How do I limit the number of CPUs used by Spacy?

Question

How do I limit the number of CPUs used by Spacy?

I want to extract parts-of-speech and named entities from a large set of sentences. Because of limitations regarding RAM, I first use the Python NLTK to parse my documents into sentences. I then iterate over my sentences and use nlp.pipe() to do the extractions. However, when I do this, Spacy consumes the whole of my computer; Spacy uses every available CPU. Such is not nice because my computer is shared. How can I limit the number of CPUs used by Spacy? Here is my code to date:

# require
from nltk import *
import spacy

# initialize
file = './walden.txt'
nlp  = spacy.load( 'en' )

# slurp up the given file
handle = open( file, 'r' )
text   = handle.read()

# parse the text into sentences, and process each one
sentences = sent_tokenize( text )
for sentence in nlp.pipe( sentences, n_threads=1 ) :

  # process each token
  for token in sentence : print( "\t".join( [ token.text, token.lemma_, token.tag_ ] ) )

# done
quit()

Answer 1

My answer to my own question is, "Call the operating system and employ a Linux utility named taskset."

# limit ourselves is a few processors only
os.system( "taskset -pc 0-1 %d > /dev/null" % os.getpid() )

This particular solution limits the running process to cores #1 and #2. This solution is good enough for me.