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docs/source/pythonapi/index.rst

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+.. _pythonapi:
+
+==========
+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
+:ref:`examples`. This assumes that you are already familiar with Python and
+common third-party packages such as `NumPy <http://www.numpy.org/>`_. 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 (:mod:`openmc.mgxs`)
+- A fully-featured nuclear data interface (:mod:`openmc.data`)
+- Depletion capability (:mod:`openmc.deplete`)
+- Convenience functions (e.g., a function returning a hexagonal region)
+- Ability to plot individual universes as geometry is being created
+- A :math:`k_\text{eff}` search function (:func:`openmc.search_for_keff`)
+- Random sphere packing for generating TRISO particle locations
+  (:func:`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
+<https://www.codecademy.com/learn/learn-python-3>`_ and/or the `Scipy lectures
+<https://scipy-lectures.github.io/>`_.
+
+The full API documentation serves to provide more information on a given module
+or class.
+
+.. tip:: Users are strongly encouraged to use the Python API to generate input
+         files and analyze results.
+
+.. rubric:: Modules
+
+.. toctree::
+   :maxdepth: 1
+
+   base
+   model
+   examples
+   deplete
+   mgxs
+   stats
+   data
+   capi
+   openmoc