Module madsci.common.types.base_types

Base types for MADSci.

Variables¶

REDACTED_PLACEHOLDER: Placeholder string used when redacting secret field values.

Functions¶

prefixed_alias_generator(prefix: str) ‑> pydantic.aliases.AliasGenerator

Create an AliasGenerator that adds prefixed serialization aliases.

This enables model_dump(by_alias=True) to produce prefixed keys (e.g., event_server_url) while code still uses unprefixed field names (e.g., server_url).

Note: Only serialization_alias is set here. Setting validation_alias would override pydantic-settings’ env_prefix, causing .env files to lose their per-manager prefixes. Instead, use :func:prefixed_model_validator on the settings class to accept prefixed keys from YAML or keyword arguments.

Args: prefix: The prefix to add (e.g., “event”). Trailing underscores are stripped.

Returns: An AliasGenerator that serializes with the prefixed name.

prefixed_model_validator(prefix: str) ‑> Any

Create a model_validator(mode='before') that accepts prefixed keys.

When a shared settings.yaml uses prefixed keys (e.g., event_server_url), this validator strips the prefix so that the model can validate them against unprefixed field names (server_url).

The validator preserves precedence: if both server_url and event_server_url are present, the unprefixed value wins (since env vars, which have higher priority, are resolved to unprefixed names by pydantic-settings’ env_prefix).

Usage::

  class EventManagerSettings(ManagerSettings, env_prefix="EVENT_", ...):
      model_config = SettingsConfigDict(
          alias_generator=prefixed_alias_generator("event"),
          populate_by_name=True,
      )
      _accept_prefixed_keys = prefixed_model_validator("event")

Args: prefix: The prefix to strip (e.g., “event”). Trailing underscores are stripped; matching is case-insensitive.

Returns: A decorated classmethod suitable for use as a Pydantic model validator.

Classes¶

Error(**data: Any)

A MADSci Error

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)¶

madsci.common.types.base_types.MadsciBaseModel
pydantic.main.BaseModel

Class variables¶

error_type: str | None :

logged_at: datetime.datetime :

message: str | None :

model_config :

Static methods¶

from_exception(exception: Exception) ‑> madsci.common.types.base_types.Error: Create an error from an exception.

MadsciBaseModel(**data: Any)

Parent class for all MADSci data models.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)¶

