meshioplusplus
meshio++: I/O for many mesh formats (C++20 core + Python bindings)
Decision gist · record as of 2026-08-14
Yes, if you work with mesh files in scientific computing or engineering. The library supports an extensive range of formats, integrates cleanly with numpy workflows, and offers both programmatic and CLI access. Medium install friction is offset by pre-built wheels and active maintenance. No known vulnerabilities and permissive MIT licensing remove barriers to adoption.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or later.
- Optional dependencies (HDF5, netCDF, Kokkos) unlock format acceleration but are not required for basic I/O.
- Medium install friction due to compiled C++20 bindings, but pre-built wheels cover Python 3.9–3.12 on macOS (arm64, x86_64), Linux (aarch64, x86_64), and Windows (amd64).
License · maintenance · safety
permissive license (permissive) — MIT license (permissive) allows commercial and private use with attribution. No restrictions on modification or redistribution.
last release 2026-08-06 (8 days) · last repo commit 2026-08-06 · 6 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 83,805 downloads/mo, #14,046 on PyPI
Alternatives
Verify before relying
pip install meshioplusplus
import meshioplusplus as mio
mesh = mio.read('input.msh')
mio.write('output.vtk', mesh)- Performance characteristics and memory overhead compared to direct C++ usage or other mesh libraries.
- Completeness of pure-Python fallback implementations for all supported formats.
- Stability and API compatibility guarantees across minor versions.
What it is and what it does
meshioplusplus is a mesh file I/O library that reads and writes unstructured mesh data in dozens of scientific and engineering formats—including STL, VTK, Gmsh, CGNS, Exodus, Nastran, OpenFOAM, and many others. It provides seamless conversion between formats and includes a command-line tool for mesh manipulation (merge, transform, refine, partition, interpolate, slice, and more). The package ships a C++20 core built with pybind11 and scikit-build-core that achieves zero-copy numpy integration at the I/O boundary, with optional HDF5 and netCDF acceleration and a selectable parallel backend (OpenMP, STL+TBB, or sequential by default). Every format also has a pure-Python fallback, so behavior and file compatibility are identical whether or not native libraries are present.
The library is designed for researchers and engineers working with finite element meshes, computational fluid dynamics, and other simulation workflows. It depends on numpy for array handling, rich for terminal output, and importlib_metadata for version introspection. Pre-built wheels are available for modern Python versions (3.9–3.12) across macOS, Linux, and Windows, making installation straightforward for most users.
Use it for
- Convert mesh files between incompatible formats (e.g., Gmsh to VTK) in a simulation pipeline.
- Load mesh data from scientific solvers into Python for post-processing and visualization.
- Merge, refine, or partition large meshes using the command-line interface without writing custom code.
- Transfer field data (temperature, pressure, etc.) across different mesh representations.
- Generate signed distance fields or isosurfaces from mesh geometry for level-set methods.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with mesh files in scientific computing or engineering.
The library supports an extensive range of formats, integrates cleanly with numpy workflows, and offers both programmatic and CLI access. Medium install friction is offset by pre-built wheels and active maintenance. No known vulnerabilities and permissive MIT licensing remove barriers to adoption.
Install
meshioplusplus on PyPI
Before you install
Medium install friction due to compiled C++20 bindings, but pre-built wheels cover Python 3.9–3.12 on macOS (arm64, x86_64), Linux (aarch64, x86_64), and Windows (amd64). Active maintenance with a release 8 days ago.
Requires Python 3.8 or later. Optional dependencies (HDF5, netCDF, Kokkos) unlock format acceleration but are not required for basic I/O.
License in practice
MIT license (permissive) allows commercial and private use with attribution. No restrictions on modification or redistribution.
Quickstart
pip install meshioplusplus
import meshioplusplus as mio
mesh = mio.read('input.msh')
mio.write('output.vtk', mesh)Verify before relying
- Performance characteristics and memory overhead compared to direct C++ usage or other mesh libraries.
- Completeness of pure-Python fallback implementations for all supported formats.
- Stability and API compatibility guarantees across minor versions.
