code: def test_fit_and_predict(model, df):
      # generate fake predictions
      with open(model.prediction_file, "w") as f:
          f.writelines(["1 0\n", "3 1\n", "5 2\n"])
  
      # patch subprocess call to vw
      with mock.patch(
          "recommenders.models.vowpal_wabbit.vw.run"
      ) as mock_run:  # noqa: F841
          model.fit(df)
          result = model.predict(df)
  
      expected = dict(
          user=dict(enumerate([1, 3, 2])),
          item=dict(enumerate([8, 7, 7])),
          rating=dict(enumerate([1, 5, 3])),
          timestamp=dict(enumerate([1, 2, 3])),
          prediction=dict(enumerate([1, 3, 5])),
      )
  
      assert result.to_dict() == expected
  
file_path: recommenders/tests/unit/recommenders/models/test_vowpal_wabbit.py
imports: import os
  import pytest
  from unittest import mock
  import pandas
  from recommenders.models.vowpal_wabbit.vw import VW
label_desc: Use image node_id 8 for calling a global function with example usage: test_fit_and_predict(model, df) without return types