| Name | qccodec JSON |
| Version |
0.9.0
JSON |
| download |
| home_page | None |
| Summary | A package for parsing Quantum Chemistry program file outputs into structured qcio data objects. |
| upload_time | 2025-10-09 18:43:48 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.10 |
| license | The MIT License (MIT)
Copyright (c) 2023 Colton Hicks
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in
all copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
THE SOFTWARE. |
| keywords |
computational chemistry
file parser
parsing
qcio
quantum chemistry
scientific computing
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# qccodec
A library for parsing Quantum Chemistry output files into structured data objects and converting structured input objects into program-native input files. Uses data structures from [qcio](https://github.com/coltonbh/qcio).
[](https://pypi.python.org/pypi/qccodec)
[](https://pypi.python.org/pypi/qccodec)
[](https://pypi.python.org/pypi/qccodec)
[](https://github.com/coltonbh/qccodec/actions)
[](https://github.com/coltonbh/qccodec/actions)
`qccodec` works in harmony with a suite of other quantum chemistry tools for fast, structured, and interoperable quantum chemistry.
## The QC Suite of Programs
- [qcconst](https://github.com/coltonbh/qcconst) - Physical constants, conversion factors, and a periodic table with clear source information for every value.
- [qcio](https://github.com/coltonbh/qcio) - Beautiful and user friendly data structures for quantum chemistry.
- [qccodec](https://github.com/coltonbh/qccodec) - A library for efficient parsing of quantum chemistry data into structured `qcio` objects and conversion of `qcio` input objects to program-native input files.
- [qcop](https://github.com/coltonbh/qcop) - A package for operating quantum chemistry programs using `qcio` standardized data structures. Compatible with `TeraChem`, `psi4`, `QChem`, `NWChem`, `ORCA`, `Molpro`, `geomeTRIC` and many more.
- [BigChem](https://github.com/mtzgroup/bigchem) - A distributed application for running quantum chemistry calculations at scale across clusters of computers or the cloud. Bring multi-node scaling to your favorite quantum chemistry program.
- `ChemCloud` - A [web application](https://github.com/mtzgroup/chemcloud-server) and associated [Python client](https://github.com/mtzgroup/chemcloud-client) for exposing a BigChem cluster securely over the internet.
## ✨ Basic Usage
- Installation:
```sh
python -m pip install qccodec
```
- Parse QC program outputs into structured data files with a single line of code.
```python
from pathlib import Path
from qcio import CalcType
from qccodec import decode
stdout = Path("tc.out").read_text()
data = decode("terachem", CalcType.gradient, stdout=stdout)
```
- The `data` object will be a `qcio` object, either `SinglePointData`, `OptimizationData`, `ConformerSearchData` or other `*Data` structure depending on the `calctype`. Run `dir(data)` inside a Python interpreter to see the various values you can access. A few prominent values are shown here as an example:
```python
from pathlib import Path
from qcio import CalcType
from qccodec import decode
stdout = Path("tc.out").read_text()
data = decode("terachem", CalcType.hessian, stdout=stdout)
data.energy
data.gradient # If a gradient calc
data.hessian # If a hessian calc
data.calcinfo_nmo # Number of molecular orbitals
```
- Parsed values can be written to disk like this:
```py
with open("data.json", "w") as f:
f.write(data.model_dumps_json())
```
- And read from disk like this:
```py
from qcio import SinglePointData
data = SinglePointData.open("data.json")
```
- You can also run `qccodec` from the command line like this:
```sh
qccodec -h # Get help message for cli
qccodec terachem hessian tests/data/terachem/water.frequencies.out > data.json # Parse TeraChem stdout to json
```
- More complex parsing can be accomplished by passing the directory containing the scratch files to `decode` and optionally the input data used to generate the calculation (usually done from `qcop` which uses structure data):
```python
from pathlib import Path
from qcio import CalcType, ProgramInput
from qccodec import decode
stdout = Path("tc.out").read_text()
directory = Path(".") / "scr.geom"
input_data = ProgramInput.open("prog_inp.json")
data = decode("terachem", CalcType.hessian, stdout=stdout, directory=directory, input_data=input_data)
```
## 💻 Contributing
Please see the [contributing guide](./CONTRIBUTING.md) for details on how to contribute new parsers to this project :)
If there's data you'd like parsed from output files or want to support input files for a new program, please open an issue in this repo explaining the data items you'd like parsed and include an example output file containing the data, like [this](https://github.com/coltonbh/qccodec/issues/2).
