PySCF with Auto-differentiation
Installation
To install the latest release, choose the command matching your hardware:
| Hardware | Installation |
|---|---|
| CPU | pip install pyscfad |
| NVIDIA GPU (CUDA 12) | pip install "pyscfad[cuda12]" |
| NVIDIA GPU (CUDA 13) | pip install "pyscfad[cuda13]" |
To install the development version, run:
pip install git+https://github.com/fishjojo/pyscfad.git
The dependent C/C++ library pyscfadlib can be compiled from source following the instruction
here.
Supported platforms
Prebuilt wheels are published for the following platforms:
| Platform | CPU | NVIDIA GPU |
|---|---|---|
| Linux, x86_64 | yes | yes |
| Linux, aarch64 | yes | yes |
| macOS, Apple silicon (arm64) | yes | n/a |
| macOS, Intel (x86_64) | no | n/a |
| Windows, x86_64 | no | no |
| Windows WSL2, x86_64 | yes | yes |
On platforms without a prebuilt wheel, pyscfadlib can still be compiled from source
(see the link above).
pyscfad depends on
jax>=0.9.1,<0.11,
pyscfadlib>=0.3,
pyscf>=2.3, and
pyscf-properties.
Citing PySCFAD
The following paper should be cited in publications utilizing the PySCFAD program package:
Differentiable quantum chemistry with PySCF for molecules and materials at the mean-field level and beyond, X. Zhang, G. K.-L. Chan, J. Chem. Phys., 157, 204801 (2022)
1 maintainer
Metadata
1 maintainer
Release files for pyscfad 0.3.4
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| pyscfad-0.3.4.tar.gz | 334.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyscfad-0.3.4-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 819.7 kB
Release files / pyscfad-0.3.4.tar.gz
| Download URL | pyscfad-0.3.4.tar.gz |
|---|---|
| Size | 334.9 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / pyscfad-0.3.4-py3-none-any.whl
| Download URL | pyscfad-0.3.4-py3-none-any.whl |
|---|---|
| Size | 484.8 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Sep 18, 2026.
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