Metadata-Version: 2.1
Name: ugropy
Version: 2.0.5
Summary: Get UNIFAC functional groups of PubChem compounds or SMILES representation.
Author-email: "Brandolín, Salvador Eduardo" <salvadorebrandolin@mi.unc.edu.ar>
License: The MIT License
Project-URL: Homepage, https://github.com/ipqa-research/ugropy
Keywords: UNIFAC,functional group,thermodynamics,chemical engineering
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.10
Classifier: Topic :: Scientific/Engineering
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: numpy>=1.25.1
Requires-Dist: pandas>=2.0.3
Requires-Dist: pubchempy==1.0.4
Requires-Dist: rdkit==2023.9.5

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`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
```
