{"categories":[{"label":"Information Analysis","url":"https://skillfed.io/packages/category/scientific-engineering-information-analysis/3"}],"enrichment":{"capability":"Provides a Python interface to Ansys Data Processing Framework (DPF) for reading, transforming, and postprocessing simulation data from Ansys solver result files and neutral formats like CSV, HDF5, and VTK.","skillfed_tags":["ansys-integration","simulation-postprocessing","scientific-computing"],"use_cases":["Extract displacement, stress, or other results from Mechanical APDL .rst files and perform post-analysis calculations in Python","Chain DPF operators to compute derived quantities (e.g., stress norms, energy sums) from raw solver output without manual data extraction","Read LS-DYNA .d3plot or Fluent .cas/.dat.h5 results and integrate them into a larger simulation workflow or optimization loop","Convert Ansys result data to neutral formats (VTK, HDF5) for visualization or sharing with non-Ansys tools","Automate batch postprocessing of multiple simulation runs by scripting DPF model loading and result evaluation"],"what_it_does":"ansys-dpf-core is a Python wrapper around Ansys Data Processing Framework, a physics-agnostic tool for accessing and transforming simulation results. It reads output from Mechanical APDL, LS-DYNA, Fluent, CFX, and other Ansys solvers, as well as neutral formats like CSV, HDF5, and VTK. The package represents data as mathematical fields and chains operators together to build reusable preprocessing or postprocessing workflows.\n\nThe library automatically starts a local DPF service in the background or can connect to a remote instance. It depends on grpcio for service communication, numpy for numerical operations, protobuf for data serialization, and optional PyVista for visualization. The package is actively maintained and supports current Python versions (3.10+).","worth_installing":"Yes, if you have access to a compatible Ansys installation or ansys-dpf-server. The package is actively maintained, has no known vulnerabilities, uses a permissive MIT license, and offers low-friction installation. It is the official Python interface to DPF and is well-suited for automating postprocessing workflows. Not suitable as a standalone tool\u2014DPF server availability is a hard prerequisite."},"id":"ansys-dpf-core","links":{"html":"https://skillfed.io/packages/ansys-dpf-core","md":"https://skillfed.io/packages/ansys-dpf-core.md","pypi":"https://pypi.org/project/ansys-dpf-core/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-06-08","license_spdx":"MIT","license_treatment":"permissive","name":"ansys-dpf-core","python_support":"supports_current","summary":"Data Processing Framework - Python Core "},"popularity":{"monthly_downloads":122727,"position":11937,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"0.16.1"}