pyvista-zstd
VTK zstandard compression library.
Decision gist · record as of 2026-08-14
Yes, if you work with VTK datasets in PyVista and care about I/O performance or file size. The package is actively maintained, has no known vulnerabilities, and integrates seamlessly with PyVista. Install friction is low. The MIT license poses no restrictions. Best suited for workflows where mesh file I/O is a performance concern; less critical for one-off analysis or small datasets.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Low install friction with a pure-Python wheel.
- Active maintenance: released 4 days ago with last commit on 2026-08-10.
- Supports Python 3.10–3.13.
License · maintenance · safety
MIT (permissive) — MIT license is permissive; you can use this in commercial and proprietary projects with minimal restrictions.
last release 2026-08-10 (4 days) · last repo commit 2026-08-10 · 15 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 88,912 downloads/mo, #13,694 on PyPI
Alternatives
Verify before relying
pip install pyvista-zstd
import pyvista_zstd
import pyvista as pv
ds = pv.Sphere()
pyvista_zstd.write(ds, "dataset.pv")
ds_in = pyvista_zstd.read("dataset.pv")- Whether the 37x read speedup and 14x write speedup claims apply to typical real-world datasets or only to the specific benchmark case shown in the description.
- Compatibility with VTK dataset types beyond those explicitly mentioned (triangles, quads, tetrahedra).
- Whether the .pv format is stable across future versions or if there are breaking changes to expect.
What it is and what it does
pyvista-zstd is a compression library that writes VTK datasets to a custom .pv format using Zstandard (zstd) compression instead of VTK's built-in XML writer. It wraps PyVista and zstandard to provide faster I/O with better compression ratios. The library automatically registers with PyVista's reader system, so once installed, pv.read() handles .pv files directly without additional imports.
The main advantage over VTK's XML format is speed and compression efficiency. According to the description, it achieves significantly higher write throughput (up to 1845 MB/s with threading) and better compression ratios (3.02 vs 2.52 for zlib) while using less disk space overall. It supports multi-threaded compression and decompression, and optimizes storage for fixed-width cell topologies by storing the cell width once instead of repeating it for every cell.
Use it for
- Save large VTK meshes to disk quickly when working with scientific simulations or 3D geometry data.
- Reduce storage footprint for archived VTK datasets while maintaining fast read access.
- Parallelize compression of multiple VTK files in batch workflows using the multi-threaded write API.
- Integrate compressed mesh I/O into PyVista-based visualization or analysis pipelines without code changes.
- Replace VTK XML format in existing projects where write speed or compression ratio is a bottleneck.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you work with VTK datasets in PyVista and care about I/O performance or file size.
The package is actively maintained, has no known vulnerabilities, and integrates seamlessly with PyVista. Install friction is low. The MIT license poses no restrictions. Best suited for workflows where mesh file I/O is a performance concern; less critical for one-off analysis or small datasets.
Install
pyvista-zstd on PyPI
Before you install
Low install friction with a pure-Python wheel. Active maintenance: released 4 days ago with last commit on 2026-08-10. Supports Python 3.10–3.13. Three runtime dependencies (pyvista, tqdm, zstandard) are all stable, widely-used libraries.
License in practice
MIT license is permissive; you can use this in commercial and proprietary projects with minimal restrictions.
Quickstart
pip install pyvista-zstd
import pyvista_zstd
import pyvista as pv
ds = pv.Sphere()
pyvista_zstd.write(ds, "dataset.pv")
ds_in = pyvista_zstd.read("dataset.pv")Verify before relying
- Whether the 37x read speedup and 14x write speedup claims apply to typical real-world datasets or only to the specific benchmark case shown in the description.
- Compatibility with VTK dataset types beyond those explicitly mentioned (triangles, quads, tetrahedra).
- Whether the .pv format is stable across future versions or if there are breaking changes to expect.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagespyvistatqdmzstandard |
| Maintenance | Actively maintained 4 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 88,912 / month, #13,694 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersOperating System :: OS IndependentProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13 |
Evidence: pyvista_zstd-0.3.0-py3-none-any.whl
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See also zstd · pyzstd · pyevtk · pyvista · zipfile-zstd · backports.zstd · zstandard · fastar · pyvistaqt · xopen