yProv4WFsLite

A simple Python tool to build W3C-PROV provenance graphs from workflow descriptions written in YAML. It uses the prov library to create entities, activities, and their relationships, and can export the results to PROV-JSON and a graph visualization (PNG).

This is useful when having to create large provenance graphs without needing to re-run the entire workflow.

Features

• Define workflows in a simple YAML file
• Each task specifies:
  • inputs (UUIDs representing files or data items)
  • outputs (UUIDs for generated results)
• Automatically constructs a PROV document linking tasks and data
• Export to:
  • prov.json (standard W3C PROV format)
  • PNG graph (requires Graphviz)

Installation

Check out the yProv4ML documentation page to install graphviz.

Then:

git clone https://github.com/HPCI-Lab/yProv4WFsLite.git
cd yProv4WFsLite
pip install -r requirements.txt

Example YAML Workflow

tasks:
  - id: task1
    label: "Load Data"
    attributes: 
      - timestamp: 12345
      - context: "training"
    inputs: []
    outputs:
      - "uuid-1234"

  - id: task2
    label: "Process Data"
    attributes: 
      - timestamp: 456677
    inputs:
      - "uuid-1234"
    outputs:
      - "uuid-5678"

  - id: task3
    label: "Analyze Results"
    inputs:
      - "uuid-5678"
    outputs:
      - "uuid-9999"

To create the corresponding graph:

python run.py test.yaml

📂 Output

• output_prov.json: PROV-JSON representation of the workflow
• output_graph.png: Graph visualization of tasks and data flow