Dear all,
I am looking for a way to extract SMILES scattered in many text documents
(thousands documents of several pages each).
At the moment, I am thinking to scan each words from the text and try to
make a mol object from them using Chem.MolFromSmiles() then store the words
if they return a mol object that is not None.
Can anyone think of a better/quicker way?
Would it be worth storing in a tuple any word that do not return a mol
object from Chem.MolFromSmiles() and exclude them from subsequent search?
Something along those lines
excluded_set = set()
smiles_list = []
For each_word in text:
If each_word not in excluded_set:
each_word_mol = Chem.MolFromSmiles(each_word)
if each_word_mol is not None:
smiles_list.append(each_word)
else:
excluded_set.add(each_word_mol)
Would not searching into that growing tuple take actually more time than
trying to blindly make a mol object for every word?
Any suggestion?
Many thanks and regards,
Alexis
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