Wavefunction analysis, made reproducible.
Wavefunction post-processing for quantum chemistry. Use the same scientific engine from the CLI, Python, MCP or terminal chat.
openWFN reads supported quantum-chemistry files and returns analysis results with units, warnings and source provenance. Analyze individual calculations and high-throughput collections without changing the scientific engine between interfaces.
See the 0.12.0 release notes for the supported interfaces, verification and scientific boundaries.
Install and inspect a file
Published package:
python -m pip install --upgrade openwfn
openwfn --version
For development from source, use a separate environment:
python -m venv .venv
source .venv/bin/activate
python -m pip install -e .
The normal installation includes format readers, output extraction, Python API, local MCP and terminal chat in the normal installation. No model weights, Gaussian utilities or public servers are installed automatically.
openwfn molecule.molden open
openwfn molecule.molden capabilities
openwfn molecule.fchk summary
openwfn --format json molecule.fchk analyze
Guided mode offers workflows supported by the selected file. It shows settings,
units and atom numbering, checks grid size, confirms save paths, and can show the
equivalent command. Scripts should use explicit commands such as summary;
file-only non-terminal invocations now return a bounded overview.
Supported input families
| Files | Available data determine the analyses |
|---|---|
.fchk, .fch, .molden, .molden.input, .wfn, .wfx, .mwfn, .mkl |
Wavefunction records, basis, orbitals and electronic state |
.cube, .cub |
Stored scalar grids, axes and units |
Gaussian, ORCA and Q-Chem .log / .out |
Source-reported properties and supported spectroscopy records |
.xyz, .pdb, .mol, .sdf |
Molecular structure and supported formal-charge records |
Binary .chk is a proprietary binary format. Conversion needs Gaussian's
separately installed formchk; pip does not supply it. A parser cannot create
wavefunction data that the input does not contain. See the
format contract for variants and limitations.
Scientific analyses
The shared engine provides geometry, frontier orbitals, MO composition/cubes, Mulliken/Löwdin/Hirshfeld populations, Mayer bond orders, DOS/PDOS, density checks, ESP, supported vibrational/excited-state properties and conservative NTO analysis. It also exposes bounded QTAIM critical-point searches and ELF/LOL/NCI fields.
Population analysis uses source-reported effective nuclear charges for ECP and ghost centers; conservation failures return partial results with warnings. The direct density default is 0.15 bohr spacing, not a convergence guarantee. Use coarser settings for exploration and check convergence before reporting values.
openwfn molecule.fchk orbitals frontier --spin all
openwfn molecule.fchk population mulliken
openwfn molecule.fchk density integrate --spacing 0.3 --padding 6
openwfn calculation.out properties
Scientific status is separate from package status. Hirshfeld and other Validated methods are validated only for their named scopes. Spectroscopy, output extraction and the newer real-space tools retain their documented Experimental boundaries. QTAIM basin integration is not included.
Conservation errors and source warnings stay visible. Unknown charge/spin is not guessed; normal job termination is not proof of optimization convergence. Density settings require a convergence study for the intended property. Methods, validation and limitations explain those boundaries.
Python, collections and saved results
from openwfn import load
calculation = load("molecule.molden")
print(calculation.capabilities())
result = calculation.analyze("frontier-all")
print(result.as_dict())
openwfn batch ./calculations \
--analyses summary,frontier --output-dir ./results --resume
openwfn --format json --output summary.json molecule.fchk summary
JSON preserves the complete result envelope. HTML/Markdown reports, CSV tables, figures, cube files and the offline workbench are export options, not requirements for Linux or headless workflows.
Scientific assistant and MCP
Configure an existing local model; openWFN does not train or download one:
openwfn molecule.molden chat --model qwen3:8b
openwfn chat
For file questions, openWFN checks capabilities and settings and supplies the scientific values. General conversation works without a file and is labelled as model-generated, not independently verified. Remote model use requires explicit permission. See assistant setup.
The normal installation also includes a read-only local MCP server:
python -m openwfn.mcp_server --data-root ./inputs
That process waits for an MCP client on stdio; it is not a public HTTP service. MCP setup describes client configuration, confirmation and resource limits. External hosts control their own generated prose.
Documentation and contributing
- First analysis
- CLI reference and Python API
- Citation
- Contributor guide and security policy
- Release history
The package includes redistributable examples:
openwfn examples install ./openwfn-examples
openwfn ./openwfn-examples/water.fchk summary
Keep the input checksum, package version, command/settings and complete result with your work. Do not post unpublished calculations, credentials or personal paths in public issues. Project-owned code is MIT licensed; dependency terms are listed in third-party notices.
Metadata
Release files for openwfn 0.12.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| openwfn-0.12.0.tar.gz | 928.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| openwfn-0.12.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 1.9 MB
Release files / openwfn-0.12.0.tar.gz
| Download URL | openwfn-0.12.0.tar.gz |
|---|---|
| Size | 928.2 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Transparency logRelease files / openwfn-0.12.0-py3-none-any.whl
| Download URL | openwfn-0.12.0-py3-none-any.whl |
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| Size | 938.7 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
9d5b038a674fa8027afd433f42ff1808fcf35a941ebb6d4f38ea6f215cac4757
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de594103bd1cef284225962bf5bdfcde3f921bb02791200e6ac813f3267b0dcb
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| Upload date | |
|
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 Oct 7, 2026.
Transparency log