pydantic.main.BaseModel

Descendants¶

madsci.common.backup_tools.base_backup.BackupInfo
madsci.common.foss_migration.FossMigrationReport
madsci.common.foss_migration.FossMigrationStepResult
madsci.common.testing.types.E2ETestCleanup
madsci.common.testing.types.E2ETestDefinition
madsci.common.testing.types.E2ETestRequirements
madsci.common.testing.types.E2ETestResult
madsci.common.testing.types.E2ETestStep
madsci.common.testing.types.StepResult
madsci.common.testing.types.ValidationConfig
madsci.common.testing.types.ValidationResult
madsci.common.testing.types.WaitConfig
madsci.common.types.action_types.ActionDatapoints
madsci.common.types.action_types.ActionDefinition
madsci.common.types.action_types.ActionFiles
madsci.common.types.action_types.ActionJSON
madsci.common.types.action_types.ActionRequest
madsci.common.types.action_types.ActionResult
madsci.common.types.action_types.ActionResultDefinition
madsci.common.types.action_types.ArgumentDefinition
madsci.common.types.action_types.RestActionRequest
madsci.common.types.admin_command_types.AdminCommandResponse
madsci.common.types.auth_types.OwnershipInfo
madsci.common.types.auth_types.ProjectInfo
madsci.common.types.auth_types.UserInfo
madsci.common.types.base_types.Error
madsci.common.types.condition_types.Condition
madsci.common.types.datapoint_types.DataPoint
madsci.common.types.event_types.EmailAlertsConfig
madsci.common.types.event_types.Event
madsci.common.types.event_types.NodeUtilizationData
madsci.common.types.event_types.SystemUtilizationData
madsci.common.types.experiment_types.Experiment
madsci.common.types.experiment_types.ExperimentDesign
madsci.common.types.experiment_types.ExperimentRegistration
madsci.common.types.experiment_types.ExperimentalCampaign
madsci.common.types.location_types.CapacityCostConfig
madsci.common.types.location_types.CreateLocationFromTemplateRequest
madsci.common.types.location_types.LabLocationConfig
madsci.common.types.location_types.Location
madsci.common.types.location_types.LocationArgument
madsci.common.types.location_types.LocationImportResult
madsci.common.types.location_types.LocationRepresentationTemplate
madsci.common.types.location_types.LocationReservation
madsci.common.types.location_types.LocationTemplate
madsci.common.types.location_types.LocationTransferCapabilities
madsci.common.types.location_types.RepresentationTrainingEntry
madsci.common.types.location_types.TransferGraphDetailedEdge
madsci.common.types.location_types.TransferGraphDetailedResponse
madsci.common.types.location_types.TransferGraphEdge
madsci.common.types.location_types.TransferStepTemplate
madsci.common.types.location_types.TransferTemplateOverrides
madsci.common.types.manager_types.ManagerDefinition
madsci.common.types.manager_types.ManagerHealth
madsci.common.types.migration_types.FileMigration
madsci.common.types.migration_types.MigrationAction
madsci.common.types.migration_types.MigrationPlan
madsci.common.types.node_types.Node
madsci.common.types.node_types.NodeClientCapabilities
madsci.common.types.node_types.NodeDefinition
madsci.common.types.node_types.NodeIntrinsicLocationDefinition
madsci.common.types.node_types.NodeRepresentationTemplateDefinition
madsci.common.types.node_types.NodeReservation
madsci.common.types.node_types.NodeResourceTemplateDefinition
madsci.common.types.node_types.NodeSetConfigResponse
madsci.common.types.node_types.NodeStatus
madsci.common.types.parameter_types.WorkflowParameter
madsci.common.types.registry_types.LocalRegistry
madsci.common.types.registry_types.RegistryEntry
madsci.common.types.registry_types.RegistryLock
madsci.common.types.registry_types.RegistryResolveResult
madsci.common.types.resource_types.custom_types.CustomResourceAttributeDefinition
madsci.common.types.resource_types.custom_types.ResourceTypeDefinition
madsci.common.types.resource_types.definitions.TemplateDefinition
madsci.common.types.resource_types.server_types.ResourceHierarchy
madsci.common.types.resource_types.server_types.ResourceRequestBase
madsci.common.types.step_types.StepDefinition
madsci.common.types.step_types.StepParameters
madsci.common.types.template_types.GeneratedProject
madsci.common.types.template_types.ParameterChoice
madsci.common.types.template_types.TemplateFile
madsci.common.types.template_types.TemplateHook
madsci.common.types.template_types.TemplateInfo
madsci.common.types.template_types.TemplateManifest
madsci.common.types.template_types.TemplateParameter
madsci.common.types.workcell_types.WorkcellInfo
madsci.common.types.workcell_types.WorkcellManagerDefinition
madsci.common.types.workcell_types.WorkcellState
madsci.common.types.workcell_types.WorkcellStatus
madsci.common.types.workflow_types.SchedulerMetadata
madsci.common.types.workflow_types.WorkflowDefinition
madsci.common.types.workflow_types.WorkflowMetadata
madsci.common.types.workflow_types.WorkflowParameters
madsci.common.types.workflow_types.WorkflowStatus

Class variables¶

model_config :

Static methods¶

from_yaml(path: str | pathlib.Path) ‑> ~_T: Allows all derived data models to be loaded from yaml.

Methods¶

model_dump_safe(self, include_secrets: bool = False, **kwargs: Any) ‑> dict[str, typing.Any]

Dump model data with secret fields redacted by default.

This method provides a safe way to export model data without accidentally exposing sensitive values. Secret fields are identified by:

Fields typed as SecretStr / SecretBytes
Fields with json_schema_extra={"secret": True} metadata

Args: include_secrets: If True, include actual secret values. Defaults to False (secrets are replaced with ***REDACTED***). **kwargs: Additional keyword arguments forwarded to model_dump(mode="json", ...).

Returns: dict: Model data with secrets redacted unless include_secrets=True.

model_dump_yaml(self, include_secrets: bool = True) ‑> str

Convert the model to a YAML string.

Args: include_secrets: If False, redact secret field values.

Returns: YAML string representation of the model

to_mongo(self) ‑> dict[str, typing.Any]

Convert the model to a MongoDB-compatible dictionary.

to_yaml(self, path: str | pathlib.Path, include_secrets: bool = True, **kwargs: Any) ‑> None

Export the model to a YAML file.

Args: path: File path to write to. include_secrets: If False, redact secret field values. Defaults to True for backwards compatibility with internal serialization (e.g., definition file round-trips). **kwargs: Additional keyword arguments forwarded to model_dump.

MadsciBaseSettings(**kwargs: Any)

Base class for all MADSci settings.

