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Easier Pythonic interface to VTK

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PyVista is a helper module for the Visualization Toolkit (VTK) that takes a different approach on interfacing with VTK through NumPy and direct array access. This package provides a Pythonic, well-documented interface exposing VTK’s powerful visualization backend to facilitate rapid prototyping, analysis, and visual integration of spatially referenced datasets.

This module can be used for scientific plotting for presentations and research papers as well as a supporting module for other mesh dependent Python modules.


Refer to the documentation for detailed installation and usage details.

For general questions about the project, its applications, or about software usage, please do not create an issue but join us on Slack or send one of the developers an email. The project support team can be reached at


PyVista can be installed from PyPI using pip on Python >= 3.5:

pip install pyvista

You can also visit PyPi, Anaconda, or GitHub to download the source.

See the Installation for more details if the installation through pip doesn’t work out.


Head over to the Quick Examples page in the docs to learn more about using PyVista.

Want to test-drive PyVista? Check out our live examples on MyBinder:

Launch on Binder
  • Pythonic interface to VTK’s Python-C++ bindings

  • Filtering/plotting tools built for interactivity in Jupyter notebooks (see IPython Tools)

  • Direct access to common VTK filters (see Filters)

  • Intuitive plotting routines with matplotlib similar syntax (see Plotting)


PyVista is a powerful tool that researchers can harness to create compelling, integrated visualizations of large datasets in an intuitive, Pythonic manner. Here are a few open-source projects that leverage PyVista:

  • pyansys: Pythonic interface to ANSYS result, full, and archive files

  • PVGeo: Python package of VTK-based algorithms to analyze geoscientific data and models. PyVista is used to make the inputs and outputs of PVGeo’s algorithms more accessible.

  • omfvista: 3D visualization for the Open Mining Format (omf). PyVista provides the foundation for this library’s visualization.

  • discretize: Discretization tools for finite volume and inverse problems. discretize provides toVTK methods that return PyVista versions of their data types for creating compelling visualizations.

  • pymeshfix: Python/Cython wrapper of Marco Attene’s wonderful, award-winning MeshFix software.

  • tetgen: Python Interface to Hang Si’s C++ TetGen Library


Please take a look at the contributors page and the active list of authors to learn more about the developers of PyVista.


We absolutely welcome contributions and we hope that this guide will facilitate an understanding of the PyVista code repository. It is important to note that the PyVista software package is maintained on a volunteer basis and thus we need to foster a community that can support user questions and develop new features to make this software a useful tool for all users. To learn more about contributing to PyVista, please see the Contributing Guide.

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