ugropy


Nameugropy JSON
Version 3.0.0 PyPI version JSON
download
home_pageNone
SummaryGet UNIFAC functional groups of PubChem compounds or SMILES representation.
upload_time2025-02-20 17:41:53
maintainerNone
docs_urlNone
authorNone
requires_pythonNone
licenseMIT
keywords unifac functional group thermodynamics chemical engineering
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            ![logo](logo.png)

[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ipqa-research/ugropy/blob/main/docs/source/tutorial/easy_way.ipynb)
[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://tldrlegal.com/license/mit-license)
![Python 3.10+](https://img.shields.io/badge/Python-3.10%2B-blue)
[![Docs](https://img.shields.io/badge/docs%20-%20green?style=flat&label=Sphinx&link=https%3A%2F%2Fipqa-research.github.io%2Fugropy%2Findex.html)](https://salvadorbrandolin.github.io/ugropy/)
[![PyPI
version](https://badge.fury.io/py/ugropy.svg)](https://badge.fury.io/py/ugropy)
[![Powered by RDKit](https://img.shields.io/badge/Powered%20by-RDKit-3838ff.svg?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQBAMAAADt3eJSAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAAFVBMVEXc3NwUFP8UPP9kZP+MjP+0tP////9ZXZotAAAAAXRSTlMAQObYZgAAAAFiS0dEBmFmuH0AAAAHdElNRQfmAwsPGi+MyC9RAAAAQElEQVQI12NgQABGQUEBMENISUkRLKBsbGwEEhIyBgJFsICLC0iIUdnExcUZwnANQWfApKCK4doRBsKtQFgKAQC5Ww1JEHSEkAAAACV0RVh0ZGF0ZTpjcmVhdGUAMjAyMi0wMy0xMVQxNToyNjo0NyswMDowMDzr2J4AAAAldEVYdGRhdGU6bW9kaWZ5ADIwMjItMDMtMTFUMTU6MjY6NDcrMDA6MDBNtmAiAAAAAElFTkSuQmCC)](https://www.rdkit.org/)
    

`ugropy` is a `Python` library to obtain subgroups from different thermodynamic
group contribution models using both the name or the SMILES representation of a
molecule. If the name is given, the library uses the
[PubChemPy](https://github.com/mcs07/PubChemPy) library to obtain the SMILES
representation from PubChem. In both cases, `ugropy` uses the
[RDKit](https://github.com/rdkit/rdkit) library to search the functional groups
in the molecule.

`ugropy` is in an early development stage, leaving issues of examples of
molecules that `ugropy` fails solving the subgroups of a model is very helpful.

`ugropy` is tested for `Python` 3.10, 3.11 and 3.12 on Linux, Windows and Mac
OS.

# Try ugropy now
You can try `ugropy` without installing it by clicking on the Colab badge.

# Models implemented

## Gibbs / EoS models
- Classic liquid-vapor UNIFAC
- Predictive Soave-Redlich-Kwong (PSRK)

## Property estimators
- Joback
- Abdulelah-Gani (beta)

# Writers
`ugropy` allows you to convert the obtained functional groups or estimated
properties to the input format required by the following thermodynamic
libraries:

- [Clapeyron.jl](https://github.com/ClapeyronThermo/Clapeyron.jl)
- [Thermo](https://github.com/CalebBell/thermo)


# Example of use
Here is a little taste of `ugropy`, please, check the full tutorial
[here](https://ipqa-research.github.io/ugropy/tutorial/tutorial.html) to see
all it has to offer!

Get groups from the molecule's name:


```python
from ugropy import Groups


hexane = Groups("hexane")

print(hexane.unifac.subgroups)
print(hexane.psrk.subgroups)
print(hexane.joback.subgroups)
print(hexane.agani.primary.subgroups)
```

    {'CH3': 2, 'CH2': 4}
    {'CH3': 2, 'CH2': 4}
    {'-CH3': 2, '-CH2-': 4}
    {'CH3': 2, 'CH2': 4}

Get groups from molecule's SMILES:

```python
propanol = Groups("CCCO", "smiles")

print(propanol.unifac.subgroups)
print(propanol.psrk.subgroups)
print(propanol.joback.subgroups)
print(propanol.agani.primary.subgroups)
```

    {'CH3': 1, 'CH2': 2, 'OH': 1}
    {'CH3': 1, 'CH2': 2, 'OH': 1}
    {'-CH3': 1, '-CH2-': 2, '-OH (alcohol)': 1}
    {'CH3': 1, 'CH2': 2, 'OH': 1}

