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23 lines
698 B
Python
23 lines
698 B
Python
from sklearn.pipeline import Pipeline
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from sklearn.preprocessing import StandardScaler
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from extract import KafkaDataFetcher, ExperimentJoiner, EventTitleAugmenter
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from mapping import SessionTransitionProbMatrixTransformer, render_graph
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from demand import DemandEstimator
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# exposable pipelines
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etl_pipeline = Pipeline([
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('kafka_fetch', KafkaDataFetcher()),
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('experiment_join', ExperimentJoiner()),
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('event_augment', EventTitleAugmenter()),
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])
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pricing_pipeline = Pipeline([
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('demand_estimation', DemandEstimator()),
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])
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if __name__ == "__main__":
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processed_data = etl_pipeline.fit_transform(None)
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pricing = pricing_pipeline.fit_transform(processed_data)
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print(pricing)
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