---
id: pyevtk
version: "1.7.0"
license: MIT
license_treatment: permissive
maintenance: active
---

# pyevtk — Export data as binary VTK files

License: permissive · Maintenance: active · Downloads: 240.9K/mo

## What it is and what it does

PyEVTK is a pure Python package for exporting scientific simulation data to binary VTK format, the standard file format for visualization in ParaView, VisIt, Mayavi, and other VTK-compatible tools. It requires only NumPy and provides both low-level interfaces for arbitrary data containers and high-level convenience functions for NumPy arrays, supporting common grid types (image data, rectilinear, structured grids) and point sets.

The package is designed for post-processing workflows where you need to write simulation results to disk in a format that visualization software can read. It handles the binary VTK encoding internally, so you work with NumPy arrays and call export functions rather than managing file formats directly. Since version 0.9 it is pure Python with no external compiled dependencies, making installation straightforward across platforms.

Use it for:

- Export structured grid results from finite-element or finite-difference simulations for visualization in ParaView
- Write point cloud data from particle or meshless simulations to VTK format for post-processing analysis
- Convert NumPy array data to VTK binary files as part of a scientific computing pipeline
- Generate rectilinear grid exports from computational fluid dynamics or geophysical modeling codes
- Batch export simulation snapshots to VTK for time-series visualization in VisIt or Mayavi

## Worth the install?

AI-flagged interpretation of the facts above — verify before relying.

Exports scientific data to binary VTK files for visualization in tools like ParaView, VisIt, and Mayavi, with both low-level and high-level interfaces for NumPy arrays.

Yes. Low install friction, active maintenance, no security vulnerabilities, MIT license, and broad Python version support (3.7–3.14) make this a safe choice. Install it if you need to export scientific data to VTK format for visualization; the NumPy-only dependency keeps it lightweight and portable.

## Install

pip install pyevtk
uv add pyevtk
poetry add pyevtk

## Installing pyevtk

Before you install: Low friction: pure Python package with only NumPy as a runtime dependency, distributed as a wheel. Active maintenance with a recent release (78 days ago) and ongoing commits.

License in practice: MIT license is permissive; you can use this package freely in commercial and private projects with minimal restrictions.

Quickstart:

pip install pyevtk

import numpy as np
from pyevtk.hl import gridToVTK

# Export a simple structured grid
x = np.arange(0, 10, 1, dtype='float64')
y = np.arange(0, 10, 1, dtype='float64')
z = np.arange(0, 10, 1, dtype='float64')
data = np.random.rand(9, 9, 9)
gridToVTK('./output', x, y, z, cellData={'data': data})

Verify before relying:

- Whether the package handles large simulation datasets efficiently as claimed in design guidelines
- Current state of documentation beyond the README and examples directory

## Package facts

- License: MIT (permissive)
- Python support: supports_current
- Install friction: low
- Maintenance: active
- Downloads: 240.9K/month (top 15,000 on PyPI)
- Known vulnerabilities: none known

## Tags

vtk file export, scientific data visualization, paraview export, binary vtk writer, numpy to vtk, evtk export, grid visualization export, scientific-computing, data-export, visualization

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