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 Example Notebooks. 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.
  • Ability to create materials based on natural elements or uranium enrichment
  • Automated multi-group cross section generation (openmc.mgxs)
  • 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_trisos())
  • A fully-featured nuclear data interface (

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.