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6 catalog data and mode mappers (#25)

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* supabase product proxy and rendering

* minor pipeline refactor

* refactoring and demand estimation

* trackion of date index searching

* fixing changes of imports

* data seeding

* chore: airline basic refactor

* feat: huge push of product changes and item review with cart

* refactored design

* chore: moving route elsewhere and align

* fix: build of web/

* chore: fixing paper build

* fixing chars
This commit is contained in:
Daniel Alves Rösel
2025-11-25 11:00:31 +01:00
committed by GitHub
parent 894ce87a5d
commit 8b76d24ade
29 changed files with 1390 additions and 1237 deletions
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27
experiments/procesing/pipeline.py
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@@ -1,15 +1,22 @@
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler
from extract import DataExtractor
from mapping import SessionTransitionProbMatrixTransformer, render_graph
from extract import KafkaDataFetcher, ExperimentJoiner, EventTitleAugmenter
from mapping import SessionTransitionProbMatrixTransformer, render_graph
from demand import DemandEstimator
# exposable pipelines
etl_pipeline = Pipeline([
('kafka_fetch', KafkaDataFetcher()),
('experiment_join', ExperimentJoiner()),
('event_augment', EventTitleAugmenter()),
])
pricing_pipeline = Pipeline([
('demand_estimation', DemandEstimator()),
])
if __name__ == "__main__":
steps = [
('data_extraction', DataExtractor()),
#('transition_matrix', SessionTransitionProbMatrixTransformer(threshold=0.05)),
]
pipeline = Pipeline(steps)
result = pipeline.fit_transform(None)
print(result)
print(result.info())
processed_data = etl_pipeline.fit_transform(None)
pricing = pricing_pipeline.fit_transform(processed_data)
print(pricing)