Estimate properties with the Joback and Abdulelah-Gani models!

```python
limonene = Groups("limonene")

print(limonene.joback.subgroups)
print(f"{limonene.joback.critical_temperature} K")
print(f"{limonene.joback.vapor_pressure(176 + 273.15)} bar")
```

    {'-CH3': 2, '=CH2': 1, '=C<': 1, 'ring-CH2-': 3, 'ring>CH-': 1, 'ring=CH-': 1, 'ring=C<': 1}
    657.4486692170663 kelvin
    1.0254019428522743 bar

```python
print(limonene.agani.primary.subgroups)
print(limonene.agani.secondary.subgroups)
print(limonene.agani.tertiary.subgroups)
print(f"{limonene.agani.critical_temperature}")
print(limonene.agani.molecular_weight / limonene.agani.liquid_molar_volume)
```

    {'CH3': 2, 'CH2=C': 1, 'CH2 (cyclic)': 3, 'CH (cyclic)': 1, 'CH=C (cyclic)': 1}
    {'CH3-CHm=CHn (m,n in 0..2)': 1, '(CHn=C)cyc-CH3 (n in 0..2)': 1, 'CHcyc-C=CHn (n in 1..2)': 1}
    {}
    640.1457030826214 kelvin
    834.8700605718585 gram / liter

Visualize your results! (The next code creates the `ugropy` logo)

```Python
mol = Groups("CCCC1=C(COC(C)(C)COC(=O)OCC)C=C(CC2=CC=CC=C2)C=C1", "smiles")

mol.unifac.draw(
    title="ugropy",
    width=800,
    height=450,
    title_font_size=50,
    legend_font_size=14
)
```

Write down the [Clapeyron.jl](https://github.com/ClapeyronThermo/Clapeyron.jl)
.csv input files.

```python
from ugropy import writers

names = ["limonene", "adrenaline", "Trinitrotoluene"]

grps = [Groups(n) for n in names]

# Write the csv files into a database directory
writers.to_clapeyron(
    molecules_names=names,
    unifac_groups=[g.unifac.subgroups for g in grps],
    psrk_groups=[g.psrk.subgroups for g in grps],
    joback_objects=[g.joback for g in grps],
    path="database"
)
```
Obtain the [Caleb Bell's Thermo](https://github.com/CalebBell/thermo) subgroups

```python
from ugropy import unifac

names = ["hexane", "ethanol"]

grps = [Groups(n) for n in names]

[writers.to_thermo(g.unifac.subgroups, unifac) for g in grps]
```

```
[{1: 2, 2: 4}, {1: 1, 2: 1, 14: 1}]
```

## Installation
```
pip install ugropy
```

            

