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Merge pull request #120 from VikramsDataScience/churn-propensity-model
Restructured codebase to begin development of a local pipeline
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from .src.config import Config
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from pathlib import Path
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# Model version
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__version__ = '0.01'
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# Initialise global variables from config module
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config = Config()
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data_path = Path(config.data_path)
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churn_app_path = Path(config.churn_app_models)
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seed = config.seed
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import argparse
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parser = argparse.ArgumentParser(description='Churn propensity pipeline')
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parser.add_argument('--module', type=str, choices=['eda', 'preprocessing', 'model_training'])
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args = parser.parse_args()
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ECommerce_Churn_Propensity_Model/src/__init__.py

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