# nschloe/meshio

:spider_web: input/output for many mesh formats

Repository: https://github.com/nschloe/meshio
Canonical: https://ross.abutalabs.com/products/meshio
Language: Python
License: MIT
License Family: permissive
Topics: vtk, pypi, python, mesh, mathematics, engineering, meshing
Last push: 2024-07-23T14:33:18+00:00

## Health v2 (maintenance only)
Score: 23/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 8, longevity 100
- inputs: {"age_days": 3950, "days_push": 771, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2325, forks 452 (observed 2026-08-28T04:06:37.382723+00:00)

## What it is
meshio is a Python library for reading and writing many unstructured mesh file formats (VTK, Gmsh, Exodus, CGNS, MED, Nastran, and more), smoothly converting between them. It is widely used in finite element analysis and scientific computing workflows.

## Use cases
- convert a Gmsh mesh to VTK format
- read Abaqus .inp mesh files in Python
- export finite element meshes to Exodus format
- load mesh files for FEM simulations
- convert between mesh formats for engineering tools
- read MED/Salome meshes programmatically

## When to choose
- you need to read or write unstructured meshes across many formats in Python
- you want a lightweight, well-maintained mesh conversion tool
- you work with FEM/CAE mesh data and need interoperability

## When to avoid
- you need mesh generation or remeshing, not just I/O
- you need structured/grid mesh handling or visualization itself
- you work outside Python

## Facets
- artifact type: library
- maturity: stable
- function: serialization, file-system
- domain: simulation, files, mathematics
- platform: python, cross-platform
- tags: mesh-io, fem, unstructured-mesh, vtk, file-format-conversion, scientific-computing, engineering

## Member repositories
- nschloe/meshio (main) score 23

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:37.382723+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 2026-08-30T02:38:24.544965+00:00, confidence not recorded.
  - readme: https://github.com/nschloe/meshio (fetched 2026-08-28T04:06:37.382723+00:00, sha 7dab77bddda3)
  - registry_pypi: https://pypi.org/pypi/meshio/json (fetched 2026-08-29T10:18:45.694275+00:00, sha f481c5d22452)
- Data as of 2026-08-30T08:39:29.467469+00:00.