Skip to main content

Data Processing Framework (DPF) for developers

Overview

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 DPF:

  • 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.

DPF as a development 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 DPF. 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.

OS and supported languages

DPF libraries are available for Windows and Linux in:

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

Documentation

DPF C++ client library

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

2024 R2

Previous

Python Result Object

Use DPF via IronPython/C# scripts from Mechanical to evaluate output quantities.

2024 R2

Previous

PyDPF - Core (open source)

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

View docs

PyDPF - Post (open source)

Build your Python client to connect with DPF and leverage its post-simulation analysis and computation capabilities.

View docs

PyDPF Composites (open source)

Build your Python client to connect with DPF and leverage its post-simulation analysis and computation capabilities on layered and short-fiber composite models.

View docs