ewoksserver.app.models.AppSettings#
- class ewoksserver.app.models.AppSettings(**data)[source]#
Bases:
BaseModel
- Parameters:
data (
Any
) –
- classmethod construct(_fields_set=None, **values)#
- copy(*, include=None, exclude=None, update=None, deep=False)#
Returns a copy of the model.
- !!! warning “Deprecated”
This method is now deprecated; use model_copy instead.
If you need include or exclude, use:
`py data = self.model_dump(include=include, exclude=exclude, round_trip=True) data = {**data, **(update or {})} copied = self.model_validate(data) `
- Args:
include: Optional set or mapping specifying which fields to include in the copied model. exclude: Optional set or mapping specifying which fields to exclude in the copied model. update: Optional dictionary of field-value pairs to override field values in the copied model. deep: If True, the values of fields that are Pydantic models will be deep-copied.
- Returns:
A copy of the model with included, excluded and updated fields as specified.
- dict(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False)#
- classmethod from_orm(obj)#
- Parameters:
obj (
Any
) –- Return type:
Self
- json(*, include=None, exclude=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, encoder=PydanticUndefined, models_as_dict=PydanticUndefined, **dumps_kwargs)#
- model_computed_fields: ClassVar[Dict[str, ComputedFieldInfo]] = {}#
A dictionary of computed field names and their corresponding ComputedFieldInfo objects.
- model_config: ClassVar[ConfigDict] = {}#
Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
- classmethod model_construct(_fields_set=None, **values)#
Creates a new instance of the Model class with validated data.
Creates a new model setting __dict__ and __pydantic_fields_set__ from trusted or pre-validated data. Default values are respected, but no other validation is performed.
- !!! note
model_construct() generally respects the model_config.extra setting on the provided model. That is, if model_config.extra == ‘allow’, then all extra passed values are added to the model instance’s __dict__ and __pydantic_extra__ fields. If model_config.extra == ‘ignore’ (the default), then all extra passed values are ignored. Because no validation is performed with a call to model_construct(), having model_config.extra == ‘forbid’ does not result in an error if extra values are passed, but they will be ignored.
- Args:
- _fields_set: A set of field names that were originally explicitly set during instantiation. If provided,
this is directly used for the [model_fields_set][pydantic.BaseModel.model_fields_set] attribute. Otherwise, the field names from the values argument will be used.
values: Trusted or pre-validated data dictionary.
- Returns:
A new instance of the Model class with validated data.
- model_copy(*, update=None, deep=False)#
Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#model_copy
Returns a copy of the model.
- Args:
- update: Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
deep: Set to True to make a deep copy of the model.
- Returns:
New model instance.
- model_dump(*, mode='python', include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)#
Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump
Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.
- Args:
- mode: The mode in which to_python should run.
If mode is ‘json’, the output will only contain JSON serializable types. If mode is ‘python’, the output may contain non-JSON-serializable Python objects.
include: A set of fields to include in the output. exclude: A set of fields to exclude from the output. context: Additional context to pass to the serializer. by_alias: Whether to use the field’s alias in the dictionary key if defined. exclude_unset: Whether to exclude fields that have not been explicitly set. exclude_defaults: Whether to exclude fields that are set to their default value. exclude_none: Whether to exclude fields that have a value of None. round_trip: If True, dumped values should be valid as input for non-idempotent types such as Json[T]. warnings: How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors,
“error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
serialize_as_any: Whether to serialize fields with duck-typing serialization behavior.
- Returns:
A dictionary representation of the model.
- model_dump_json(*, indent=None, include=None, exclude=None, context=None, by_alias=False, exclude_unset=False, exclude_defaults=False, exclude_none=False, round_trip=False, warnings=True, serialize_as_any=False)#
Usage docs: https://docs.pydantic.dev/2.9/concepts/serialization/#modelmodel_dump_json
Generates a JSON representation of the model using Pydantic’s to_json method.
- Args:
indent: Indentation to use in the JSON output. If None is passed, the output will be compact. include: Field(s) to include in the JSON output. exclude: Field(s) to exclude from the JSON output. context: Additional context to pass to the serializer. by_alias: Whether to serialize using field aliases. exclude_unset: Whether to exclude fields that have not been explicitly set. exclude_defaults: Whether to exclude fields that are set to their default value. exclude_none: Whether to exclude fields that have a value of None. round_trip: If True, dumped values should be valid as input for non-idempotent types such as Json[T]. warnings: How to handle serialization errors. False/”none” ignores them, True/”warn” logs errors,
“error” raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
serialize_as_any: Whether to serialize fields with duck-typing serialization behavior.
- Returns:
A JSON string representation of the model.
