{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/17"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/8"}],"enrichment":{"capability":"OpenML-Python provides a Python interface to download and upload datasets, tasks, and machine learning experiment results from the OpenML online platform for collaborative open science research.","skillfed_tags":["benchmark-datasets","open-science","ml-collaboration"],"use_cases":["Download standardized datasets for machine learning experiments without manual file management.","Retrieve pre-defined classification or regression tasks with consistent train-test splits for benchmarking.","Access curated benchmarking suites to run your models against a community-agreed set of problems.","Upload experiment results back to OpenML to contribute to collaborative research and compare performance.","Build reproducible ML pipelines that reference datasets by ID, ensuring consistency across runs and teams."],"what_it_does":"OpenML-Python is a client library that connects your Python environment to OpenML, an online platform for sharing and benchmarking machine learning datasets and experiments. It lets you programmatically fetch datasets, retrieve pre-defined machine learning tasks with standardized train-test splits, and access curated benchmarking suites\u2014all without manually downloading files or managing data locally. The library wraps OpenML's REST API and integrates with pandas, scikit-learn, and numpy, so datasets come back in formats you already work with.\n\nThe package is designed for researchers and practitioners who want to run reproducible ML experiments on shared, versioned datasets, compare results across a community, or build on existing benchmarks. It handles the network communication, data parsing, and format conversion, so you focus on model development rather than data plumbing.","worth_installing":"Yes. The package is actively maintained, has low install friction, carries a permissive BSD license, and solves a real problem for anyone doing collaborative or reproducible ML research. It integrates cleanly with the scientific Python stack (scikit-learn, pandas, numpy) and has no known vulnerabilities. Install it if you work with OpenML datasets or benchmarks; skip it if you manage datasets locally or use a different platform."},"id":"openml","links":{"html":"https://skillfed.io/packages/openml","md":"https://skillfed.io/packages/openml.md","pypi":"https://pypi.org/project/openml/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2025-01-25","license_spdx":null,"license_treatment":"permissive","name":"openml","python_support":"supports_current","summary":"Python API for OpenML"},"popularity":{"monthly_downloads":97049,"position":13176,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.15.1"}