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DataEngineX - Core framework for AI/ML/Data engineering projects

Project description

dataenginex

Unified Data + ML + AI framework. Config-driven, self-hosted, production-ready.

Install

# Core (DuckDB, FastAPI, structlog, Pydantic, Click, Rich)
pip install dataenginex

# With optional extras
pip install dataenginex[dagster]      # Dagster orchestration
pip install dataenginex[mlflow]       # MLflow experiment tracking
pip install dataenginex[agents]       # LangGraph agent runtime
pip install dataenginex[vectors]      # Qdrant + LanceDB vector stores
pip install dataenginex[embeddings]   # sentence-transformers + ONNX
pip install dataenginex[spark]        # PySpark transforms
pip install dataenginex[cloud]        # S3 + GCS storage backends
pip install dataenginex[all]          # Everything

Submodules

Module Requires Extra Description
dataenginex.config dex.yaml schema, loader, env var resolution, layering
dataenginex.core Exceptions, interfaces (10 Base* ABCs), backend registry
dataenginex.cli dex CLI (validate, version, init, serve)
dataenginex.api FastAPI app, auth (JWT), health, rate limiting
dataenginex.data Connectors, schema registry, profiler
dataenginex.ml Training, model registry, serving, drift detection
dataenginex.middleware Structured logging, Prometheus metrics, tracing
dataenginex.lakehouse optional [cloud] Storage backends (local, S3, GCS), catalog
dataenginex.warehouse SQL/Spark transforms, lineage
dataenginex.plugins Plugin system (entry-point discovery)

Quick Usage

# Config system
from dataenginex.config import load_config
cfg = load_config(Path("dex.yaml"))

# Core interfaces + registry
from dataenginex.core.interfaces import BaseConnector
from dataenginex.core.registry import BackendRegistry

# Exceptions
from dataenginex.core.exceptions import DataEngineXError, BackendNotInstalledError

# ML
from dataenginex.ml import ModelRegistry

# CLI
# dex validate dex.yaml
# dex version

Source and Docs

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