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Medium. Platform-specific wheel |
| Runtime dependencies | 3 packagesimportlib_metadatanumpyrich |
| Maintenance | Actively maintained 8 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 83,805 / month, #14,046 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableIntended Audience :: Science/ResearchLicense :: OSI Approved :: MIT LicenseOperating System :: OS IndependentProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.8Programming Language :: Python :: 3.9Topic :: Scientific/EngineeringTopic :: Utilities |
Evidence: meshioplusplus-10.0.0-cp310-cp310-macosx_13_0_arm64.whl; meshioplusplus-10.0.0-cp310-cp310-macosx_13_0_x86_64.whl; meshioplusplus-10.0.0-cp310-cp310-manylinux_2_34_aarch64.whl; meshioplusplus-10.0.0-cp310-cp310-manylinux_2_34_x86_64.whl; meshioplusplus-10.0.0-cp310-cp310-win_amd64.whl; meshioplusplus-10.0.0-cp311-cp311-macosx_13_0_arm64.whl; meshioplusplus-10.0.0-cp311-cp311-macosx_13_0_x86_64.whl; meshioplusplus-10.0.0-cp311-cp311-manylinux_2_34_aarch64.whl; meshioplusplus-10.0.0-cp311-cp311-manylinux_2_34_x86_64.whl; meshioplusplus-10.0.0-cp311-cp311-win_amd64.whl; meshioplusplus-10.0.0-cp312-cp312-macosx_13_0_arm64.whl; meshioplusplus-10.0.0-cp312-cp312-macosx_13_0_x86_64.whl; meshioplusplus-10.0.0-cp312-cp312-manylinux_2_34_aarch64.whl; meshioplusplus-10.0.0-cp312-cp312-manylinux_2_34_x86_64.whl; meshioplusplus-10.0.0-cp312-cp312-win_amd64.whl; meshioplusplus-10.0.0-cp39-cp39-macosx_13_0_arm64.whl; meshioplusplus-10.0.0-cp39-cp39-macosx_13_0_x86_64.whl; meshioplusplus-10.0.0-cp39-cp39-manylinux_2_34_aarch64.whl; meshioplusplus-10.0.0-cp39-cp39-manylinux_2_34_x86_64.whl; meshioplusplus-10.0.0-cp39-cp39-win_amd64.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “STL VTK Gmsh I/O”
- meshioplusplusmeshioplusplus reads and writes mesh files in dozens of formats (STL,…
- meshioReads and writes mesh files in dozens of formats (STL, VTK, Gmsh,…
- pygmshpygmsh provides a Python interface to Gmsh, a mesh generation tool,…
Give your agent the search over MCP, or paste the wish link into any chat.
More Scientific/Engineering packages
NumPy provides an N-dimensional array object and a comprehensive suite of mathematical, linear algebra, Fourier transform, and random number functions for scientific computing in Python.
pandas provides fast, flexible data structures (Series and DataFrame) for loading, cleaning, transforming, and analyzing labeled or relational data in Python.
scipy provides numerical algorithms for mathematics, science, and engineering—including optimization, integration, linear algebra, Fourier transforms, signal and image processing, and ODE solvers—built on numpy arrays.
scikit-learn provides a comprehensive Python library for supervised and unsupervised machine learning, including classification, regression, clustering, dimensionality reduction, and model evaluation tools built on NumPy and SciPy.
Install it if you need to train, evaluate, or deploy supervised or unsupervised learning models.
dill extends Python's pickle module to serialize and deserialize a much wider range of Python objects, including functions, lambdas, classes, and interpreter sessions, to byte streams for storage or network transmission.
Multiprocess is an enhanced fork of Python's standard multiprocessing library that uses dill for better serialization, allowing you to spawn processes with a threading-like API and share complex objects between them.
Install it if you use multiprocessing and encounter pickle serialization limits with lambdas or complex objects.
See also meshio · numpy-stl · pygmsh · plyfile · gmsh · pysplashsurf · lib3mf · DracoPy · pymeshfix · pypcd4