Chrfinder 1.0.1

The package find the best chromatography based on properties of the mixture

Chrfinder

Project overview

Welcome to Chrfinder! This project automates the selection of the most suitable chromatography technique . By simply providing the names of the molecules in the mixture, the code retrieves their physicochemical properties from PubChem (web source) and determines the optimal chromatography method based on these properties. It also gives the optimal conditions.

✅ Benefits

• 🚀 Efficiency: Automates the property retrieval and decision-making process, saving time and reducing manual effort.
• 🎯 Accuracy: Utilizes precise physicochemical data to ensure the most suitable chromatography technique is chosen.
• 🌐 Versatility: Supports a wide range of organic compounds and chromatography methods (PubChem database).

⚙ Installation

To get started with Chrfinder, you can follow these steps: Create a new environment, you may also give the environment a different name.

conda create -n Chrfinder python=3.10 

Then install it through pypi (easy, recommended):

conda activate Chrfinder

pip install Chrfinder

You also have the choice to install it without pypi:

git clone https://github.com/Averhv/Chrfinder.git
cd Chrfinder
pip install .

🛠️ Installation for Development

If you want to contribute to Chrfinder or run the tests and get coverage, you can install the package in editable mode along with the necessary dependencies for testing and documentation. The following script allows the changes to be reflected immediately:

git clone https://github.com/Averhv/Chrfinder.git
cd Chrfinder
pip install -e ".[test,doc]"

Then you need to run the tests as follow in your terminal:

pip install tox
tox

Test result: 15 passed in ~20s

📒 Features

The following should be written in the terminal in python mode:

from Chrfinder import main

Running the main file asks for molecules through Tkinter and returns the best chromatography.

main()

🌐 Optional functions

• find_pka(inchikey) Finds the pKa value for a compound using its InChIKey.

from Chrfinder import find_pka

inchikey = "XEFQLINVKFYRCS-UHFFFAOYSA-N"
find_pka(inchikey)

• find_boiling_point(name) Finds the boiling point for a compound by name.

from Chrfinder import find_boiling_point

compound_name = "Ethanol"
find_boiling_point(compound_name)

• get_df_properties() Get a DataFrame of properties for a mixture of compounds.

from Chrfinder import get_df_properties

mixture = ["Acetone", "Ethanol", "Methanol"]
get_df_properties(mixture, verbose=True)

Work in progress...

• Efficiency: build a database;
• Research thermostability in lab to improve precision
• Taking into account multiple pKa values for polyacids for exemple;
• Optimize the research: search only one time the same name;

🫱🏽‍🫲🏼 Contributing

Contributions are welcome! Please submit a pull request or open an issue to discuss any changes.