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di-agent-flow-datastage

Edit existing IBM watsonx.data DataStage batch flows via SDK code.

3|Updated May 1, 2026
Search Tags:#sdk#flow editing#batch pipelines#datastage#watsonx.data#schema propagation
One-click install
npx skills add https://github.com/IBM/ibm-watsonx-data-integration-skills --skill di-agent-flow-datastage
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: di-agent-flow-datastage
Source: https://github.com/IBM/ibm-watsonx-data-integration-skills/tree/main/agent/skills/di-agent-flow-datastage
Command: npx skills add https://github.com/IBM/ibm-watsonx-data-integration-skills --skill di-agent-flow-datastage

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill helps you safely edit existing IBM watsonx.data integration DataStage batch flows without hand-building entire pipelines, reducing the risk and effort of making precise changes to validated production logic.

Core Features & Use Cases

  • In-place flow editing: Retrieve an existing DataStage flow, modify stage properties, and resubmit the complete SDK code back to the platform.
  • Stage and property guidance: Use the skill's references to choose valid stages, inspect accepted property values, and configure schemas correctly.
  • Schema-aware updates: Add or adjust link fields, derived columns, connection bindings, and downstream propagation for batch flows.
  • Safe operational workflow: Make controlled changes with versioning guidance, backup recommendations, and compilation-focused validation.

Quick Start

Tell the assistant to update an existing DataStage batch flow by editing the current SDK code to add the change you need.

Frequently Asked Questions about di-agent-flow-datastage

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I edit an existing DataStage flow without rebuilding the pipeline?▼

To edit a DataStage flow without rebuilding, retrieve the existing SDK code, apply in-place stage property updates or link schema edits, and resubmit the complete modified Python code to watsonx.data for compilation.

How do I update stage properties and link schemas in a watsonx.data batch pipeline?▼

Updating stage properties and link schemas in a watsonx.data batch pipeline requires modifying the existing SDK Python code, adjusting derived columns and connection bindings, and resubmitting the full flow with schema propagation safeguards enabled.

Can I add derived columns to DataStage flows using Python SDK submissions?▼

Yes, you can add derived columns to DataStage flows by editing the existing SDK Python code, configuring the new link fields, and resubmitting the complete batch flow to ensure proper downstream schema propagation.

What is the best way to make structural adjustments to DataStage batch flows safely?▼

The best way to make structural adjustments safely is applying controlled in-place changes to the validated DataStage SDK code, following backup recommendations and versioning guidance before resubmitting for compilation-focused validation.

Does the DataStage flow editing approach work for changes that pyflow cannot express?▼

Yes, this SDK-style Python submission approach specifically handles stage-specific configurations, complex structural adjustments, and schema propagation edits in DataStage batch flows that pyflow cannot express.

Why does my DataStage flow fail compilation after modifying stage properties?▼

DataStage flow compilation can fail after modifying stage properties if the complete flow is not resubmitted properly or if schema propagation safeguards are missing, requiring stage-specific lookup guidance to validate accepted property values.

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