--- id: meshio version: "5.3.5" license: The MIT License (MIT) Copyright (c) 2015-2021 Nico Schlömer et al. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files… (full text in the JSON record) license_treatment: permissive maintenance: dormant --- # meshio — I/O for many mesh formats License: permissive · Maintenance: dormant · Downloads: 904.7K/mo ## What it is and what it does meshio is a Python library for reading, writing, and converting between mesh file formats used in scientific computing and engineering. It supports a wide range of formats including STL, VTK, Gmsh, ANSYS, Exodus, CGNS, Nastran, and many others—both binary and ASCII variants. The library provides a unified interface to work with unstructured meshes regardless of their source format, making it easy to integrate mesh data from different simulation tools or to prepare meshes for use in different applications. The package is built on numpy for core data handling and uses rich for command-line output formatting. It offers both a Python API for programmatic mesh manipulation and command-line tools for batch format conversion, compression, and inspection. Time-series mesh data (supported by XDMF format) can be read and written with dedicated reader/writer classes, and the library integrates with ParaView as a plugin for visualization. Use it for: - Convert mesh files between incompatible simulation software (e.g., Gmsh to ANSYS format) for interoperability in multi-tool workflows - Batch process and compress mesh files from the command line without writing custom code - Load mesh geometry and associated data (point/cell fields) into Python for post-processing or analysis - Write custom-generated or modified meshes to standard formats for use in FEM or CFD solvers - Read time-series mesh data from XDMF files for transient simulation analysis ## Worth the install? AI-flagged interpretation of the facts above — verify before relying. Reads and writes mesh files in dozens of formats (STL, VTK, Gmsh, ANSYS, Exodus, and others), converting smoothly between them for scientific and engineering workflows. Yes. meshio is a mature, stable library (Production/Stable, 2320 stars) with low install friction and no known vulnerabilities. Dormant maintenance (last release Jan 2024) is acceptable for a format-conversion tool with a stable API. Install it if you work with mesh files across multiple tools or need programmatic mesh I/O in Python. ## Install pip install meshio uv add meshio poetry add meshio ## Installing meshio Before you install: Low friction install with only three runtime dependencies (numpy, rich, importlib-metadata). Maintenance is dormant—last release was 2024-01-31 and last commit 2024-07-23—but the codebase is stable (Production/Stable classifier) and has accumulated 2320 GitHub stars since its 2015 inception. License in practice: MIT license permits commercial and private use with minimal restrictions; you may use, modify, and distribute the software freely provided you retain the copyright notice and license text. Quickstart: pip install meshio import meshio mesh = meshio.read("input.msh") mesh.write("output.vtk") Verify before relying: - Whether optional dependencies (netcdf4, h5py) are required for specific formats you plan to use - Performance characteristics for large meshes in your target formats ## Package facts - License: The MIT License (MIT) Copyright (c) 2015-2021 Nico Schlömer et al. Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files… (full text in the JSON record) (permissive) - Python support: supports_current - Install friction: low - Maintenance: dormant - Downloads: 904.7K/month (top 5,000 on PyPI) - Known vulnerabilities: none known ## Tags mesh file format conversion, read write mesh files, stl vtk gmsh converter, finite element mesh I/O, unstructured mesh formats, mesh format translator, scientific mesh file handler, mesh-io, format-conversion, scientific-computing [View on SkillFed](https://skillfed.io/packages/meshio) · [View on PyPI](https://pypi.org/project/meshio/)