Initialize settings with walk-up file discovery.

Configuration file paths (YAML, JSON, TOML, .env) are resolved via walk-up discovery from a starting directory. Each filename walks up independently, so node.settings.yaml can resolve in the node dir while settings.yaml resolves in the lab root.

The starting directory is determined by (in priority order):

_settings_dir keyword argument
MADSCI_SETTINGS_DIR environment variable
Current working directory (default)

Args: _settings_dir: Starting directory for walk-up file discovery. **kwargs: Forwarded to BaseSettings.__init__.

Ancestors (in MRO)¶

pydantic_settings.main.BaseSettings
pydantic.main.BaseModel

Descendants¶

madsci.common.foss_migration.FossMigrationSettings
madsci.common.types.backup_types.BaseBackupSettings
madsci.common.types.client_types.MadsciHttpClientConfig
madsci.common.types.client_types.SilaNodeClientConfig
madsci.common.types.context_types.MadsciContext
madsci.common.types.datapoint_types.ObjectStorageSettings
madsci.common.types.docker_types.DockerComposeSettings
madsci.common.types.document_db_migration_types.DocumentDBMigrationSettings
madsci.common.types.interface_types.InterfaceSettings
madsci.common.types.manager_types.ManagerSettings
madsci.common.types.module_types.ModuleSettings
madsci.common.types.node_types.NodeConfig
madsci.experiment_application.experiment_base.ExperimentBaseConfig
madsci.resource_manager.migration_tool.DatabaseMigrationSettings

Class variables¶

model_config: pydantic_settings.main.SettingsConfigDict: Configuration for the settings model.

Static methods¶

settings_customise_sources(settings_cls: type[pydantic_settings.main.BaseSettings], init_settings: pydantic_settings.sources.base.PydanticBaseSettingsSource, env_settings: pydantic_settings.sources.base.PydanticBaseSettingsSource, dotenv_settings: pydantic_settings.sources.base.PydanticBaseSettingsSource, file_secret_settings: pydantic_settings.sources.base.PydanticBaseSettingsSource) ‑> tuple[pydantic_settings.sources.base.PydanticBaseSettingsSource, ...]

Sets the order of settings sources for the settings model.

File paths are resolved with walk-up discovery from the settings directory (defaulting to CWD). Each filename walks up independently, so shared configs in parent directories are found automatically.

Methods¶

model_dump_safe(self, include_secrets: bool = False, **kwargs: Any) ‑> dict[str, typing.Any]

Dump settings data with secret fields redacted by default.

Secret fields are identified by json_schema_extra={"secret": True} or SecretStr / SecretBytes type annotations. Nested models are recursively redacted.

Args: include_secrets: If True, include actual secret values. **kwargs: Additional keyword arguments forwarded to model_dump.

Returns: dict: Settings with secrets redacted unless include_secrets=True.

MadsciDeveloperSettings(**values: Any)

Developer-focused settings for MADSci behavior.

These settings control development experience features like rich tracebacks. All settings use the MADSCI_ prefix for environment variables.

Environment Variables: MADSCI_DISABLE_RICH_TRACEBACKS: Set to true to disable rich tracebacks (default: false, rich tracebacks are enabled) MADSCI_RICH_TRACEBACKS_SHOW_LOCALS: Set to true to show local variables in tracebacks (default: false for security - can leak secrets)

Note: show_locals is disabled by default to prevent accidental exposure of sensitive data (tokens, passwords) that may be present in local variables during exceptions.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)¶

pydantic_settings.main.BaseSettings
pydantic.main.BaseModel

Class variables¶

disable_rich_tracebacks: bool :

model_config: ClassVar[pydantic_settings.main.SettingsConfigDict] :

rich_tracebacks_show_locals: bool :

MadsciSQLModel(**data: Any)

Parent class for all MADSci data models that are SQLModel-based.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Ancestors (in MRO)¶

sqlmodel.main.SQLModel
pydantic.main.BaseModel

Descendants¶

madsci.common.types.resource_types.definitions.CustomResourceAttributeDefinition
madsci.common.types.resource_types.definitions.ResourceDefinition
madsci.resource_manager.resource_tables.SchemaVersionTable

Class variables¶

model_config: Configuration for the SQLModel model.

Static methods¶

from_yaml(path: str | pathlib.Path) ‑> ~_T: Allows all derived data models to be loaded from yaml.

Methods¶

to_yaml(self, path: str | pathlib.Path, **kwargs: Any) ‑> None

Allows all derived data models to be exported into yaml.

kwargs are passed to model_dump