs!r})'
class PydanticBaseEnvSettingsSource(PydanticBaseSettingsSource):
def __init__(
self,
settings_cls: type[BaseSettings],
case_sensitive: bool | None = None,
env_prefix: str | None = None,
env_prefix_target: EnvPrefixTarget | None = None,
env_ignore_empty: bool | None = None,
env_parse_none_str: str | None = None,
env_parse_enums: bool | None = None,
_init_state: InitState | None = None,
) -> None:
super().__init__(settings_cls, _init_state)
self.case_sensitive = case_sensitive if case_sensitive is not None else self.config.get('case_sensitive', False)
self.env_prefix = env_prefix if env_prefix is not None else self.config.get('env_prefix', '')
self.env_prefix_target = (
env_prefix_target if env_prefix_target is not None else self.config.get('env_prefix_target', 'variable')
)
self.env_ignore_empty = (
env_ignore_empty if env_ignore_empty is not None else self.config.get('env_ignore_empty', False)
)
self.env_parse_none_str = (
env_parse_none_str if env_parse_none_str is not None else self.config.get('env_parse_none_str')
)
self.env_parse_enums = env_parse_enums if env_parse_enums is not None else self.config.get('env_parse_enums')
def _apply_case_sensitive(self, value: str) -> str:
return value.lower() if not self.case_sensitive else value
def _extract_field_info(
self, field: FieldInfo, field_name: str, model_config: Mapping[str, Any] | None = None
) -> list[tuple[str, str, bool]]:
"""
Extracts field info. This info is used to get the value of field from environment variables.
It returns a list of tuples, each tuple contains:
* field_key: The key of field that has to be used in model creation.
* env_name: The environment variable name of the field.
* value_is_complex: A flag to determine whether the value from environment variable
is complex and has to be parsed.
Args:
field (FieldInfo): The field.
field_name (str): The field name.
model_config (Mapping[str, Any] | None): The config of the model owning the field, which decides
whether its alias and name are accepted. Defaults to the settings config, pass it for a field
of a nested model.
Returns:
list[tuple[str, str, bool]]: List of tuples, each tuple contains field_key, env_name, and value_is_complex.
"""
_warn_if_field_info_incomplete(field, field_name, self._init_state)
field_info: list[tuple[str, str, bool]] = []
v_alias: str | list[str | int] | list[list[str | int]] | None
if model_config is None:
model_config = self.config
if not _validate_by_alias_enabled(model_config):
# pydantic ignores the aliases, so only the field name can populate the field.
v_alias = None
elif isinstance(field.validation_alias, (AliasChoices, AliasPath)):
v_alias = field.validation_alias.convert_to_aliases()
else:
v_alias = field.validation_alias
if v_alias:
env_prefix = self.env_prefix if self.env_prefix_target in ('alias', 'all') else ''
if isinstance(v_alias, list): # AliasChoices, AliasPath
if isinstance(v_alias[0], list): # AliasChoices: one entry per choice
for alias in v_alias:
first_arg = cast(str, alias[0]) # first item of an AliasChoices must be a str
field_info.append(
(
first_arg,
self._apply_case_sensitive(env_prefix + first_arg),
len(alias) > 1,
)
)
else: # bare AliasPath: a single flat path, e.g. ['a', 0, 'b']
# Only the head names the env var to read; the remaining segments are
# navigated in-memory once the value has been JSON-decoded, so they must
# never be looked up as env vars of their own (previously each string
# segment produced its own candidate). Complexity must reflect the number
# of segments in the whole path, not the length of the head's name.
head = cast(str, v_alias[0]) # first item of an AliasPath must be a str
field_info.append((head, self._apply_case_sensitive(env_prefix + head), len(v_alias) > 1))
else: # string validation alias
field_info.append((v_alias, self._apply_case_sensitive(env_prefix + v_alias), False))
if not v_alias or _validate_by_name_enabled(model_config):
annotation, metadata = _get_field_annotation_and_metadata(field)
env_prefix = self.env_prefix if self.env_prefix_target in ('variable', 'all') else ''
if is_union_origin(get_origin(annotation)) and _union_is_complex(annotation, metadata, self._init_state):
field_info.append((field_name, self._apply_case_sensitive(env_prefix + field_name), True))
else:
field_info.append((field_name, self._apply_case_sensitive(env_prefix + field_name), False))
return field_info
def _replace_field_names_case_insensitively(self, field: FieldInfo, field_values: dict[str, Any]) -> dict[str, Any]:
"""
Replace field names in values dict by looking in models fields insensitively.
