.. _ref_getting_started:

===============
Getting started
===============

The Data Processing Framework (DPF) provides numerical simulation users and engineers with a toolbox
for accessing and transforming simulation data. DPF can access data from Ansys solver
result files as well as from several neutral file formats. For more information, see :ref:`introduction`.

This **workflow-based** framework allows you to perform complex preprocessing and
postprocessing operations on large amounts of simulation data.

PyDPF-Core is a Python client API communicating with a **DPF Server**, either
through the network using gRPC or directly in the same process.

.. grid:: 1 2 3 3
    :gutter: 1 2 3 3
    :padding: 1 2 3 3

    .. grid-item-card:: Installation summary :fa:`rectangle-list`
        :link: summary
        :link-type: doc

        Short overview of the installation steps to get started with PyDPF-Core.

    .. grid-item-card:: Installing PyDPF-Core :fa:`file-arrow-down`
        :link: install
        :link-type: doc

        Learn how to install the PyDPF-Core python package.

    .. grid-item-card:: Installing DPF Server :fa:`download`
        :link: dpf_server
        :link-type: doc

        Learn how to install the DPF Server.

    .. grid-item-card:: Compatibility :fa:`handshake`
        :link: compatibility
        :link-type: doc

        Learn about the compatibility between PyDPF-Core and DPF Server versions.

    .. grid-item-card:: Licensing :fa:`user-check`
        :link: licensing
        :link-type: doc

        Learn about the licensing requirements for using PyDPF-Core and DPF Server.

    .. grid-item-card:: Dependencies :fa:`circle-nodes`
        :link: dependencies
        :link-type: doc

        Learn about the dependencies required to use PyDPF-Core.



.. toctree::
   :maxdepth: 2
   :hidden:

   summary
   install
   dpf_server
   compatibility
   licensing
   dependencies