Splitting text into sentences is one of those tasks that looks simple but on closer inspection is more difficult than you think. A common approach is to use regular expressions to divide up the text on punction marks. But without adding layers of complexity, that method fails on a sentence such as:

“Trapper John, M.D. was as fine as any Ph.D."

It’s obviously only one sentence, but try it with regex and the difficulty is obvious.

A solution suggested on Stack Overflow is to use the spaCy natural language processing module along with its ‘sentencizer’ pipeline to do the heavy lifting. The recommended solutions are all based on English language processing; so I was anxious to see if it would work on Russian text. The short answer is “yes.” This post is just to document the solution.

from spacy.lang.ru import Russian

nlp_simple = Russian()
nlp_simple.add_pipe('sentencizer')

doc = nlp_simple(text)
sentences = [str(sent).strip() for sent in doc.sents]