By having the following models:
```py
class SubSubSub(BaseModel):
VaL3: str
class SubSub(BaseModel):
Val2: str
SUB_sub_SuB: SubSubSub
class Sub(BaseModel):
VAL1: str
SUB_sub: SubSub
class Settings(BaseSettings):
nested: Sub
model_config = SettingsConfigDict(env_nested_delimiter='__')
```
Then:
_replace_field_names_case_insensitively(
field,
{"val1": "v1", "sub_SUB": {"VAL2": "v2", "sub_SUB_sUb": {"vAl3": "v3"}}}
)
Returns {'VAL1': 'v1', 'SUB_sub': {'Val2': 'v2', 'SUB_sub_SuB': {'VaL3': 'v3'}}}
"""
values: dict[str, Any] = {}
for name, value in field_values.items():
sub_model_field: FieldInfo | None = None
annotation = _strip_annotated(_unwrap_optional_annotation(field.annotation))
if not _is_model_or_dataclass(annotation):
values[name] = value
continue
model_fields = _get_model_fields(annotation)
validate_by_alias = _validate_by_alias_enabled(_get_model_config(annotation))
# Find field in sub model by looking in fields case insensitively
field_key: str | None = None
for sub_model_field_name, sub_model_field in model_fields.items():
_warn_if_field_info_incomplete(sub_model_field, sub_model_field_name, self._init_state)
aliases, _ = _get_alias_names(
sub_model_field_name, sub_model_field, validate_by_alias=validate_by_alias
)
_search = (alias for alias in aliases if alias.lower() == name.lower())
if field_key := next(_search, None):
break
if not field_key:
values[name] = value
continue
if (
sub_model_field is not None
and _is_model_or_dataclass(_strip_annotated(_unwrap_optional_annotation(sub_model_field.annotation)))
and isinstance(value, dict)
):
values[field_key] = self._replace_field_names_case_insensitively(sub_model_field, value)
else:
values[field_key] = value
return values
def _replace_env_none_type_values(self, field_value: dict[str, Any]) -> dict[str, Any]:
"""
Recursively parse values that are of "None" type(EnvNoneType) to `None` type(None).
"""
values: dict[str, Any] = {}
for key, value in field_value.items():
if not isinstance(value, EnvNoneType):
values[key] = value if not isinstance(value, dict) else self._replace_env_none_type_values(value)
else:
values[key] = None
return values
def _get_resolved_field_value(self, field: FieldInfo, field_name: str) -> tuple[Any, str, bool]:
"""
Gets the value, the preferred alias key for model creation, and a flag to determine whether value
is complex.
Note:
In V3, this method should either be made public, or, this method should be removed and the
abstract method get_field_value should be updated to include a "use_preferred_alias" flag.
Args:
field: The field.
field_name: The field name.
Returns:
A tuple that contains the value, preferred key and a flag to determine whether value is complex.
"""
field_value, field_key, value_is_complex = self.get_field_value(field, field_name)
if not (value_is_complex or (_validate_by_name_enabled(self.config) and (field_key == field_name))):
field_infos = self._extract_field_info(field, field_name)
preferred_key, _, preferred_is_complex = field_infos[0]
# Only normalize to preferred_key when it's a simple string alias.
# When the preferred key comes from an AliasPath (complex entry), skip normalization
# to avoid using the AliasPath's first element as the key (see #766).
if not preferred_is_complex:
return field_value, preferred_key, value_is_complex
return field_value, field_key, value_is_complex
def __call__(self) -> dict[str, Any]:
data: dict[str, Any] = {}
for field_name, field in self.settings_cls.model_fields.items():
_warn_if_field_info_incomplete(field, field_name, self._init_state)
try:
field_value, field_key, value_is_complex = self._get_resolved_field_value(field, field_name)
except Exception as e:
raise SettingsError(
f'error getting value for field "{field_name}" from source "{self.__class__.__name__}"'
) from e
try:
field_value = self.prepare_field_value(field_name, field, field_value, value_is_complex)
except ValueError as e:
raise SettingsError(
f'error parsing value for field "{field_name}" from source "{self.__class__.__name__}"'
) from e
if field_value is not None:
if self.env_parse_none_str is not None:
if isinstance(field_value, dict):
field_value = self._replace_env_none_type_values(field_value)
elif isinstance(field_value, EnvNoneType):
field_value = None
if (
not self.case_sensitive
# and _lenient_issubclass(field.annotation, BaseModel)
and isinstance(field_value, dict)
):
data[field_key] = self._replace_field_names_case_insensitively(field, field_value)
else:
data[field_key] = field_value
return data
__all__ = [
'ConfigFileSourceMixin',
'DefaultSettingsSource',
'InitSettingsSource',
'PydanticBaseEnvSettingsSource',
'PydanticBaseSettingsSource',
'SettingsError',
]