Expand description
Shared error types for Pureflow runtime-facing APIs.
§Fragment: error-taxonomy
The foundation layer uses one shared error enum because downstream crates already need a consistent contract, but the taxonomy is still kept narrow: validation, execution, cancellation, lifecycle observation, and metadata collection. That is enough to remove stringly-typed errors without inventing categories the runtime has not earned yet.
§Fragment: error-code-stability
Error codes are explicit instead of being derived from enum names so logs, tests, and future CLI or API surfaces can depend on stable identifiers even if wording changes. The code surface is intentionally small and can grow only when a new externally meaningful error condition appears.
§Fragment: error-visibility-and-retry
Visibility and retry guidance live next to the error variants because they are part of the policy, not just formatting. A validation failure should be safe to show and not worth retrying, while an execution or lifecycle failure is mostly diagnostic until the runtime grows more concrete recovery rules.
§Fragment: asupersync-error-boundary
asupersync errors are runtime substrate details. The shared Pureflow error
model maps them into cancellation or execution failures at the boundary so
downstream node and workflow APIs do not grow a public dependency on raw
channel or task error types.
Structs§
- Cancellation
Error - Cancellation observed at the runtime boundary.
- Execution
Error - Runtime execution failure from a node.
- Lifecycle
Error - Failure while recording or reacting to a lifecycle event.
- Metadata
Error - Failure while collecting runtime metadata.
Enums§
- Error
Code - Stable machine-readable code for one Pureflow error condition.
- Error
Visibility - Whether an error should be surfaced directly to a human.
- Pureflow
Error - Shared runtime-facing error for the Pureflow foundation layer.
- Retry
Disposition - Retry guidance for one error condition.
- Validation
Error - Validation error exposed through the shared runtime-facing error model.