Apologies, there was a bug in the code I sent in my previous message. The problem is the same. Here is the corrected code in a gist.
https://gist.github.com/PatWalters/ca41289a6990ebf7af1e5c44e188fccd On Mon, Mar 22, 2021 at 8:16 AM Patrick Walters <wpwalt...@gmail.com> wrote: > Hi All, > > I've been trying to calculate BCUT2D descriptors in parallel with Dask and > get this error with the code below. > TypeError: cannot pickle 'Boost.Python.function' object > > Everything works if I call mw_df, which calculates molecular weight, but I > get the error above if I call bcut_df. Does anyone have a workaround? > > Thanks, > > Pat > > #!/usr/bin/env python > > import sys > import dask.dataframe as dd > import pandas as pd > from rdkit import Chem > from rdkit.Chem.Descriptors import MolWt > from rdkit.Chem.rdMolDescriptors import BCUT2D > import time > > # -- molecular weight functions > def calc_mw(smi): > mol = Chem.MolFromSmiles(smi) > return MolWt(mol) > > def mw_df(df): > return df.SMILES.apply(calc_mw) > > # -- bcut functions > def bcut_df(df): > return df.apply(calc_bcut) > > def calc_bcut(smi): > mol = Chem.MolFromSmiles(smi) > return BCUT2D(mol) > > def main(): > start = time.time() > df = pd.read_csv(sys.argv[1],sep=" ",names=["SMILES","Name"]) > ddf = dd.from_pandas(df,npartitions=16) > ddf['MW'] = > ddf.map_partitions(mw_df,meta='float').compute(scheduler='processes') > ddf['BCUT'] = > ddf.map_partitions(bcut_df,meta='float').compute(scheduler='processes') > print(time.time()-start) > print(ddf.head()) > > > if __name__ == "__main__": > main() >
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