Raw data

            {
    "_id": null,
    "home_page": null,
    "name": "ugropy",
    "maintainer": null,
    "docs_url": null,
    "requires_python": null,
    "maintainer_email": null,
    "keywords": "UNIFAC, functional group, thermodynamics, chemical engineering",
    "author": null,
    "author_email": "\"Brandol\u00edn, Salvador Eduardo\" <salvadorebrandolin@mi.unc.edu.ar>",
    "download_url": "https://files.pythonhosted.org/packages/d0/d6/1fddc77298f08ad0972045164288988a42fc76092c850c9a2af9836ce971/ugropy-3.0.0.tar.gz",
    "platform": null,
    "description": "![logo](logo.png)\n\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/ipqa-research/ugropy/blob/main/docs/source/tutorial/easy_way.ipynb)\n[![License](https://img.shields.io/badge/License-MIT-blue.svg)](https://tldrlegal.com/license/mit-license)\n![Python 3.10+](https://img.shields.io/badge/Python-3.10%2B-blue)\n[![Docs](https://img.shields.io/badge/docs%20-%20green?style=flat&label=Sphinx&link=https%3A%2F%2Fipqa-research.github.io%2Fugropy%2Findex.html)](https://salvadorbrandolin.github.io/ugropy/)\n[![PyPI\nversion](https://badge.fury.io/py/ugropy.svg)](https://badge.fury.io/py/ugropy)\n[![Powered by RDKit](https://img.shields.io/badge/Powered%20by-RDKit-3838ff.svg?logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQBAMAAADt3eJSAAAABGdBTUEAALGPC/xhBQAAACBjSFJNAAB6JgAAgIQAAPoAAACA6AAAdTAAAOpgAAA6mAAAF3CculE8AAAAFVBMVEXc3NwUFP8UPP9kZP+MjP+0tP////9ZXZotAAAAAXRSTlMAQObYZgAAAAFiS0dEBmFmuH0AAAAHdElNRQfmAwsPGi+MyC9RAAAAQElEQVQI12NgQABGQUEBMENISUkRLKBsbGwEEhIyBgJFsICLC0iIUdnExcUZwnANQWfApKCK4doRBsKtQFgKAQC5Ww1JEHSEkAAAACV0RVh0ZGF0ZTpjcmVhdGUAMjAyMi0wMy0xMVQxNToyNjo0NyswMDowMDzr2J4AAAAldEVYdGRhdGU6bW9kaWZ5ADIwMjItMDMtMTFUMTU6MjY6NDcrMDA6MDBNtmAiAAAAAElFTkSuQmCC)](https://www.rdkit.org/)\n    \n\n`ugropy` is a `Python` library to obtain subgroups from different thermodynamic\ngroup contribution models using both the name or the SMILES representation of a\nmolecule. If the name is given, the library uses the\n[PubChemPy](https://github.com/mcs07/PubChemPy) library to obtain the SMILES\nrepresentation from PubChem. In both cases, `ugropy` uses the\n[RDKit](https://github.com/rdkit/rdkit) library to search the functional groups\nin the molecule.\n\n`ugropy` is in an early development stage, leaving issues of examples of\nmolecules that `ugropy` fails solving the subgroups of a model is very helpful.\n\n`ugropy` is tested for `Python` 3.10, 3.11 and 3.12 on Linux, Windows and Mac\nOS.\n\n# Try ugropy now\nYou can try `ugropy` without installing it by clicking on the Colab badge.\n\n# Models implemented\n\n## Gibbs / EoS models\n- Classic liquid-vapor UNIFAC\n- Predictive Soave-Redlich-Kwong (PSRK)\n\n## Property estimators\n- Joback\n- Abdulelah-Gani (beta)\n\n# Writers\n`ugropy` allows you to convert the obtained functional groups or estimated\nproperties to the input format required by the following thermodynamic\nlibraries:\n\n- [Clapeyron.jl](https://github.com/ClapeyronThermo/Clapeyron.jl)\n- [Thermo](https://github.com/CalebBell/thermo)\n\n\n# Example of use\nHere is a little taste of `ugropy`, please, check the full tutorial\n[here](https://ipqa-research.github.io/ugropy/tutorial/tutorial.html) to see\nall it has to offer!\n\nGet groups from the molecule's name:\n\n\n```python\nfrom ugropy import Groups\n\n\nhexane = Groups(\"hexane\")\n\nprint(hexane.unifac.subgroups)\nprint(hexane.psrk.subgroups)\nprint(hexane.joback.subgroups)\nprint(hexane.agani.primary.subgroups)\n```\n\n    {'CH3': 2, 'CH2': 4}\n    {'CH3': 2, 'CH2': 4}\n    {'-CH3': 2, '-CH2-': 4}\n    {'CH3': 2, 'CH2': 4}\n\nGet groups from molecule's SMILES:\n\n```python\npropanol = Groups(\"CCCO\", \"smiles\")\n\nprint(propanol.unifac.subgroups)\nprint(propanol.psrk.subgroups)\nprint(propanol.joback.subgroups)\nprint(propanol.agani.primary.subgroups)\n```\n\n    {'CH3': 1, 'CH2': 2, 'OH': 1}\n    {'CH3': 1, 'CH2': 2, 'OH': 1}\n    {'-CH3': 1, '-CH2-': 2, '-OH (alcohol)': 1}\n    {'CH3': 1, 'CH2': 2, 'OH': 1}\n\nEstimate properties with the Joback and Abdulelah-Gani models!