{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/8"},{"label":"Artificial Intelligence","url":"https://skillfed.io/packages/category/scientific-engineering-artificial-intelligence/6"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Image Recognition","url":"https://skillfed.io/packages/category/scientific-engineering-image-recognition"}],"enrichment":{"capability":"Provides shared utilities and common infrastructure for AutoGluon's automated machine learning framework, supporting tabular, time series, multimodal, and image data tasks.","skillfed_tags":["automl","aws-ai","infrastructure"],"use_cases":["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"],"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.\n\nThis is primarily a dependency package\u2014it 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\u20133.13 across Linux, macOS, and Windows, and carries no known security vulnerabilities.","worth_installing":"Yes\u2014install 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."},"id":"autogluon-common","links":{"html":"https://skillfed.io/packages/autogluon-common","md":"https://skillfed.io/packages/autogluon-common.md","pypi":"https://pypi.org/project/autogluon-common/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-06","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"autogluon.common","python_support":"supports_current","summary":"Fast and Accurate ML in 3 Lines of Code"},"popularity":{"monthly_downloads":372186,"position":7165,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"1.6.1"}