chemparseplot 1.6.1

Parsers and plotting tools for computational chemistry

Table of Contents

• About
  • Installation
  • Ecosystem Overview
  • Features
    • Supported Engines
  • Documentation
  • Contributing
• License
• Acknowledgments

About

A pure-python¹ parsing and plotting library for computational chemistry outputs. chemparseplot extracts structured data from quantum chemistry codes (ORCA, eOn, Sella, ChemGP) and produces publication-quality, unit-aware visualizations with scientific color maps.

Computational tasks (surface fitting, structure analysis, interpolation) are handled by rgpycrumbs, which is a required dependency. chemparseplot parses output files, delegates heavy computation to rgpycrumbs, and produces publication-quality plots.

Installation

pip install chemparseplot
# With plotting support
pip install "chemparseplot[plot]"
# Everything
pip install "chemparseplot[all]"

For development:

git clone https://github.com/HaoZeke/chemparseplot
cd chemparseplot
uv sync --all-extras

See the installation guide and quickstart for details.

Ecosystem Overview

chemparseplot is part of the rgpycrumbs suite of interlinked libraries.

Features

• Parsing computational chemistry output files into structured data
• Plotting with scientific color maps (camera-ready)
• Unit preserving throughout via pint
• Computation delegated to rgpycrumbs for surface fitting, interpolation, and structure analysis

Supported Engines

• ORCA (5.x)
  • Geometry scan (OPT) energy profiles
  • Nudged elastic band (NEB) path visualization
• eOn
  • Saddle search parsing (Dimer, GPRD, LBFGS methods)
  • NEB path energy profiles with landscape projections
• Sella
  • Saddle point optimization result parsing
• Trajectory formats
  • HDF5 trajectories (ChemGP output with pre-computed forces)
  • Generic ASE-readable formats (extxyz, .traj) for NEB analysis

Documentation

Full documentation is at https://chemparseplot.rgoswami.me. This includes:

• A quickstart guide
• Tutorials for common workflows
• API reference

Contributing

Contributions are welcome. See CONTRIBUTING.md for development setup and guidelines, and our Code of Conduct.

For bug reports or questions, open an issue on GitHub.

License

MIT. However, this is an academic resource, so please cite as much as possible via:

• The Zenodo DOI for general use.
• The wailord paper for ORCA usage

Acknowledgments

This project builds on work supported by the University of Iceland and the Icelandic Research Fund. chemparseplot relies on rgpycrumbs for computational modules.

Footnotes

¹ To distinguish it from my other thin-python wrapper projects