docs/v3/api-ref/python/prefect-settings-models-root.mdx
prefect.settings.models.rootcanonical_environment_prefix <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L402" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>canonical_environment_prefix(settings: 'Settings') -> str
Settings <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L49" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>Settings for Prefect using Pydantic settings.
See https://docs.pydantic.dev/latest/concepts/pydantic_settings
Methods:
connected_to_cloud <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L268" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>connected_to_cloud(self) -> bool
True when the API URL points at the configured Prefect Cloud API.
copy_with_update <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L279" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>copy_with_update(self: Self, updates: Optional[Mapping['Setting', Any]] = None, set_defaults: Optional[Mapping['Setting', Any]] = None, restore_defaults: Optional[Iterable['Setting']] = None) -> Self
Create a new Settings object with validation.
Args:
updates: A mapping of settings to new values. Existing values for the
given settings will be overridden.set_defaults: A mapping of settings to new default values. Existing values for
the given settings will only be overridden if they were not set.restore_defaults: An iterable of settings to restore to their default values.Returns:
emit_warnings <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L261" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>emit_warnings(self) -> Self
More post-hoc validation of settings, including warnings for misconfigurations.
hash_key <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L350" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>hash_key(self) -> str
Return a hash key for the settings object. This is needed since some settings may be unhashable, like lists.
post_hoc_settings <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/models/root.py#L199" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>post_hoc_settings(self) -> Self
Handle remaining complex default assignments that aren't yet migrated to dependent settings.
With Pydantic 2.10's dependent settings feature, we've migrated simple path-based defaults to use default_factory. The remaining items here require access to the full Settings instance or have complex interdependencies that will be migrated in future PRs.
settings_customise_sources <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/base.py#L33" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>settings_customise_sources(cls, settings_cls: type[BaseSettings], init_settings: PydanticBaseSettingsSource, env_settings: PydanticBaseSettingsSource, dotenv_settings: PydanticBaseSettingsSource, file_secret_settings: PydanticBaseSettingsSource) -> tuple[PydanticBaseSettingsSource, ...]
Define an order for Prefect settings sources.
The order of the returned callables decides the priority of inputs; first item is the highest priority.
See https://docs.pydantic.dev/latest/concepts/pydantic_settings/#customise-settings-sources
to_environment_variables <sup><a href="https://github.com/PrefectHQ/prefect/blob/main/src/prefect/settings/base.py#L124" target="_blank"><Icon icon="github" style="width: 14px; height: 14px;" /></a></sup>to_environment_variables(self, exclude_unset: bool = False, include_secrets: bool = True, include_aliases: bool = False) -> dict[str, str]
Convert the settings object to a dictionary of environment variables.