SimpNMR
SimpNMR is an open-source Python toolkit for prediction, fitting, and analysis of paramagnetic NMR spectra based on experimental data and ab initio calculations.
Features
- Prediction of paramagnetic NMR shifts and spectra
- Susceptibility tensor fitting from experimental measurements
- Integration with quantum chemistry outputs (ORCA, Gaussian, Molcas)
Installation
pip install simpnmr
simpnmr --help
Quick example
simpnmr predict input.yml
Documentation
Project status
Active development. Public APIs and configuration schemas are considered stable; breaking changes are coordinated with maintainers and documented in the changelog.
Support
Please use GitLab Issues for bug reports and feature requests.
Contributing
Development guidelines, architecture, and release policies are documented in the Developer Guide:
👉 https://simpnmr.org/developer_guide/
Citation
If you use SimpNMR in academic work, please cite the associated preprint and the specific version used:
SimpNMR, ChemRxiv (2026). https://chemrxiv.org/doi/full/10.26434/chemrxiv.15001463/v1
License
GPL-3.0-or-later. See LICENSE.
2 maintainers
Release files for simpnmr 2.4.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| simpnmr-2.4.0.tar.gz | 331.3 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| simpnmr-2.4.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 737.3 kB
Release files / simpnmr-2.4.0.tar.gz
| Download URL | simpnmr-2.4.0.tar.gz |
|---|---|
| Size | 331.3 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.2.0 CPython/3.11.15
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Release files / simpnmr-2.4.0-py3-none-any.whl
| Download URL | simpnmr-2.4.0-py3-none-any.whl |
|---|---|
| Size | 406.0 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/6.2.0 CPython/3.11.15
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