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Module tipg.settings

tipg config.

Classes

APISettings

class APISettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

API settings

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_cors_origin

def parse_cors_origin(
    v
)

Parse CORS origins.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

CustomSQLSettings

class CustomSQLSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

TiPg Custom SQL settings.

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

sql_files

return a list of SQL files within the custom sql directory.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

DatabaseSettings

class DatabaseSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

TiPg Database settings.

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

FeaturesSettings

class FeaturesSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

TiPG Items settings

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

max_default

def max_default(
    self
)

Set default bounds and srid when this is a function.

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

MVTSettings

class MVTSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

TiPG MVT settings

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

PostgresSettings

class PostgresSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

Postgres connection settings.

Attributes

Name Type Description Default
postgres_user None postgres username. None
postgres_pass None postgres password. None
postgres_host None hostname for the connection. None
postgres_port None database port. None
postgres_dbname None database name. None

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

assemble_db_connection

def assemble_db_connection(
    v: Union[str, NoneType],
    info: pydantic_core.core_schema.ValidationInfo
) -> typing_extensions.Annotated[pydantic_core._pydantic_core.MultiHostUrl, UrlConstraints(max_length=None, allowed_schemes=['postgres', 'postgresql', 'postgresql+asyncpg', 'postgresql+pg8000', 'postgresql+psycopg', 'postgresql+psycopg2', 'postgresql+psycopg2cffi', 'postgresql+py-postgresql', 'postgresql+pygresql'], host_required=True, default_host=None, default_port=None, default_path=None)]

Validate db url settings.

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

TMSSettings

class TMSSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

TiPG TMS settings

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

TableConfig

class TableConfig(
    /,
    **data: 'Any'
)

Configuration to add table options with env variables.

Ancestors (in MRO)

  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.

TableSettings

class TableSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_ignore_empty: 'bool | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _env_parse_none_str: 'str | None' = None,
    _env_parse_enums: 'bool | None' = None,
    _cli_prog_name: 'str | None' = None,
    _cli_parse_args: 'bool | list[str] | tuple[str, ...] | None' = None,
    _cli_settings_source: 'CliSettingsSource[Any] | None' = None,
    _cli_parse_none_str: 'str | None' = None,
    _cli_hide_none_type: 'bool | None' = None,
    _cli_avoid_json: 'bool | None' = None,
    _cli_enforce_required: 'bool | None' = None,
    _cli_use_class_docs_for_groups: 'bool | None' = None,
    _cli_prefix: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

Table configuration settings

Ancestors (in MRO)

  • pydantic_settings.main.BaseSettings
  • pydantic.main.BaseModel

Class variables

model_computed_fields
model_config
model_fields

Static methods

construct

def construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

from_orm

def from_orm(
    obj: 'Any'
) -> 'Model'

model_construct

def model_construct(
    _fields_set: 'set[str] | None' = None,
    **values: 'Any'
) -> 'Model'

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.

Parameters:

Name Type Description Default
_fields_set None The set of field names accepted for the Model instance. None
values None Trusted or pre-validated data dictionary. None

Returns:

Type Description
None A new instance of the Model class with validated data.

model_json_schema

def model_json_schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    schema_generator: 'type[GenerateJsonSchema]' = <class 'pydantic.json_schema.GenerateJsonSchema'>,
    mode: 'JsonSchemaMode' = 'validation'
) -> 'dict[str, Any]'

Generates a JSON schema for a model class.

Parameters:

Name Type Description Default
by_alias None Whether to use attribute aliases or not. None
ref_template None The reference template. None
schema_generator None To override the logic used to generate the JSON schema, as a subclass of
GenerateJsonSchema with your desired modifications
None
mode None The mode in which to generate the schema. None

Returns:

Type Description
None The JSON schema for the given model class.

model_parametrized_name

def model_parametrized_name(
    params: 'tuple[type[Any], ...]'
) -> 'str'

Compute the class name for parametrizations of generic classes.

This method can be overridden to achieve a custom naming scheme for generic BaseModels.

Parameters:

Name Type Description Default
params None 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.
None

Returns:

Type Description
None String representing the new class where params are passed to cls as type variables.

Raises:

Type Description
TypeError Raised when trying to generate concrete names for non-generic models.

model_rebuild

def model_rebuild(
    *,
    force: 'bool' = False,
    raise_errors: 'bool' = True,
    _parent_namespace_depth: 'int' = 2,
    _types_namespace: 'dict[str, Any] | None' = None
) -> 'bool | 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.

Parameters:

Name Type Description Default
force None Whether to force the rebuilding of the model schema, defaults to False. None
raise_errors None Whether to raise errors, defaults to True. None
_parent_namespace_depth None The depth level of the parent namespace, defaults to 2. None
_types_namespace None The types namespace, defaults to None. None

Returns:

Type Description
None 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.

model_validate

def model_validate(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    from_attributes: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate a pydantic model instance.

Parameters:

Name Type Description Default
obj None The object to validate. None
strict None Whether to enforce types strictly. None
from_attributes None Whether to extract data from object attributes. None
context None Additional context to pass to the validator. None

Returns:

Type Description
None The validated model instance.

Raises:

Type Description
ValidationError If the object could not be validated.

model_validate_json

def model_validate_json(
    json_data: 'str | bytes | bytearray',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/json/#json-parsing

Validate the given JSON data against the Pydantic model.

Parameters:

Name Type Description Default
json_data None The JSON data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

Raises:

Type Description
ValueError If json_data is not a JSON string.

model_validate_strings

def model_validate_strings(
    obj: 'Any',
    *,
    strict: 'bool | None' = None,
    context: 'dict[str, Any] | None' = None
) -> 'Model'

Validate the given object contains string data against the Pydantic model.

