tencent-wedata-auto-ml 0.2.0

AutoML SDK for Tencent Cloud WeData using FLAML with MLflow integration.

wedata-automl

AutoML SDK for Tencent Cloud WeData, powered by FLAML and integrated with MLflow for experiment tracking and model registry.

Features

• FLAML-based AutoML with graceful fallback to RandomForest
• MLflow integration: experiment tracking, model logging, and Model Registry registration
• Quiet, production-friendly logging helpers
• Simple pipeline API and CLI demo

Installation

pip install wedata-automl
# Optional extras
pip install "wedata-automl[xgboost]"
pip install "wedata-automl[lightgbm]"

Quickstart (Python API)

from wedata_automl import run_pipeline

# Uses a demo dataset by default, and creates/uses the specified MLflow experiment
result = run_pipeline(experiment_name="blueszzhang-test-automl")
print(result)

Quickstart (CLI)

wedata-automl-demo

Notes

• Ensure MLflow Tracking/Registry is configured in your environment (MLFLOW_TRACKING_URI, credentials, etc.)
• XGBoost/LightGBM are optional; install via extras if you want those estimators considered
• Python >= 3.8

License

MIT