PyVista

0.47.3 · active · verified Sat Apr 11

PyVista is a high-level Pythonic interface to the Visualization Toolkit (VTK), simplifying 3D plotting, mesh data structures, and filtering methods for spatial datasets. It is an active project, currently at version 0.47.3, with frequent patch releases and minor versions addressing bugs and introducing new features.

Warnings

breaking The behavior of `Plotter.show()` regarding image depth storage changed in v0.47. It no longer automatically stores the last image depth.
Fix: To obtain image depth after the plotter closes, you must explicitly enable `store_image_depth=True` in the `show()` method (e.g., `plotter.show(store_image_depth=True)`).
breaking Setting new attributes on PyVista classes was restricted starting from v0.46.0.
Fix: In v0.46.0 and v0.46.1, you had to use `pyvista.set_new_attribute(obj, name, value)`. In v0.46.3+, this was relaxed: new *public* attributes still require `set_new_attribute()`, but *private* attributes (prefixed with `_`) can be set directly.
gotcha Performance of `mesh.ray_trace` was significantly slower in versions 0.46.0 to 0.46.3 due to the removal of `obbTree` caching.
Fix: Upgrade to PyVista v0.46.4 or later, which re-enabled the caching mechanism and resolved the performance degradation.
deprecated Accessing arrays in `DataSetAttributes` (e.g., `mesh.point_data` or `mesh.cell_data`) using integer indexing (`obj[index]`) is deprecated.
Fix: Use the `DataSetAttributes.get_array(index)` method instead of the `[]` operator for integer indexing. String-based access (`obj['array_name']`) remains valid.

Install

pip install pyvista Install stable version

Imports

pyvista
```
import pyvista as pv
```
The convention is to import PyVista as `pv` for brevity and consistency.
examples
```
from pyvista import examples
```
Commonly used to access built-in example datasets and functions for quick demonstrations.

Quickstart

This example demonstrates how to download a sample 3D mesh, assign scalar data to its points for coloring, and then visualize it using PyVista's `Plotter` with a specified colormap and camera position.

import pyvista as pv
from pyvista import examples

# Download and load an example mesh (e.g., the Stanford dragon)
mesh = examples.download_dragon()

# Add scalar data based on point coordinates for coloring
mesh['scalars'] = mesh.points[:, 1]

# Create a plotter and add the mesh
plotter = pv.Plotter()
plotter.add_mesh(mesh, cmap='plasma', show_edges=True)

# Set the camera position and display the plot
plotter.show(cpos='xy')

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