code: def prec1(eval_data, predictions, scores='ignored', learner='ignored'):
      '''
      Return the precision@1 of each prediction in `predictions`: 1 if it is equal
      to any of the correct outputs for the corresponding instance in `eval_data`,
      0 otherwise.
  
      >>> data = [Instance('input', ['correct', 'right']),
      ...         Instance('input', ['correct', 'right']),
      ...         Instance('input', ['correct', 'right'])]
      >>> prec1(data, ['correct', 'wrong', 'right'])
      [1, 0, 1]
      '''
      return [int(any(o == pred for o in inst.output))
              for inst, pred in zip(eval_data, predictions)f prec1(eval_data, predictions, scores='ignored', learner='ignored'):
      '''
      Return the precision@1 of each prediction in `predictions`: 1 if it is equal
      to any of the correct outputs for the corresponding instance in `eval_data`,
      0 otherwise.
  
      >>> data = [Instance('input', ['correct', 'right']),
      ...         Instance('input', ['correct', 'right']),
      ...         Instance('input', ['correct', 'right'])]
      >>> prec1(data, ['correct', 'wrong', 'right'])
      [1, 0, 1]
      '''
      return [int(any(o == pred for o in inst.output))
              for inst, pred in zip(eval_data, predictions)]
docs: Return the precision@1 of each prediction in `predictions`: 1 if it is equal
      to any of the correct outputs for the corresponding instance in `eval_data`,
      0 otherwise.
  
      >>> data = [Instance('input', ['correct', 'right']),
      ...         Instance('input', ['correct', 'right']),
      ...         Instance('input', ['correct', 'right'])]
      >>> prec1(data, ['correct', 'wrong', 'right'])
      [1, 0, 1]