---
id: autogluon-common
version: "1.6.1"
license: Apache-2.0
license_treatment: permissive
maintenance: active
---

# autogluon.common — Fast and Accurate ML in 3 Lines of Code

License: permissive · Maintenance: active · Downloads: 372.2K/mo

## What it is and what it does

autogluon.common is a shared utility package within the AutoGluon automated machine learning framework, developed by AWS AI. It provides common infrastructure and helper functions used across AutoGluon's various predictors (TabularPredictor, TimeSeriesPredictor, MultiModalPredictor) and other components. The package abstracts away boilerplate and reusable logic so that higher-level AutoGluon modules can focus on their specific tasks without duplicating code.

This is primarily a dependency package—it is installed as part of the AutoGluon ecosystem rather than used standalone. It depends on standard data science libraries (numpy, pandas, scikit-learn) and AWS integration tools (boto3), along with utilities for task scheduling (joblib), progress reporting (tqdm), and configuration management (pyyaml). The package is actively maintained, supports Python 3.10–3.13 across Linux, macOS, and Windows, and carries no known security vulnerabilities.

Use it for:

- As a dependency when installing AutoGluon for tabular, time series, or multimodal machine learning tasks
- Accessing shared data preprocessing or validation utilities if you are extending AutoGluon or building on top of its ecosystem
- Leveraging common configuration and logging infrastructure across multiple AutoGluon-based workflows
- Working with AWS S3 integration for model storage and data loading via boto3 bindings in the common layer

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Provides shared utilities and common infrastructure for AutoGluon's automated machine learning framework, supporting tabular, time series, multimodal, and image data tasks.

Yes—install it as part of AutoGluon if you are using any AutoGluon predictor (tabular, time series, or multimodal). It is a required dependency, actively maintained, has no security issues, and carries a permissive Apache-2.0 license. If you are not using AutoGluon, there is no reason to install this package directly.

## Install

pip install autogluon-common
uv add autogluon-common
poetry add autogluon-common

## Installing autogluon.common

Before you install: Low friction installation with a pure-Python wheel. Active maintenance with a recent release (8 days old) and strong repository signal (10596 stars). Depends on well-established libraries (numpy, pandas, scikit-learn, boto3, joblib) with no exotic or compiled dependencies.

License in practice: Apache-2.0 permissive license allows commercial and private use with minimal restrictions. You may use, modify, and distribute the code provided you retain license notices and include a copy of the license.

Quickstart:

pip install autogluon.common

from autogluon.common import something
# Use shared utilities from AutoGluon ecosystem

Requires Python 3.10–3.13; earlier or later versions are not supported.

Verify before relying:

- What specific utilities and functions autogluon.common exports and what they are used for
- Whether this package is intended for direct use or primarily as an internal dependency for other AutoGluon modules
- Performance characteristics or scalability limits for the shared infrastructure

## Package facts

- License: Apache-2.0 (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 372.2K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

automl common utilities, autogluon shared infrastructure, machine learning automation helpers, ml model training utilities, automated feature engineering, ml pipeline orchestration, data preprocessing for automl, automl, aws-ai, infrastructure

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