\n\n```python\nlimonene = Groups(\"limonene\")\n\nprint(limonene.joback.subgroups)\nprint(f\"{limonene.joback.critical_temperature} K\")\nprint(f\"{limonene.joback.vapor_pressure(176 + 273.15)} bar\")\n```\n\n    {'-CH3': 2, '=CH2': 1, '=C<': 1, 'ring-CH2-': 3, 'ring>CH-': 1, 'ring=CH-': 1, 'ring=C<': 1}\n    657.4486692170663 kelvin\n    1.0254019428522743 bar\n\n```python\nprint(limonene.agani.primary.subgroups)\nprint(limonene.agani.secondary.subgroups)\nprint(limonene.agani.tertiary.subgroups)\nprint(f\"{limonene.agani.critical_temperature}\")\nprint(limonene.agani.molecular_weight / limonene.agani.liquid_molar_volume)\n```\n\n    {'CH3': 2, 'CH2=C': 1, 'CH2 (cyclic)': 3, 'CH (cyclic)': 1, 'CH=C (cyclic)': 1}\n    {'CH3-CHm=CHn (m,n in 0..2)': 1, '(CHn=C)cyc-CH3 (n in 0..2)': 1, 'CHcyc-C=CHn (n in 1..2)': 1}\n    {}\n    640.1457030826214 kelvin\n    834.8700605718585 gram / liter\n\nVisualize your results! (The next code creates the `ugropy` logo)\n\n```Python\nmol = Groups(\"CCCC1=C(COC(C)(C)COC(=O)OCC)C=C(CC2=CC=CC=C2)C=C1\", \"smiles\")\n\nmol.unifac.draw(\n    title=\"ugropy\",\n    width=800,\n    height=450,\n    title_font_size=50,\n    legend_font_size=14\n)\n```\n\nWrite down the [Clapeyron.jl](https://github.com/ClapeyronThermo/Clapeyron.jl)\n.csv input files.\n\n```python\nfrom ugropy import writers\n\nnames = [\"limonene\", \"adrenaline\", \"Trinitrotoluene\"]\n\ngrps = [Groups(n) for n in names]\n\n# Write the csv files into a database directory\nwriters.to_clapeyron(\n    molecules_names=names,\n    unifac_groups=[g.unifac.subgroups for g in grps],\n    psrk_groups=[g.psrk.subgroups for g in grps],\n    joback_objects=[g.joback for g in grps],\n    path=\"database\"\n)\n```\nObtain the [Caleb Bell's Thermo](https://github.com/CalebBell/thermo) subgroups\n\n```python\nfrom ugropy import unifac\n\nnames = [\"hexane\", \"ethanol\"]\n\ngrps = [Groups(n) for n in names]\n\n[writers.to_thermo(g.unifac.subgroups, unifac) for g in grps]\n```\n\n```\n[{1: 2, 2: 4}, {1: 1, 2: 1, 14: 1}]\n```\n\n## Installation\n```\npip install ugropy\n```\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "Get UNIFAC functional groups of PubChem compounds or SMILES representation.",
    "version": "3.0.0",
    "project_urls": {
        "Homepage": "https://github.com/ipqa-research/ugropy"
    },
    "split_keywords": [
        "unifac",
        " functional group",
        " thermodynamics",
        " chemical engineering"
    ],
    "urls": [
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "d6c9a21ada0a253adc000084016e8e319aa97ca397fc6d5e5f6e56586e8f46a3",
                "md5": "33f8c3777bf4d3330c9cfd2769252420",
                "sha256": "64abf1d7b58498bbb6bc4941ec44fd0cb8f20452dcd23a041bd754c0d5dcbccb"
            },
            "downloads": -1,
            "filename": "ugropy-3.0.0-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "33f8c3777bf4d3330c9cfd2769252420",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 111716,
            "upload_time": "2025-02-20T17:41:51",
            "upload_time_iso_8601": "2025-02-20T17:41:51.708498Z",
            "url": "https://files.pythonhosted.org/packages/d6/c9/a21ada0a253adc000084016e8e319aa97ca397fc6d5e5f6e56586e8f46a3/ugropy-3.0.0-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": null,
            "digests": {
                "blake2b_256": "d0d61fddc77298f08ad0972045164288988a42fc76092c850c9a2af9836ce971",
                "md5": "e2c00f61552b1f0794b7b1c28782c62d",
                "sha256": "47857eb54111395fab375102e4481b2d05fafcc7c5e7179eb513374df9e6f067"
            },
            "downloads": -1,
            "filename": "ugropy-3.0.0.tar.gz",
            "has_sig": false,
            "md5_digest": "e2c00f61552b1f0794b7b1c28782c62d",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 94052,
            "upload_time": "2025-02-20T17:41:53",
            "upload_time_iso_8601": "2025-02-20T17:41:53.604234Z",
            "url": "https://files.pythonhosted.org/packages/d0/d6/1fddc77298f08ad0972045164288988a42fc76092c850c9a2af9836ce971/ugropy-3.0.0.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2025-02-20 17:41:53",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "ipqa-research",
    "github_project": "ugropy",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": true,
    "tox": true,
    "lcname": "ugropy"
}
        
Elapsed time: 9.36391s