jacbeekers/dq-made-easy-engine repository overview

⁠Data Quality Rules Engine

Python-based rule translation service for dq-made-easy. It exposes compile-time Great Expectations translation, while Spark execution and run reporting are handled by the dq-engine-gx-worker runtime.

⁠Features

• Rule translation from JSON to Great Expectations expectations
• POST /compile translation endpoint
• GET /health and GET /readiness management endpoints
• FastAPI-based management interface

⁠Quick Start

# Pull image
docker pull jacbeekers/dq-engine:latest

# Run engine
docker run -d \
  -p 8000:8000 \
  -e DQ_LOG_LEVEL=INFO \
  jacbeekers/dq-engine:latest

⁠Environment Variables

⁠Exposed Ports

• 8000 - HTTP management interface

⁠Supported Rule Types

• ✅ Completeness checks (NULL/NOT NULL)
• ✅ Uniqueness checks (duplicate detection)
• ✅ Value range validation
• ✅ Pattern matching (regex)
• ✅ Custom SQL expressions

⁠Tags

• latest - Most recent build
• 0.3.0-xxxxxxx - Semantic version with content hash

⁠Part of Data Quality Made Easy Platform

Complete deployment: GitHub Repository⁠