Utility Components

Semantiva provides two lightweight utility components designed to improve control and observability within pipelines: DataDump and CopyDataProbe. Both operate entirely within normal Semantiva data-flow semantics and can be inserted anywhere in a pipeline without side effects on orchestration or context consistency.

Overview

Utility components are general-purpose processors that:

• Accept BaseDataType as input (universal compatibility)

• Operate on data and context channels independently

• Provide explicit control over data propagation and observation

• Are registered in the core framework (no extension required)

Summary Table

Utility	Type	Input → Output	Effect on Data	Effect on Context	Typical Use
DataDump	DataOperation	BaseDataType → NoDataType	Discards data	Forwards unchanged	Restart data flow; insert new source
CopyDataProbe	DataProbe	BaseDataType → BaseDataType	Forwards data	Identity (no changes)	Save intermediate values, debugging

DataDump — Explicit Data Channel Terminator

class semantiva.data_processors.DataDump(context_observer=None, logger=None)

Bases: DataOperation

classmethod input_data_type()

classmethod output_data_type()

Purpose

DataDump is a universal “data dumper” operation that stops data propagation in the pipeline while preserving the context. It converts any BaseDataType input into NoDataType, effectively signaling that downstream nodes should not expect data from previous stages.

This component is useful when you want to:

• Reset the data stream mid-pipeline before injecting a new DataSource

• Discard intermediary data for performance or privacy reasons

• Isolate context continuity from data continuity

Behavior

Component type	DataOperation
Input data type	BaseDataType (accepts any subclass)
Output data type	NoDataType
Effect	Drops incoming data, forwards context unchanged

Value

• Enables mid-pipeline re-seeding of data (insert sources anywhere)

• Prevents accidental reuse of heavy or sensitive data objects

• Enhances modularity — context can continue while data resets cleanly

CopyDataProbe — Pass-Through Inspection

class semantiva.data_processors.CopyDataProbe(logger=None)

Bases: DataProbe

classmethod input_data_type()

Purpose

CopyDataProbe allows you to inspect data without modifying the data stream. It acts as a transparent “tap” or “mirror”: data flows through unchanged, making it ideal for debugging, logging, or verification points.

Typical uses include:

• Debugging during development (inspect intermediate states)

• Logging or analysis without affecting pipeline behavior

• Verification that data passes through correctly

• Custom probes via subclassing for metrics or monitoring

Behavior

Component type	DataProbe
Input data type	BaseDataType (accepts any subclass)
Output data type	Same as input (identity function)
Effect	Returns input unchanged (preserves object identity)

Value

• Offers a non-intrusive way to observe intermediate values

• Enables verification points without breaking data flow

• Ideal for analysis, visualization, or debugging pipelines

See Also

• Data Operations and Data Probes — Base classes for data processors

• Data Types — Data type system overview

• Introspection & Validation — Type compatibility rules

• Creating Components (Authoring Guide) — Creating custom processors

• Pipelines in Semantiva — Pipeline architecture and data flow