refactoring and demand estimation

experiments/procesing/pipeline.py

@@ -1,20 +1,22 @@
 from sklearn.pipeline import Pipeline
 from sklearn.preprocessing import StandardScaler
 
-from extract import DataExtractor
+from extract import KafkaDataFetcher, ExperimentJoiner, EventTitleAugmenter
 from mapping import SessionTransitionProbMatrixTransformer, render_graph
 from demand import DemandEstimator
 
 
 # exposable pipelines
 etl_pipeline = Pipeline([
-    ('data_extraction', DataExtractor()),
+    ('kafka_fetch', KafkaDataFetcher()),
+    ('experiment_join', ExperimentJoiner()),
+    ('event_augment', EventTitleAugmenter()),
 ])
 pricing_pipeline = Pipeline([
     ('demand_estimation', DemandEstimator()),
-    ('scaling', StandardScaler()),
 ])
 
 if __name__ == "__main__":
     processed_data = etl_pipeline.fit_transform(None)
     pricing = pricing_pipeline.fit_transform(processed_data)
+    print(pricing)