turing/monitoring/__init__.py

"""
Data Drift Monitoring Module

This module provides tools for detecting and logging data drift in production predictions
against reference baselines from training data. It integrates with MLflow for baseline
storage and drift metric logging.

Components:
- drift_detector: Core drift detection using statistical tests (KS test, Chi-square)
- baseline_manager: Extract and manage baseline statistics from training data
- mlflow_logger: Log drift metrics and alerts to MLflow
- synthetic_data_generator: Generate synthetic drifted data for testing
"""

from turing.monitoring.baseline_manager import (
    BaselineManager,
    extract_baseline_statistics,
)
from turing.monitoring.drift_detector import DriftDetector
from turing.monitoring.mlflow_logger import DriftLogger

__all__ = [
    "DriftDetector",
    "BaselineManager",
    "DriftLogger",
    "extract_baseline_statistics",
]