Raw data
{
"_id": null,
"home_page": null,
"name": "qccodec",
"maintainer": null,
"docs_url": null,
"requires_python": ">=3.10",
"maintainer_email": null,
"keywords": "computational chemistry, file parser, parsing, qcio, quantum chemistry, scientific computing",
"author": null,
"author_email": "Colton Hicks <github@coltonhicks.com>",
"download_url": "https://files.pythonhosted.org/packages/2f/17/0083b860463e1ca22b2772634f91c28f45b717f53d1d1f58e86e06b6243b/qccodec-0.9.0.tar.gz",
"platform": null,
"description": "# qccodec\n\nA library for parsing Quantum Chemistry output files into structured data objects and converting structured input objects into program-native input files. Uses data structures from [qcio](https://github.com/coltonbh/qcio).\n\n[](https://pypi.python.org/pypi/qccodec)\n[](https://pypi.python.org/pypi/qccodec)\n[](https://pypi.python.org/pypi/qccodec)\n[](https://github.com/coltonbh/qccodec/actions)\n[](https://github.com/coltonbh/qccodec/actions)\n\n`qccodec` works in harmony with a suite of other quantum chemistry tools for fast, structured, and interoperable quantum chemistry.\n\n## The QC Suite of Programs\n\n- [qcconst](https://github.com/coltonbh/qcconst) - Physical constants, conversion factors, and a periodic table with clear source information for every value.\n- [qcio](https://github.com/coltonbh/qcio) - Beautiful and user friendly data structures for quantum chemistry.\n- [qccodec](https://github.com/coltonbh/qccodec) - A library for efficient parsing of quantum chemistry data into structured `qcio` objects and conversion of `qcio` input objects to program-native input files.\n- [qcop](https://github.com/coltonbh/qcop) - A package for operating quantum chemistry programs using `qcio` standardized data structures. Compatible with `TeraChem`, `psi4`, `QChem`, `NWChem`, `ORCA`, `Molpro`, `geomeTRIC` and many more.\n- [BigChem](https://github.com/mtzgroup/bigchem) - A distributed application for running quantum chemistry calculations at scale across clusters of computers or the cloud. Bring multi-node scaling to your favorite quantum chemistry program.\n- `ChemCloud` - A [web application](https://github.com/mtzgroup/chemcloud-server) and associated [Python client](https://github.com/mtzgroup/chemcloud-client) for exposing a BigChem cluster securely over the internet.\n\n## \u2728 Basic Usage\n\n- Installation:\n\n ```sh\n python -m pip install qccodec\n ```\n\n- Parse QC program outputs into structured data files with a single line of code.\n\n ```python\n from pathlib import Path\n from qcio import CalcType\n from qccodec import decode\n\n stdout = Path(\"tc.out\").read_text()\n data = decode(\"terachem\", CalcType.gradient, stdout=stdout)\n ```\n\n- The `data` object will be a `qcio` object, either `SinglePointData`, `OptimizationData`, `ConformerSearchData` or other `*Data` structure depending on the `calctype`. Run `dir(data)` inside a Python interpreter to see the various values you can access. A few prominent values are shown here as an example:\n\n ```python\n from pathlib import Path\n from qcio import CalcType\n from qccodec import decode\n\n stdout = Path(\"tc.out\").read_text()\n data = decode(\"terachem\", CalcType.hessian, stdout=stdout)\n\n data.energy\n data.gradient # If a gradient calc\n data.hessian # If a hessian calc\n data.calcinfo_nmo # Number of molecular orbitals\n ```\n\n- Parsed values can be written to disk like this:\n\n ```py\n with open(\"data.json\", \"w\") as f:\n f.write(data.model_dumps_json())\n ```\n\n- And read from disk like this:\n\n ```py\n from qcio import SinglePointData\n\n data = SinglePointData.open(\"data.json\")\n ```\n\n- You can also run `qccodec` from the command line like this:\n\n ```sh\n qccodec -h # Get help message for cli\n\n qccodec terachem hessian tests/data/terachem/water.frequencies.out > data.json # Parse TeraChem stdout to json\n ```\n\n- More complex parsing can be accomplished by passing the directory containing the scratch files to `decode` and optionally the input data used to generate the calculation (usually done from `qcop` which uses structure data):\n\n ```python\n from pathlib import Path\n from qcio import CalcType, ProgramInput\n from qccodec import decode\n\n stdout = Path(\"tc.out\").read_text()\n directory = Path(\".