content: import pytest
  import numpy as np
  
  from spacy.vocab import Vocab
  from spacy.language import Language
  from whatlies.language import SpacyLanguage
  
  
  @pytest.fixture()
  def color_lang():
      vector_data = {
          "red": np.array([1.0, 0.0]),
          "green": np.array([0.5, 0.5]),
          "blue": np.array([0.0, 1.0]),
          "purple": np.array([0.0, 1.0]),
      }
  
      vocab = Vocab(strings=list(vector_data.keys()))
      for word, vector in vector_data.items():
          vocab.set_vector(word, vector)
      nlp = Language(vocab=vocab)
      return SpacyLanguage(nlp)
  
  
  def test_basic_usage(color_lang):
      queries = [
          "green is blue and yellow",
          "purple is red and blue",
          "purple isn't same as red!",
          "red and blue is a like a glue!",
      ]
      emb = color_lang[queries]
      assert len(emb) == 4
      assert emb[queries[0]].name == "green is blue and yellow"
      assert emb[queries[0]].vector.shape == (2,)
  
  
  def test_score_similar_one(color_lang):
      scores = color_lang.score_similar("blue", n=2, prob_limit=None, lower=False)
      print(scores)
      assert all([s[1] == 0 for s in scores])
      assert "blue" in [s[0].name for s in scores]
      assert "purple" in [s[0].name for s in scores]
  
  
  def test_single_token_words(color_lang):
      # test for issue here: https://github.com/RasaHQ/whatlies/issues/5
      assert len(color_lang["red"].vector) > 0
  