# shapely/shapely

Manipulation and analysis of geometric objects

Repository: https://github.com/shapely/shapely
Canonical: https://ross.abutalabs.com/products/shapely
Homepage: https://shapely.readthedocs.io/en/stable/
Language: Python
License: BSD-3-Clause
License Family: permissive
Last push: 2026-08-20T08:29:29+00:00

## Health v2 (maintenance only)
Score: 77/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 98, release rhythm 37, longevity 100
- inputs: {"age_days": 5359, "days_push": 13, "days_rel": 343, "gap_med": 62, "n_releases_24m": 4}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 4493, forks 630 (observed 2026-08-28T04:08:51.381207+00:00)

## What it is
Shapely is a BSD-licensed Python library for manipulation and analysis of planar geometric objects, wrapping the GEOS geometry engine. It provides a rich scalar Geometry interface plus high-performance NumPy ufuncs for vectorized operations on arrays of geometries.

## Use cases
- manipulate geometric shapes in python
- compute polygon area and buffer operations
- spatial geometry analysis with numpy arrays
- check if points intersect polygons
- build gis geometry processing pipeline
- perform set operations on geometries like union and intersection

## When to choose
- you need robust 2D geometry operations backed by GEOS
- you want vectorized geometry computations over NumPy arrays
- you need a mature, widely used library that integrates with the geospatial Python ecosystem

## When to avoid
- you need 3D geometry or spherical/geodesic computations
- you need coordinate reference system transformations or file format I/O as the primary task
- you work outside Python

## Facets
- artifact type: library
- maturity: stable
- function: geospatial, math
- domain: data-science
- platform: python, cross-platform
- tags: geometry, geos, numpy-ufuncs, gis, computational-geometry, geospatial

## Member repositories
- shapely/shapely (main) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:51.381207+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T18:20:27.924324+00:00, confidence not recorded.
  - readme: https://github.com/shapely/shapely (fetched 2026-08-28T04:08:51.381207+00:00, sha 4c2f3e8cafb1)
- Data as of 2026-08-30T08:39:29.467469+00:00.