Python API

OpenMC includes a rich Python API that enables programmatic pre- and post-processing. The easiest way to begin using the API is to take a look at the examples. This assumes that you are already familiar with Python and common third-party packages such as NumPy. If you have never used Python before, the prospect of learning a new code and a programming language might sound daunting. However, you should keep in mind that there are many substantial benefits to using the Python API, including:

  • The ability to define dimensions using variables.

  • Availability of standard-library modules for working with files.

  • An entire ecosystem of third-party packages for scientific computing.

  • Automated multi-group cross section generation (openmc.mgxs)

  • A fully-featured nuclear data interface (

  • Depletion capability (openmc.deplete)

  • Convenience functions (e.g., a function returning a hexagonal region)

  • Ability to plot individual universes as geometry is being created

  • A \(k_\text{eff}\) search function (openmc.search_for_keff())

  • Random sphere packing for generating TRISO particle locations (openmc.model.pack_spheres())

  • Ability to create materials based on natural elements or uranium enrichment

For those new to Python, there are many good tutorials available online. We recommend going through the modules from Codecademy and/or the Scipy lectures.

The full API documentation serves to provide more information on a given module or class.


Users are strongly encouraged to use the Python API to generate input files and analyze results.