RuntimeError when using calc.pandas

[alsalehf]

description

I get stuck in a loop when using pandas.clac and results in runtime error RuntimeError: An attempt has been made to start a new process before the current process has finished its bootstrapping phase

Below is the code im using for testing: minimal reproduction code from rdkit import Chem from mordred import Calculator, descriptors

import pandas as pd

import unicodedata

components = ["CCO"]

def s2d(smiles_list): final_list = [unicodedata.normalize("NFKD", ls) for ls in smiles_list]

mols = [Chem.MolFromSmiles(smi) for smi in final_list]
calc = Calculator(descriptors, ignore_3D=True)
df3 = calc.pandas(mols)
return df3

s2d(components)

df = s2d(components) print(df)

Please fill me if possible.

environment

I'm running the code in a windows 10 machine with a venv environment.

Please fill me.

conda or pip

pip.

python version

Python 3.10.4

library version

Please execute the command and paste result.

• pip

Package Version

---

mordred 1.2.0 networkx 2.8.8 numpy 1.24.2 pandas 1.5.3 Pillow 9.4.0 pip 22.0.4 python-dateutil 2.8.2 pytz 2022.7.1 rdkit 2022.9.5 setuptools 58.1.0 six 1.16.0

pip show rdkit Name: rdkit Version: 2022.9.5 Summary: A collection of chemoinformatics and machine-learning software written in C++ and Python Home-page: https://github.com/kuelumbus/rdkit-pypi Author: Christopher Kuenneth Author-email: chris@kuenneth.dev License: BSD-3-Clause Location: c:\users\admin\chemslenv\lib\site-packages Requires: numpy, Pillow Required-by:

[ismorphism]

@alsalehf Hello! That's very important question, but somehow the developers do not have a time to answer it. The solution is to drop all "bad" descriptors - they do not work for you due to problems with your molecules' stereochemistry or smth else. That's my idea, which it's based on my experience:

from mordred import Calculator, PBF, MomentOfInertia, TopologicalCharge, MolecularDistanceEdge, MoRSE, GravitationalIndex, GeometricalIndex, EState, DistanceMatrix, DetourMatrix, CPSA, BaryszMatrix, Autocorrelation, AdjacencyMatrix, descriptors, get_descriptors_from_module

descs = get_descriptors_from_module(descriptors, submodule=True)

# exclude some from descs
descs = filter(lambda d: ((d.__module__ != AdjacencyMatrix.__name__) and 
                          (d.__module__ != Autocorrelation.__name__) and
                          (d.__module__ != DetourMatrix.__name__) and 
                          (d.__module__ != BaryszMatrix.__name__) and 
                          (d.__module__ != CPSA.__name__) and 
                          (d.__module__ != DistanceMatrix.__name__) and 
                          (d.__module__ != EState.__name__) and 
                          (d.__module__ != GeometricalIndex.__name__) and 
                          (d.__module__ != GravitationalIndex.__name__) and 
                          (d.__module__ != MoRSE.__name__) and 
                          (d.__module__ != MolecularDistanceEdge.__name__) and 
                          (d.__module__ != MomentOfInertia.__name__) and 
                          (d.__module__ != PBF.__name__) and 
                          (d.__module__ != TopologicalCharge.__name__)), descs)

calc = Calculator(descs)
calc.pandas(mols)