Name | qcparse JSON |
Version |
0.7.3
JSON |
| download |
home_page | None |
Summary | A package for parsing Quantum Chemistry program file outputs into structured qcio data objects. |
upload_time | 2025-02-09 01:58:06 |
maintainer | None |
docs_url | None |
author | Colton Hicks |
requires_python | <4.0,>=3.9 |
license | MIT |
keywords |
|
VCS |
 |
bugtrack_url |
|
requirements |
No requirements were recorded.
|
Travis-CI |
No Travis.
|
coveralls test coverage |
No coveralls.
|
# qcparse
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/qcparse)
[](https://pypi.python.org/pypi/qcparse)
[](https://pypi.python.org/pypi/qcparse)
[](https://github.com/coltonbh/qcparse/actions)
[](https://github.com/coltonbh/qcparse/actions)
[](https://github.com/charliermarsh/ruff)
`qcparse` works in harmony with a suite of other quantum chemistry tools for fast, structured, and interoperable quantum chemistry.
## The QC Suite of Programs
- [qcio](https://github.com/coltonbh/qcio) - Beautiful and user friendly data structures for quantum chemistry.
- [qcparse](https://github.com/coltonbh/qcparse) - 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 qcparse
```
- Parse a file into a `SinglePointResults` object with a single line of code.
```python
from qcparse import parse
# May pass a path or the contents of a file as string/bytes
results = parse("terachem", "/path/to/stdout.log")
```
- The `results` object will be a `qcio.SinglePointResults` object. Run `dir(results)` inside a Python interpreter to see the various values you can access. A few prominent values are shown here as an example:
```python
from qcparse import parse
results = parse("/path/to/tc.out", "terachem")
results.energy
results.gradient # If a gradient calc
results.hessian # If a hessian calc
results.calcinfo_nmo # Number of molecular orbitals
```
- Parsed values can be written to disk like this:
```py
with open("results.json", "w") as f:
f.write(result.model_dumps_json())
```
- And read from disk like this:
```py
from qcio import SinglePointResults
results = SinglePointResults.open("results.json")
```
- You can also run `qcparse` from the command line like this:
```sh
qcparse -h # Get help message for cli
qcparse terachem ./path/to/tc.out > results.json # Parse TeraChem stdout to json
```
## 💻 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/qcparse/issues/2).
Raw data
{
"_id": null,
"home_page": null,
"name": "qcparse",
"maintainer": null,
"docs_url": null,
"requires_python": "<4.0,>=3.9",
"maintainer_email": null,
"keywords": null,
"author": "Colton Hicks",
"author_email": "github@coltonhicks.com",
"download_url": "https://files.pythonhosted.org/packages/e7/97/fd86195f927adef3cb5758e3bced8e23546f69d6b452938b49ee0f04fed2/qcparse-0.7.3.tar.gz",
"platform": null,
"description": "# qcparse\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/qcparse)\n[](https://pypi.python.org/pypi/qcparse)\n[](https://pypi.python.org/pypi/qcparse)\n[](https://github.com/coltonbh/qcparse/actions)\n[](https://github.com/coltonbh/qcparse/actions)\n[](https://github.com/charliermarsh/ruff)\n\n`qcparse` 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- [qcio](https://github.com/coltonbh/qcio) - Beautiful and user friendly data structures for quantum chemistry.\n- [qcparse](https://github.com/coltonbh/qcparse) - 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 qcparse\n ```\n\n- Parse a file into a `SinglePointResults` object with a single line of code.\n\n ```python\n from qcparse import parse\n # May pass a path or the contents of a file as string/bytes\n results = parse(\"terachem\", \"/path/to/stdout.log\")\n ```\n\n- The `results` object will be a `qcio.SinglePointResults` object. Run `dir(results)` 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 qcparse import parse\n\n results = parse(\"/path/to/tc.out\", \"terachem\")\n\n results.energy\n results.gradient # If a gradient calc\n results.hessian # If a hessian calc\n\n results.calcinfo_nmo # Number of molecular orbitals\n ```\n\n- Parsed values can be written to disk like this:\n\n ```py\n with open(\"results.json\", \"w\") as f:\n f.write(result.model_dumps_json())\n ```\n\n- And read from disk like this:\n\n ```py\n from qcio import SinglePointResults\n\n results = SinglePointResults.open(\"results.json\")\n ```\n\n- You can also run `qcparse` from the command line like this:\n\n ```sh\n qcparse -h # Get help message for cli\n\n qcparse terachem ./path/to/tc.out > results.json # Parse TeraChem stdout to json\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/qcparse/issues/2).\n\n",
"bugtrack_url": null,
"license": "MIT",
"summary": "A package for parsing Quantum Chemistry program file outputs into structured qcio data objects.",
"version": "0.7.3",
"project_urls": {
"Homepage": "https://github.com/coltonbh/qcparse",
"Repository": "https://github.com/coltonbh/qcparse"
},
"split_keywords": [],
"urls": [
{
"comment_text": null,
"digests": {
"blake2b_256": "dbfa4702c43c7392c9a73420007210fb7a6c9084574b5056eb6b5bb5db5bb569",
"md5": "92ef964c0a0b95e30ddd9817c3628e64",
"sha256": "656555b71c589569803706f1e0b335fcc3df4096fa183e5dc6bd977f24e3c93d"
},
"downloads": -1,
"filename": "qcparse-0.7.3-py3-none-any.whl",
"has_sig": false,
"md5_digest": "92ef964c0a0b95e30ddd9817c3628e64",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": "<4.0,>=3.9",
"size": 18659,
"upload_time": "2025-02-09T01:58:02",
"upload_time_iso_8601": "2025-02-09T01:58:02.771400Z",
"url": "https://files.pythonhosted.org/packages/db/fa/4702c43c7392c9a73420007210fb7a6c9084574b5056eb6b5bb5db5bb569/qcparse-0.7.3-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": null,
"digests": {
"blake2b_256": "e797fd86195f927adef3cb5758e3bced8e23546f69d6b452938b49ee0f04fed2",
"md5": "e2f83e6a1b67a8b98fd50de45739bd3a",
"sha256": "a1143e817a7b45ff6c2dab37f9898dbf5197780b262c5e046968c04b9a6548e9"
},
"downloads": -1,
"filename": "qcparse-0.7.3.tar.gz",
"has_sig": false,
"md5_digest": "e2f83e6a1b67a8b98fd50de45739bd3a",
"packagetype": "sdist",
"python_version": "source",
"requires_python": "<4.0,>=3.9",
"size": 15071,
"upload_time": "2025-02-09T01:58:06",
"upload_time_iso_8601": "2025-02-09T01:58:06.645170Z",
"url": "https://files.pythonhosted.org/packages/e7/97/fd86195f927adef3cb5758e3bced8e23546f69d6b452938b49ee0f04fed2/qcparse-0.7.3.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2025-02-09 01:58:06",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "coltonbh",
"github_project": "qcparse",
"travis_ci": false,
"coveralls": false,
"github_actions": true,
"lcname": "qcparse"
}