About

Introduction

Screenshot of pyiron running inside jupyterlab.

pyiron is an integrated development environment for implementing, testing, and running simulations in computational materials science. It combines several tools in a common plattform:

  • Atomic structure objects – compatible to the Atomic Simulation Environment (ASE).
  • Atomistic simulation codes – like LAMMPS and VASP.
  • Feedback Loops – to construct dynamic simulation life cycles.
  • Hierarchical data management – interfacing with storage resources like SQL and HDF5.
  • Integrated visualization – based on NGLview.
  • Interactive simulation protocols - based on Jupyter notebooks.
  • Object oriented job management – for scaling complex simulation protocols from single jobs to high-throughput simulations.

pyiron (called pyron) is developed in the Computational Materials Design department of Joerg Neugebauer at the Max Planck Insitut für Eisenforschung (Max Planck Insitute for iron research). While its original focus was to provide a framework to develop and run complex simulation protocols as needed for ab initio thermodynamics it quickly evolved into a versatile tool to manage a wide variety of simulation tasks. In 2016 the Interdisciplinary Centre for Advanced Materials Simulation (ICAMS) joined the development of the framework with a specific focus on high throughput applications. In 2018 pyiron was released as open-source project.

Getting Help

Technical issues and bugs should be reported on Github.

Release history

Release 1.0.0 (2018)

  • plugin based infrastructure for flexible extension.
  • opensource release - licensed under the BSD license.
  • installation available on pip and anaconda.
  • moved opensource repository to github.

Release 0.9.3 (2017)

  • Name changed from PyIron to pyiron
  • Fileoperations implemented (move, copy_to and remove).
  • NGLview for visualisation.
  • Atoms class speedup.
  • Serial- and parallelmaster work with the cluster environment.
  • S/PHI/nX support added.
  • Python 3.6 support added.

Release 0.9.2 (2016)

  • Rewirte serial- and parallelmaster.
  • Deprecated Qt environment in favor of jupyter.
  • Python 3.5 support added.
  • Use anaconda as recommended Python environment.
  • Switch to Gitlab rather than subversion.

Release 0.9.1 (2015)

  • Linux and Mac OS X support added.
  • ASE compatible atom and atoms class.

Release 0.0.1 (2011)

  • initial version named PyCMW