Ask AI


Core Dagster error classes.

All errors thrown by the Dagster framework inherit from DagsterError. Users should not subclass this base class for their own exceptions.

There is another exception base class, DagsterUserCodeExecutionError, which is used by the framework in concert with the user_code_error_boundary().

Dagster uses this construct to wrap user code into which it calls. User code can perform arbitrary computations and may itself throw exceptions. The error boundary catches these user code-generated exceptions, and then reraises them wrapped in a subclass of DagsterUserCodeExecutionError.

The wrapped exceptions include additional context for the original exceptions, injected by the Dagster runtime.

exception dagster.DagsterError[source]

Base class for all errors thrown by the Dagster framework.

Users should not subclass this base class for their own exceptions.

property is_user_code_error

Returns true if this error is attributable to user code.

exception dagster.DagsterConfigMappingFunctionError(*args, **kwargs)[source]

Indicates that an unexpected error occurred while executing the body of a config mapping function defined in a JobDefinition or ~dagster.GraphDefinition during config parsing.

exception dagster.DagsterEventLogInvalidForRun(run_id)[source]

Raised when the event logs for a historical run are malformed or invalid.

exception dagster.DagsterExecutionStepExecutionError(*args, **kwargs)[source]

Indicates an error occurred while executing the body of an execution step.

exception dagster.DagsterExecutionStepNotFoundError(*args, **kwargs)[source]

Thrown when the user specifies execution step keys that do not exist.

exception dagster.DagsterInvalidConfigError(preamble, errors, config_value, *args, **kwargs)[source]

Thrown when provided config is invalid (does not type check against the relevant config schema).

exception dagster.DagsterInvalidConfigDefinitionError(original_root, current_value, stack, reason=None, **kwargs)[source]

Indicates that you have attempted to construct a config with an invalid value.

Acceptable values for config types are any of:
  1. A Python primitive type that resolves to a Dagster config type

    (python:int, python:float, python:bool, python:str, or python:list).

  2. A Dagster config type: Int, Float,

    Bool, String, StringSource, Any, Array, Noneable, Enum, Selector, Shape, or Permissive.

  3. A bare python dictionary, which will be automatically wrapped in

    Shape. Values of the dictionary are resolved recursively according to the same rules.

  4. A bare python list of length one which itself is config type.

    Becomes Array with list element as an argument.

  5. An instance of Field.

exception dagster.DagsterInvalidDefinitionError[source]

Indicates that the rules for a definition have been violated by the user.

exception dagster.DagsterInvalidSubsetError[source]

Indicates that a subset of a pipeline is invalid because either: - One or more ops in the specified subset do not exist on the job.’ - The subset produces an invalid job.

exception dagster.DagsterInvariantViolationError[source]

Indicates the user has violated a well-defined invariant that can only be enforced at runtime.

exception dagster.DagsterResourceFunctionError(*args, **kwargs)[source]

Indicates an error occurred while executing the body of the resource_fn in a ResourceDefinition during resource initialization.

exception dagster.DagsterRunNotFoundError(*args, **kwargs)[source]

Thrown when a run cannot be found in run storage.

exception dagster.DagsterStepOutputNotFoundError(*args, **kwargs)[source]

Indicates that previous step outputs required for an execution step to proceed are not available.

exception dagster.DagsterSubprocessError(*args, **kwargs)[source]

An exception has occurred in one or more of the child processes dagster manages. This error forwards the message and stack trace for all of the collected errors.

exception dagster.DagsterTypeCheckDidNotPass(description=None, metadata=None, dagster_type=None)[source]

Indicates that a type check failed.

This is raised when raise_on_error is True in calls to the synchronous job and graph execution APIs (e.g. graph.execute_in_process(), job.execute_in_process() – typically within a test), and a DagsterType’s type check fails by returning either False or an instance of TypeCheck whose success member is False.

exception dagster.DagsterTypeCheckError(*args, **kwargs)[source]

Indicates an error in the op type system at runtime. E.g. a op receives an unexpected input, or produces an output that does not match the type of the output definition.

exception dagster.DagsterUnknownResourceError(resource_name, *args, **kwargs)[source]

Indicates that an unknown resource was accessed in the body of an execution step. May often happen by accessing a resource in the compute function of an op without first supplying the op with the correct required_resource_keys argument.

exception dagster.DagsterUnmetExecutorRequirementsError[source]

Indicates the resolved executor is incompatible with the state of other systems such as the DagsterInstance or system storage configuration.

exception dagster.DagsterUserCodeExecutionError(*args, **kwargs)[source]

This is the base class for any exception that is meant to wrap an python:Exception thrown by user code. It wraps that existing user code. The original_exc_info argument to the constructor is meant to be a tuple of the type returned by sys.exc_info at the call site of the constructor.

Users should not subclass this base class for their own exceptions and should instead throw freely from user code. User exceptions will be automatically wrapped and rethrown.

property is_user_code_error

Returns true if this error is attributable to user code.