Example transformer for tapping into your Pipeline

tap_transformer_sklearn.py

def TapTransformer(TransformerMixin):
    def __init__(self, fn):
        self.fn = fn

    def transform(self, X, **transform_params):
        self.fn(x)
        return X

    def fit(self, X, y=none, **fit_params):
        return self

features = []

def save_features(f)
    features.append(f)

pipeline = Pipeline([
  ('extract_essays', EssayExractor()),
  ('features', FeatureUnion([
    ('ngram_tf_idf', Pipeline([
      ('counts', CountVectorizer()),
      ('tf_idf', TfidfTransformer())
    ])),
    ('essay_length', LengthTransformer()),
    ('misspellings', MispellingCountTransformer())
  ])),
  ('print_features', TapTransformer(lambda X: print(X))),
  ('save_features', TapTransformer(save_features))
  ('classifier', MultinomialNB())
])

Can you provide examples of your LengthTransformer and MispellingCountTransformer?