ORCA Meets Python─The ORCA Python Interface OPI

The ORCA program suite is one of the most widely used quantum chemistry software packages. It features a wide range of electronic structure methods and algorithms for the prediction of molecular chemical properties, reactivity, and spectroscopy. In this paper, we present a fully featured ORCA Python Interface termed OPI to drastically increase the accessibility of ORCA's method portfolio and enable efficient automation of quantum chemical workflows. OPI is an open-source Python library that provides straightforward low-level access to ORCA's input, execution, and output with a few lines of Python code. In the following, we introduce OPI version 2.0 and its key features, also outlining its general architecture. In addition, we demonstrate its application through several diverse examples of quantum chemical workflows. These examples include a system-dependent optimal-tuning procedure for range-separated hybrid functionals, generation of training data for machine learning purposes, orbital localization and visualization for chemical education, and calculations with density functional ensembles. Finally, we outline the current status of OPI and future plans for its development. OPI is compatible with ORCA ≥ 6.1.1 and Python ≥ 3.11. The project, its code, and its including documentation are available at https://github.com/faccts/opi. OPI is also available through PyPI (https://pypi.org/project/orca-pi).

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Publication Details

Journal
Journal of Chemical Theory and Computation
Published
2026-03-26
DOI
https://doi.org/10.1021/acs.jctc.5c02141
Primary Topic
Machine Learning in Materials Science
Type
article
Field-Weighted Citation Impact
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article

ORCA Meets Python─The ORCA Python Interface OPI

Christoph Riplinger, Hagen Neugebauer, Christoph Plett, Markus Bursch et al.
Journal of Chemical Theory and Computation
Machine Learning in Materials Science
article

ORCA Meets Python─The ORCA Python Interface OPI

Christoph Riplinger, Hagen Neugebauer, Christoph Plett, Markus Bursch, Tim Tetenberg, Nakul Santhosh
article en

Abstract

The ORCA program suite is one of the most widely used quantum chemistry software packages. It features a wide range of electronic structure methods and algorithms for the prediction of molecular chemical properties, reactivity, and spectroscopy. In this paper, we present a fully featured ORCA Python Interface termed OPI to drastically increase the accessibility of ORCA's method portfolio and enable efficient automation of quantum chemical workflows. OPI is an open-source Python library that provides straightforward low-level access to ORCA's input, execution, and output with a few lines of Python code. In the following, we introduce OPI version 2.0 and its key features, also outlining its general architecture. In addition, we demonstrate its application through several diverse examples of quantum chemical workflows. These examples include a system-dependent optimal-tuning procedure for range-separated hybrid functionals, generation of training data for machine learning purposes, orbital localization and visualization for chemical education, and calculations with density functional ensembles. Finally, we outline the current status of OPI and future plans for its development. OPI is compatible with ORCA ≥ 6.1.1 and Python ≥ 3.11. The project, its code, and its including documentation are available at https://github.com/faccts/opi. OPI is also available through PyPI (https://pypi.org/project/orca-pi).

Journal of Chemical Theory and Computation
Fracture Analysis Consultants (United States) (US)
Quality Education
Openalex Percentile: Top 8%
Machine Learning in Materials Science
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ORCA Meets Python─The ORCA Python Interface OPI — Christoph Riplinger, Hagen Neugebauer, et al. · Journal of Chemical Theory and Computation (2026) | TGRS Research Map | TGRS