vtki Documentation

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vtki 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 module simplifies mesh creation and plotting by adding functionality to existing VTK objects.

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.


vtki 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 vtki:

  • pyansys: Pythonic interface to ANSYS result, full, and archive files
  • PVGeo: Python package of VTK-based algorithms to analyze geoscientific data and models. vtki is used to make the inputs and outputs of PVGeo’s algorithms more accessible.
  • omfvtk: 3D visualization for the Open Mining Format (omf). vtki provides the foundation for this library’s visualization.
  • discretize: Discretization tools for finite volume and inverse problems. discretize provides toVTK methods that return vtki 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

Getting Started

If you have a working copy of VTK, installation is simply:

$ pip install vtki

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

See Installation for more details.

Data Types

The Visualization Toolkit (VTK), developed by Kitware, has many mesh data types that vtki wraps. This chapter is intended to describe these different mesh types on the VTK side to help new users understand which data types to use.


Be sure to head over to the Quick Examples chapter to explore different use cases of vtki and to start visualizing 3D data in Pyhton!


  • 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)

Project Index