openwfn 0.8.0

Wavefunction analysis, made reproducible.

A unified post-processing toolkit for turning quantum-chemistry calculations into traceable, reproducible, review-ready results.

Get started · CLI reference · Validation · Citation

openWFN connects scientific analysis, automation, validation evidence, and research output through one typed calculation model. It works locally through the command line or Python, from individual calculations and high-throughput collections.

Analyze · Automate · Validate · Publish

• Analyze molecular structure, orbitals, electron density, atomic populations, electrostatic potential, and derived properties.
• Automate with stable CLI commands, a typed Python API, structured results, resumable batches, and JSON/CSV exports.
• Validate using explicit capability status, parser provenance, transformations, numerical controls, and fixture-backed evidence.
• Publish durable reports, figures, cube files, structures, and batch manifests.

Install

openWFN supports Python 3.10–3.13.

Install the stable release:

python -m pip install --upgrade openwfn
openwfn --version

Install the exact release when reproducing research:

python -m pip install openwfn==0.8.0

First analysis

openwfn examples install ./openwfn-examples
openwfn ./openwfn-examples/water.fchk doctor
openwfn ./openwfn-examples/water.fchk summary
openwfn ./openwfn-examples/water.fchk orbitals frontier

For your own calculation, replace the example path:

openwfn molecule.fchk summary

Run a collection of calculations with resumable, structured output:

openwfn batch ./calculations \
  --analyses summary,frontier \
  --output-dir ./results \
  --resume

Use JSON when another program will consume the result:

openwfn --format json --output summary.json molecule.fchk summary

Capability map

“Validated” is deliberately scoped. Review the validation evidence and limitations before research use.

Input support

Gaussian formatted-checkpoint (.fchk) data currently provides the full electronic wavefunction record used by openWFN analyses. Gaussian .chk is a proprietary binary format; openWFN calls Gaussian's separately installed formchk utility and does not decode it directly.

XYZ, MOL/SDF, and PDB inputs provide structure-only records. Additional quantum-chemistry parsers will be listed as supported only after their implementation and validation evidence are available.

openwfn calculation.chk formchk calculation.fchk
openwfn calculation.fchk convert --to sdf --output molecule.sdf
openwfn calculation.fchk density cube density.cube

Documentation

• First analysis
• CLI workflows
• Complete CLI reference
• Python API
• Scientific methods
• Validation status
• Optional workbench
• Troubleshooting

Security and privacy

Computations are local, but input and generated artifacts can contain unpublished research. Never post private checkpoint files, credentials, personal filesystem paths, or license details in public issues. Read the security and data-privacy guide.

Development

python -m pip install -e ".[test,docs]"
python -m pytest
python -m ruff check .
python scripts/run_validation.py
python scripts/check_docs.py --root .
python -m mkdocs build --strict

Contributions should include tests, documented units and assumptions, and validation evidence appropriate to the claim. See Contributing.

Project policies: Code of Conduct · Security · Maintainers · Contributors · Roadmap

Citation and license

Cite the exact version used and the project repository; see the citation guide. openWFN is released under the MIT License.

Author: Muhammed Shah Shaji