Module titiler.pgstac.settings

API settings.

Functions

RetrySettings

def RetrySettings(

) -> titiler.pgstac.settings._RetrySettings

This function returns a cached instance of the RetrySettings object.

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_nested_delimiter: '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_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. Behaves as if Config.extra = 'allow' was set since it adds all passed values

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 raise an exception on invalid fields.	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/2.5/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_computed_fields

Get the computed fields of this model instance.

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/2.5/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,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: 'bool' = True
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.5/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 dictionary will only contain JSON serializable types. If mode is 'python', the dictionary may contain any Python objects.	None
include	None	A list of fields to include in the output.	None
exclude	None	A list of fields to exclude from the output.	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 from the output.	None
exclude_none	None	Whether to exclude fields that have a value of None from the output.	None
round_trip	None	Whether to enable serialization and deserialization round-trip support.	None
warnings	None	Whether to log warnings when invalid fields are encountered.	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,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: 'bool' = True
) -> 'str'

Usage docs: docs.pydantic.dev/2.5/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. Can take either a string or set of strings.	None
exclude	None	Field(s) to exclude from the JSON output. Can take either a string or set of strings.	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 have the default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
round_trip	None	Whether to use serialization/deserialization between JSON and class instance.	None
warnings	None	Whether to show any warnings that occurred during serialization.	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.

CacheSettings

class CacheSettings(
    __pydantic_self__,
    _case_sensitive: 'bool | None' = None,
    _env_prefix: 'str | None' = None,
    _env_file: 'DotenvType | None' = PosixPath('.'),
    _env_file_encoding: 'str | None' = None,
    _env_nested_delimiter: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

Cache settings

Ancestors (in MRO)

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

Class variables

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. Behaves as if Config.extra = 'allow' was set since it adds all passed values

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 raise an exception on invalid fields.	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/2.5/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_computed_fields

Get the computed fields of this model instance.

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

check_enable

def check_enable(
    self
)

Check if cache is disabled.

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/2.5/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,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: 'bool' = True
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.5/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 dictionary will only contain JSON serializable types. If mode is 'python', the dictionary may contain any Python objects.	None
include	None	A list of fields to include in the output.	None
exclude	None	A list of fields to exclude from the output.	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 from the output.	None
exclude_none	None	Whether to exclude fields that have a value of None from the output.	None
round_trip	None	Whether to enable serialization and deserialization round-trip support.	None
warnings	None	Whether to log warnings when invalid fields are encountered.	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,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: 'bool' = True
) -> 'str'

Usage docs: docs.pydantic.dev/2.5/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. Can take either a string or set of strings.	None
exclude	None	Field(s) to exclude from the JSON output. Can take either a string or set of strings.	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 have the default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
round_trip	None	Whether to use serialization/deserialization between JSON and class instance.	None
warnings	None	Whether to show any warnings that occurred during serialization.	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_nested_delimiter: 'str | None' = None,
    _secrets_dir: 'str | Path | None' = None,
    **values: 'Any'
)

Postgres-specific API settings.

Attributes

Name	Type	Description	Default
postgres_user	None	postgres username.	None
postgres_pass	None	postgres password.	None
postgres_host	None	database hostname.	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_config

model_fields

Static methods

assemble_db_connection

def assemble_db_connection(
    v: Union[str, NoneType],
    info: pydantic_core.core_schema.ValidationInfo
) -> Any

Validate database config.

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. Behaves as if Config.extra = 'allow' was set since it adds all passed values

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 raise an exception on invalid fields.	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/2.5/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_computed_fields

Get the computed fields of this model instance.

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/2.5/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,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: 'bool' = True
) -> 'dict[str, Any]'

Usage docs: docs.pydantic.dev/2.5/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 dictionary will only contain JSON serializable types. If mode is 'python', the dictionary may contain any Python objects.	None
include	None	A list of fields to include in the output.	None
exclude	None	A list of fields to exclude from the output.	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 from the output.	None
exclude_none	None	Whether to exclude fields that have a value of None from the output.	None
round_trip	None	Whether to enable serialization and deserialization round-trip support.	None
warnings	None	Whether to log warnings when invalid fields are encountered.	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,
    by_alias: 'bool' = False,
    exclude_unset: 'bool' = False,
    exclude_defaults: 'bool' = False,
    exclude_none: 'bool' = False,
    round_trip: 'bool' = False,
    warnings: 'bool' = True
) -> 'str'

Usage docs: docs.pydantic.dev/2.5/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. Can take either a string or set of strings.	None
exclude	None	Field(s) to exclude from the JSON output. Can take either a string or set of strings.	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 have the default value.	None
exclude_none	None	Whether to exclude fields that have a value of None.	None
round_trip	None	Whether to use serialization/deserialization between JSON and class instance.	None
warnings	None	Whether to show any warnings that occurred during serialization.	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.