[](https://mybinder.org/v2/gh/ipqa-research/ugropy/main)
[](https://tldrlegal.com/license/mit-license)
[](https://salvadorbrandolin.github.io/ugropy/)
[](https://badge.fury.io/py/ugropy)
`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 from its
[Binder](https://mybinder.org/v2/gh/ipqa-research/ugropy/main). Open the
binder.ipynb file to explore the basic features.
## Models supported v2.0.5
- Classic liquid-vapor UNIFAC
- Predictive Soave-Redlich-Kwong (PSRK)
- Joback
## 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](github.com/ClapeyronThermo/Clapeyron.jl)
- [Thermo](https://github.com/CalebBell/thermo)
## Example of use
You can check the full tutorial
[here](https://ipqa-research.github.io/ugropy/tutorial/tutorial.html).
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)
```
{'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)
```
{'CH3': 1, 'CH2': 2, 'OH': 1}
{'CH3': 1, 'CH2': 2, 'OH': 1}
{'-CH3': 1, '-CH2-': 2, '-OH (alcohol)': 1}
Estimate properties with the Joback model!
```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 K
1.0254019428522743 bar
Visualize your results! (The next code creates the `ugropy` logo)
```Python
from IPython.display import SVG
mol = Groups("CCCC1=C(COC(C)(C)COC(=O)OCC)C=C(CC2=CC=CC=C2)C=C1", "smiles")
svg = mol.unifac.draw(
title="ugropy",
width=800,
height=450,
title_font_size=50,
legend_font_size=14
)
SVG(svg)
```
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", "2-butanone"]
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, 18: 1}]
```
## Installation
```
pip install ugropy
```
Raw data
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"description": "\n\n[](https://mybinder.org/v2/gh/ipqa-research/ugropy/main)\n[](https://tldrlegal.com/license/mit-license)\n\n[](https://salvadorbrandolin.github.io/ugropy/)\n[](https://badge.fury.io/py/ugropy)\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 from its\n[Binder](https://mybinder.org/v2/gh/ipqa-research/ugropy/main). Open the\nbinder.ipynb file to explore the basic features.\n\n## Models supported v2.0.5\n- Classic liquid-vapor UNIFAC\n- Predictive Soave-Redlich-Kwong (PSRK)\n- Joback\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](github.com/ClapeyronThermo/Clapeyron.jl)\n- [Thermo](https://github.com/CalebBell/thermo)\n\n\n## Example of use\nYou can check the full tutorial\n[here](https://ipqa-research.github.io/ugropy/tutorial/tutorial.html).\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)\n```\n\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)\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\nEstimate properties with the Joback model!\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 K\n 1.0254019428522743 bar\n\nVisualize your results! (The next code creates the `ugropy` logo)\n\n```Python\nfrom IPython.display import SVG\n\nmol = Groups(\"CCCC1=C(COC(C)(C)COC(=O)OCC)C=C(CC2=CC=CC=C2)C=C1\", \"smiles\")\n\nsvg = mol.unifac.draw(\n title=\"ugropy\",\n width=800,\n height=450,\n title_font_size=50,\n legend_font_size=14\n)\n\nSVG(svg)\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\", \"2-butanone\"]\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, 18: 1}]\n```\n\n## Installation\n```\npip install ugropy\n```\n",
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