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workflow_dag(workflow, title="Workflow Dependency Graph")

The workflow_dag function renders a Directed Acyclic Graph (DAG) visualization for a given workflow. This helps you visualize dependencies and relationships within the workflow, making it easier to understand and debug complex processes.

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Parameters

• workflow: A workflow object representing the process or pipeline to be visualized.
• title (str, optional): The title displayed above the visualization. Defaults to "Workflow Dependency Graph".
• size (float): (Optional) The width of the component in a row. Defaults to 1.0 (full row). See the Layout Guide for details.

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Returns

• Plotly Chart: An interactive Plotly chart representing the workflow’s DAG.

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Usage Example

Here’s an example of how to visualize a workflow using workflow_dag:

from preswald import workflow_dag, Workflow

# Create a workflow object
workflow = Workflow()

# Render the workflow DAG
workflow_dag(workflow, title="Example Workflow")

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Key Features

1. Visualize Dependencies: Provides a clear representation of task dependencies in the workflow.
2. Interactive Exploration: Zoom, pan, and hover over nodes to inspect details.
3. Customizable Title: Add meaningful titles to make the visualization more descriptive.

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Example Use Case

Imagine you’re working on a data pipeline with multiple interconnected tasks:

• Use workflow_dag to render a visual map of how tasks depend on one another.
• Quickly identify bottlenecks, cycles, or missing connections in your workflow.

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Why Use workflow_dag?

• Clarity: Converts complex workflows into easy-to-understand visuals.
• Diagnostics: Spot issues or inefficiencies in the workflow structure.
• Professional Presentation: Share high-quality visualizations with stakeholders or team members.

Simplify and visualize your workflows effortlessly with workflow_dag! 🛠️