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Ansys Data Processing Framework™(DPF) provides reusable operators that allow you to access and transform simulation data coming from different Ansys and third-party result files. These operators are computation libraries that can be extended with custom libraries. You have multiple options for interfacing with the DPF framework:

  • Via APIs for building your client in C, C++, or Python (with open source libraries).
  • Via the dedicated IronPython/C# scripting interface provided by the Ansys Mechanical application.
The DPF framework allows you to extend its capabilities by exposing your product capabilities as native operators. You can use these custom operators within Mechanical or other Ansys applications that support the DPF framework. Plus, you can access these operators remotely via gRPC from Python/C#/C++ client APIs, without having to learn gRPC or any of these languages. To use the DPF APIs, you need to install a DPF server on your machine. The Ansys Unified Installer includes major releases of the DPF server by default, requiring no extra selection. You can find beta releases on the [DPF Pre-Release page](https://download.ansys.com/Others/DPF%20Pre-Release "(opens in a new window)") of the Ansys Customer Portal.

OS and supported languages

DPF libraries are available for Windows and Linux in:

  • C/C++
  • C#
  • IronPython
  • Python (open source)

Documentation

DPF Framework

Get a comprehensive overview of the DPF framework with detailed specifications for all operators in the official Ansys plugins. This guide is your starting point for API integration and advanced usage, and includes a changelog to track the latest updates.

DPF C++ client library

Build your client in C++ to connect with the DPF framework and leverage its post-simulation analysis and computation. Customize workflows and expand operator libraries as needed.

PyDPF - Core (open source)

Use the PyDPF-Core library, which provides the same functionality as the DPF C++ client library, to connect to and interact with DPF.

PyDPF Composites (open source)

Build your Python module based on DPF to perform composite-specific postprocessing by using failure criteria or user-defined routines. This module is applicable for short-fiber, layered, and homogeneous structures.