Parameters:

Name Type Description Default
obj None The object contains string data to validate. None
strict None Whether to enforce types strictly. None
context None Extra variables to pass to the validator. None

Returns:

Type Description
None The validated Pydantic model.

parse_file

def parse_file(
    path: 'str | Path',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

parse_obj

def parse_obj(
    obj: 'Any'
) -> 'Model'

parse_raw

def parse_raw(
    b: 'str | bytes',
    *,
    content_type: 'str | None' = None,
    encoding: 'str' = 'utf8',
    proto: 'DeprecatedParseProtocol | None' = None,
    allow_pickle: 'bool' = False
) -> 'Model'

schema

def schema(
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}'
) -> 'typing.Dict[str, Any]'

schema_json

def schema_json(
    *,
    by_alias: 'bool' = True,
    ref_template: 'str' = '#/$defs/{model}',
    **dumps_kwargs: 'Any'
) -> 'str'

settings_customise_sources

def settings_customise_sources(
    settings_cls: 'type[BaseSettings]',
    init_settings: 'PydanticBaseSettingsSource',
    env_settings: 'PydanticBaseSettingsSource',
    dotenv_settings: 'PydanticBaseSettingsSource',
    file_secret_settings: 'PydanticBaseSettingsSource'
) -> 'tuple[PydanticBaseSettingsSource, ...]'

Define the sources and their order for loading the settings values.

Parameters:

Name Type Description Default
settings_cls None The Settings class. None
init_settings None The InitSettingsSource instance. None
env_settings None The EnvSettingsSource instance. None
dotenv_settings None The DotEnvSettingsSource instance. None
file_secret_settings None The SecretsSettingsSource instance. None

Returns:

Type Description
None A tuple containing the sources and their order for loading the settings values.

update_forward_refs

def update_forward_refs(
    **localns: 'Any'
) -> 'None'

validate

def validate(
    value: 'Any'
) -> 'Model'

Instance variables

model_extra

Get extra fields set during validation.

model_fields_set

Returns the set of fields that have been explicitly set on this model instance.

Methods

copy

def copy(
    self: 'Model',
    *,
    include: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    exclude: 'AbstractSetIntStr | MappingIntStrAny | None' = None,
    update: 'typing.Dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Returns a copy of the model.

Deprecated

This method is now deprecated; use model_copy instead.

If you need include or exclude, use:

data = self.model_dump(include=include, exclude=exclude, round_trip=True)
data = {**data, **(update or {})}
copied = self.model_validate(data)

Parameters:

Name Type Description Default
include None Optional set or mapping specifying which fields to include in the copied model. None
exclude None Optional set or mapping specifying which fields to exclude in the copied model. None
update None Optional dictionary of field-value pairs to override field values in the copied model. None
deep None If True, the values of fields that are Pydantic models will be deep-copied. None

Returns:

Type Description
None A copy of the model with included, excluded and updated fields as specified.

dict

def dict(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False
) -> 'typing.Dict[str, Any]'

json

def json(
    self,
    *,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    encoder: 'typing.Callable[[Any], Any] | None' = PydanticUndefined,
    models_as_dict: 'bool' = PydanticUndefined,
    **dumps_kwargs: 'Any'
) -> 'str'

model_copy

def model_copy(
    self: 'Model',
    *,
    update: 'dict[str, Any] | None' = None,
    deep: 'bool' = False
) -> 'Model'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#model_copy

Returns a copy of the model.

Parameters:

Name Type Description Default
update None Values to change/add in the new model. Note: the data is not validated
before creating the new model. You should trust this data.
None
deep None Set to True to make a deep copy of the model. None

Returns:

Type Description
None New model instance.

model_dump

def model_dump(
    self,
    *,
    mode: "Literal[('json', 'python')] | str" = 'python',
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump

Generate a dictionary representation of the model, optionally specifying which fields to include or exclude.

Parameters:

Name Type Description Default
mode None 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.
None
include None A set of fields to include in the output. None
exclude None A set of fields to exclude from the output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to use the field's alias in the dictionary key if defined. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A dictionary representation of the model.

model_dump_json

def model_dump_json(
    self,
    *,
    indent: 'int | None' = None,
    include: 'IncEx' = None,
    exclude: 'IncEx' = None,
    context: 'dict[str, Any] | None' = None,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: "bool | Literal[('none', 'warn', 'error')]" = True,
    serialize_as_any: 'bool' = False
) -> 'str'

Usage docs: docs.pydantic.dev/2.7/concepts/serialization/#modelmodel_dump_json

Generates a JSON representation of the model using Pydantic's to_json method.

Parameters:

Name Type Description Default
indent None Indentation to use in the JSON output. If None is passed, the output will be compact. None
include None Field(s) to include in the JSON output. None
exclude None Field(s) to exclude from the JSON output. None
context None Additional context to pass to the serializer. None
by_alias None Whether to serialize using field aliases. None
exclude_unset None Whether to exclude fields that have not been explicitly set. None
exclude_defaults None Whether to exclude fields that are set to their default value. None
exclude_none None Whether to exclude fields that have a value of None. None
round_trip None If True, dumped values should be valid as input for non-idempotent types such as Json[T]. None
warnings None How to handle serialization errors. False/"none" ignores them, True/"warn" logs errors,
"error" raises a [PydanticSerializationError][pydantic_core.PydanticSerializationError].
None
serialize_as_any None Whether to serialize fields with duck-typing serialization behavior. None

Returns:

Type Description
None A JSON string representation of the model.

model_post_init

def model_post_init(
    self,
    _BaseModel__context: 'Any'
) -> 'None'

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.