- property model_extra: dict[str, Any] | None#
Get extra fields set during validation.
- Returns:
A dictionary of extra fields, or None if config.extra is not set to “allow”.
- model_fields: ClassVar[Dict[str, FieldInfo]] = {'no_older_versions': FieldInfo(annotation=bool, required=False, default=False, title='Do not create end points for older API versions')}#
Metadata about the fields defined on the model, mapping of field names to [FieldInfo][pydantic.fields.FieldInfo] objects.
This replaces Model.__fields__ from Pydantic V1.
- property model_fields_set: set[str]#
Returns the set of fields that have been explicitly set on this model instance.
- Returns:
- A set of strings representing the fields that have been set,
i.e. that were not filled from defaults.
- classmethod model_json_schema(by_alias=True, ref_template='#/$defs/{model}', schema_generator=<class 'pydantic.json_schema.GenerateJsonSchema'>, mode='validation')#
Generates a JSON schema for a model class.
- Args:
by_alias: Whether to use attribute aliases or not. ref_template: The reference template. schema_generator: To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
mode: The mode in which to generate the schema.
- Returns:
The JSON schema for the given model class.
- classmethod model_parametrized_name(params)#
Compute the class name for parametrizations of generic classes.
This method can be overridden to achieve a custom naming scheme for generic BaseModels.
- Args:
- params: Tuple of types of the class. Given a generic class
Model with 2 type variables and a concrete model Model[str, int], the value (str, int) would be passed to params.
- Returns:
String representing the new class where params are passed to cls as type variables.
- Raises:
TypeError: Raised when trying to generate concrete names for non-generic models.
- model_post_init(_BaseModel__context)#
Override this method to perform additional initialization after __init__ and model_construct. This is useful if you want to do some validation that requires the entire model to be initialized.
- Parameters:
_BaseModel__context (
Any
) –- Return type:
None
- classmethod model_rebuild(*, force=False, raise_errors=True, _parent_namespace_depth=2, _types_namespace=None)#
Try to rebuild the pydantic-core schema for the model.
This may be necessary when one of the annotations is a ForwardRef which could not be resolved during the initial attempt to build the schema, and automatic rebuilding fails.
- Args:
force: Whether to force the rebuilding of the model schema, defaults to False. raise_errors: Whether to raise errors, defaults to True. _parent_namespace_depth: The depth level of the parent namespace, defaults to 2. _types_namespace: The types namespace, defaults to None.
- Returns:
Returns None if the schema is already “complete” and rebuilding was not required. If rebuilding _was_ required, returns True if rebuilding was successful, otherwise False.
- classmethod model_validate(obj, *, strict=None, from_attributes=None, context=None)#
Validate a pydantic model instance.
- Args:
obj: The object to validate. strict: Whether to enforce types strictly. from_attributes: Whether to extract data from object attributes. context: Additional context to pass to the validator.
- Raises:
ValidationError: If the object could not be validated.
- Returns:
The validated model instance.
- classmethod model_validate_json(json_data, *, strict=None, context=None)#
Usage docs: https://docs.pydantic.dev/2.9/concepts/json/#json-parsing
Validate the given JSON data against the Pydantic model.
- Args:
json_data: The JSON data to validate. strict: Whether to enforce types strictly. context: Extra variables to pass to the validator.
- Returns:
The validated Pydantic model.
- Raises:
ValidationError: If json_data is not a JSON string or the object could not be validated.
- classmethod model_validate_strings(obj, *, strict=None, context=None)#
Validate the given object with string data against the Pydantic model.
- Args:
obj: The object containing string data to validate. strict: Whether to enforce types strictly. context: Extra variables to pass to the validator.
- Returns:
The validated Pydantic model.
-
no_older_versions:
bool
#
- classmethod parse_file(path, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)#
- classmethod parse_obj(obj)#
- Parameters:
obj (
Any
) –- Return type:
Self
- classmethod parse_raw(b, *, content_type=None, encoding='utf8', proto=None, allow_pickle=False)#
- classmethod schema(by_alias=True, ref_template='#/$defs/{model}')#
- Parameters:
by_alias (
bool
) –ref_template (
str
) –
- Return type:
Dict
[str
,Any
]
- classmethod schema_json(*, by_alias=True, ref_template='#/$defs/{model}', **dumps_kwargs)#
- Parameters:
by_alias (
bool
) –ref_template (
str
) –dumps_kwargs (
Any
) –
- Return type:
str
- classmethod update_forward_refs(**localns)#
- Parameters:
localns (
Any
) –- Return type:
None
- classmethod validate(value)#
- Parameters:
value (
Any
) –- Return type:
Self