# pyvista/pyvista

3D visualization and mesh analysis for science and engineering

Repository: https://github.com/pyvista/pyvista
Canonical: https://ross.abutalabs.com/products/pyvista
Homepage: https://docs.pyvista.org
Language: Python
License: MIT
License Family: permissive
Topics: vtk, python, visualization, 3d, meshviewer, scientific-visualization, plotting, mesh, mesh-processing, hacktoberfest, finite-elements, finite-element-analysis
Last push: 2026-08-26T21:10:13+00:00

## Health v2 (maintenance only)
Score: 93/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 99, release rhythm 82, longevity 100
- inputs: {"age_days": 3381, "days_push": 7, "days_rel": 123, "gap_med": 19.5, "n_releases_24m": 15}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 3786, forks 649 (observed 2026-08-28T04:08:18.569757+00:00)

## What it is
PyVista is a Python library providing a NumPy-native interface to VTK for 3D visualization and mesh analysis. It offers dataset structures and filters for points, surfaces, and volumes, plus a unified plotting framework that works in notebooks, scripts, CI, and embedded applications.

## Use cases
- visualize 3d meshes in python
- plot stl files with a few lines of code
- analyze and filter volumetric meshes
- create publication-quality 3d figures for papers
- render 3d data interactively in jupyter notebooks
- process point clouds and surfaces with numpy
- add 3d visualization to a python application
- clip slice and threshold 3d datasets

## When to choose
- you need a simple, Pythonic API over VTK for 3D plotting and mesh analysis
- you want reproducible, image-regression-tested rendering for scientific or engineering workflows
- you need one plotting framework that works in Jupyter, headless CI, and embedded apps
- you want NumPy-native dataset structures for point clouds, surfaces, and volumes

## When to avoid
- you need raw, low-level control over the full VTK pipeline
- you are building high-performance real-time rendering outside Python
- you need 2D-only plotting where matplotlib alone suffices

## Facets
- artifact type: library
- maturity: stable
- function: data-visualization, image-processing, simulation
- domain: data-visualization, graphics, data-science, simulation, developer-tools
- platform: python, cross-platform
- tags: vtk, 3d-visualization, mesh-processing, numpy, scientific-computing, finite-element-analysis, point-clouds, jupyter, plotting, web-server, desktop

## Member repositories
- pyvista/pyvista (main) score 93

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:08:18.569757+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 2026-08-29T18:27:40.758834+00:00, confidence not recorded.
  - readme: https://github.com/pyvista/pyvista (fetched 2026-08-28T04:08:18.569757+00:00, sha bd5bc74a800d)
  - homepage: https://docs.pyvista.org (fetched 2026-08-29T09:22:31.825545+00:00, sha 1f819a9118e7)
  - site_page: https://docs.pyvista.org/getting-started (fetched 2026-08-29T09:22:31.835126+00:00, sha 9c7c7c296e45)
  - site_page: https://docs.pyvista.org/getting-started/why (fetched 2026-08-29T09:22:31.837096+00:00, sha af05b16e909f)
  - site_page: https://docs.pyvista.org/getting-started/authors (fetched 2026-08-29T09:22:31.838883+00:00, sha a32fc8754c2b)
  - site_page: https://docs.pyvista.org/getting-started/installation (fetched 2026-08-29T09:22:31.840766+00:00, sha 5a14f60f75cf)
  - site_page: https://docs.pyvista.org/getting-started/connections (fetched 2026-08-29T09:22:31.842705+00:00, sha f8443fc04826)
  - site_page: https://docs.pyvista.org/getting-started/external_examples (fetched 2026-08-29T09:22:31.844308+00:00, sha dfdc0d288a1f)
  - site_page: https://docs.pyvista.org/user-guide/optional_features (fetched 2026-08-29T09:22:31.846190+00:00, sha b9be92ffd306)
  - site_page: https://docs.pyvista.org/extras/pyinstaller (fetched 2026-08-29T09:22:31.847908+00:00, sha eb8c4be00527)
- Data as of 2026-08-30T08:39:29.467469+00:00.