code: def test_plaintext_functionality(text):
      preprocessed_text = preprocessing.normalize.whitespace(text)
      preprocessed_text = preprocessing.remove.punctuation(text)
      preprocessed_text = preprocessed_text.lower()
      assert all(
          char.islower() for char in preprocessed_text if char.isalpha()
      )
      assert all(
          char.isalnum() or char.isspace() for char in preprocessed_text
      )
      keyword = "America"
      kwics = extract.keyword_in_context(text, keyword, window_width=35)
      for pre, kw, post in kwics:
          assert kw == keyword
          assert isinstance(pre, str)
          assert isinstance(post, str)
  
imports: import numpy
  import pytest
  import scipy.sparse
  from spacy.tokens import Doc, Span
  import textacy.datasets
  from textacy import Corpus
  from textacy import extract, preprocessing
  from textacy import load_spacy_lang, make_spacy_doc
  from textacy.extract import keyterms
  from textacy.text_stats import TextStats
  from textacy.tm import TopicModel
  from textacy.representations import Vectorizer
label_desc: Use image node_id 7 for calling a global function with example usage: test_plaintext_functionality(text) without return types