\") / \"scr.geom\"\n input_data = ProgramInput.open(\"prog_inp.json\")\n\n data = decode(\"terachem\", CalcType.hessian, stdout=stdout, directory=directory, input_data=input_data)\n ```\n\n## \ud83d\udcbb Contributing\n\nPlease see the [contributing guide](./CONTRIBUTING.md) for details on how to contribute new parsers to this project :)\n\nIf there's data you'd like parsed from output files or want to support input files for a new program, please open an issue in this repo explaining the data items you'd like parsed and include an example output file containing the data, like [this](https://github.com/coltonbh/qccodec/issues/2).\n",
"bugtrack_url": null,
"license": "The MIT License (MIT)\n \n Copyright (c) 2023 Colton Hicks\n \n Permission is hereby granted, free of charge, to any person obtaining a copy\n of this software and associated documentation files (the \"Software\"), to deal\n in the Software without restriction, including without limitation the rights\n to use, copy, modify, merge, publish, distribute, sublicense, and/or sell\n copies of the Software, and to permit persons to whom the Software is\n furnished to do so, subject to the following conditions:\n \n The above copyright notice and this permission notice shall be included in\n all copies or substantial portions of the Software.\n \n THE SOFTWARE IS PROVIDED \"AS IS\", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR\n IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,\n FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE\n AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER\n LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,\n OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN\n THE SOFTWARE.",
"summary": "A package for parsing Quantum Chemistry program file outputs into structured qcio data objects.",
"version": "0.9.0",
"project_urls": {
"Bug Tracker": "https://github.com/coltonbh/qccodec/issues",
"Changelog": "https://github.com/coltonbh/qccodec/blob/master/CHANGELOG.md",
"Documentation": "https://github.com/coltonbh/qccodec#readme",
"Homepage": "https://github.com/coltonbh/qccodec",
"Source": "https://github.com/coltonbh/qccodec"
},
"split_keywords": [
"computational chemistry",
" file parser",
" parsing",
" qcio",
" quantum chemistry",
" scientific computing"
],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "c8f3c927721458c8cd84e3cf0554cf55497c0f879f608ca17944a1c8d5189725",
"md5": "c44066cfb5c16db8520eeb2079373d3f",
"sha256": "953d27230e3d954daaa8aa1c0869f228ea4741cee3b624c780684b0d681a080f"
},
"downloads": -1,
"filename": "qccodec-0.9.0-py3-none-any.whl",
"has_sig": false,
"md5_digest": "c44066cfb5c16db8520eeb2079373d3f",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": ">=3.10",
"size": 24626,
"upload_time": "2025-10-09T18:43:46",
"upload_time_iso_8601": "2025-10-09T18:43:46.613670Z",
"url": "https://files.pythonhosted.org/packages/c8/f3/c927721458c8cd84e3cf0554cf55497c0f879f608ca17944a1c8d5189725/qccodec-0.9.0-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "2f170083b860463e1ca22b2772634f91c28f45b717f53d1d1f58e86e06b6243b",
"md5": "0edd08d55f46085e3d476876960a8e69",
"sha256": "f1fe3630093a47ae24047db670e5da5fd470fbef09e29f0aff93fb7135437e6e"
},
"downloads": -1,
"filename": "qccodec-0.9.0.tar.gz",
"has_sig": false,
"md5_digest": "0edd08d55f46085e3d476876960a8e69",
"packagetype": "sdist",
"python_version": "source",
"requires_python": ">=3.10",
"size": 401329,
"upload_time": "2025-10-09T18:43:48",
"upload_time_iso_8601": "2025-10-09T18:43:48.314563Z",
"url": "https://files.pythonhosted.org/packages/2f/17/0083b860463e1ca22b2772634f91c28f45b717f53d1d1f58e86e06b6243b/qccodec-0.9.0.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-10-09 18:43:48",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "coltonbh",
"github_project": "qccodec",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "qccodec"
}
