{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/7"},{"label":"Scientific/Engineering","url":"https://skillfed.io/packages/category/scientific-engineering/3"},{"label":"Utilities","url":"https://skillfed.io/packages/category/utilities/5"},{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/2"},{"label":"Mathematics","url":"https://skillfed.io/packages/category/scientific-engineering-mathematics/2"},{"label":"Physics","url":"https://skillfed.io/packages/category/scientific-engineering-physics"}],"enrichment":{"capability":"coffea provides columnar data analysis tools for high-energy physics (HEP) experiments, enabling efficient manipulation of ROOT file data and event structures using NumPy-like syntax with horizontal scaling support.","skillfed_tags":["hep-physics","distributed-computing","data-analysis"],"use_cases":["Process and analyze ROOT files from particle detector experiments using columnar operations and NumPy-like syntax.","Build scalable physics analysis pipelines that run unchanged on a laptop, multi-core server, or computing cluster.","Apply corrections and transformations to Monte Carlo simulation data to match real experimental measurements.","Manipulate jagged and nested event structures (e.g., variable-length particle lists per event) efficiently.","Prototype analysis logic locally and then scale horizontally to process large datasets without code changes."],"what_it_does":"coffea is a Python framework for columnar analysis of high-energy physics data, designed to make working with ROOT files and complex event structures feel natural to scientists familiar with NumPy and Pandas. It wraps uproot for transparent ROOT file access and awkward-array for handling jagged and nested data structures common in particle physics, allowing analysts to write physics logic in a vectorized, array-oriented style rather than event-by-event loops.\n\nThe package also provides histogramming, plotting, and lookup-table utilities needed for physics analysis workflows, plus built-in support for horizontal scaling across diverse compute resources\u2014from a laptop to multi-core servers, clusters, and supercomputers\u2014without requiring changes to analysis code. This is achieved through integration with modern distributed computing frameworks like Dask and Parsl, making it possible to prototype locally and scale to production without rewriting.","worth_installing":"Yes, if you are doing high-energy physics analysis with ROOT files and want columnar, vectorized workflows with built-in scaling. The package is actively maintained, has no known vulnerabilities, and carries a permissive license. The 25 dependencies are standard for scientific Python and will not be unusual in a physics environment. The Beta status and 'prototype' framing suggest the API may evolve, but active maintenance and recent releases indicate serious ongoing development."},"id":"coffea","links":{"html":"https://skillfed.io/packages/coffea","md":"https://skillfed.io/packages/coffea.md","pypi":"https://pypi.org/project/coffea/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-07-06","license_spdx":null,"license_treatment":"permissive","name":"coffea","python_support":"supports_current","summary":"Basic tools and wrappers for enabling not-too-alien syntax when running columnar Collider HEP analysis."},"popularity":{"monthly_downloads":657901,"position":5474,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"2026.7.0"}