qhull

{
  "aliases": [],
  "alternatives": [
    "CGAL",
    "Boost.Geometry",
    "scipy.spatial"
  ],
  "build_dependencies": [
    "cmake"
  ],
  "categories": [
    "library",
    "math",
    "scientific"
  ],
  "caveats": null,
  "conflicts_with": [],
  "dependencies": [],
  "deprecated": 0,
  "deprecation_reason": null,
  "desc": "Computes convex hulls in n dimensions",
  "disable_reason": null,
  "disabled": 0,
  "enrichment_fetched_at": "2026-06-20T23:41:01+00:00",
  "first_seen": "2026-06-20T23:34:18+00:00",
  "full_name": "qhull",
  "github_default_branch": null,
  "github_last_commit_at": null,
  "github_readme_excerpt": null,
  "github_repo": null,
  "github_stars": null,
  "github_topics": [],
  "homepage": "http://www.qhull.org/",
  "homepage_og_description": null,
  "homepage_og_image": null,
  "homepage_title": "Qhull code for Convex Hull, Delaunay Triangulation, Voronoi Diagram, and Halfspace Intersection about a Point",
  "installs_30d": 4130,
  "installs_365d": 49969,
  "installs_90d": 15658,
  "keg_only": 0,
  "keg_only_reason": null,
  "last_seen": "2026-06-20T23:34:18+00:00",
  "license": "Qhull",
  "llm_generated_at": "2026-06-20T23:46:25+00:00",
  "llm_model": "claude-haiku-4-5",
  "name": "qhull",
  "oldnames": [],
  "one_liner": "Computes convex hulls, Delaunay triangulations, and Voronoi diagrams in n-dimensional space.",
  "optional_dependencies": [],
  "rank_30d": 690,
  "rank_365d": 690,
  "rank_90d": 631,
  "raw_hash": "c1a5caac411e206c",
  "recommended_dependencies": [],
  "revision": 0,
  "ruby_source_path": "Formula/q/qhull.rb",
  "tap": "homebrew/core",
  "test_dependencies": [],
  "uses_from_macos": [],
  "version_head": "HEAD",
  "version_stable": "2020.2",
  "versioned_formulae": [],
  "why_use_this": "Essential computational geometry library for applications needing convex hull or Voronoi diagram algorithms. Used as a build dependency by scientific and graphics software; provides fast, robust implementations of classic algorithms. Available as C library or command-line tools for one-off computations."
}