luisfernandoagottani
/
end-to-end-data-engineer
connected to https://github.com/luisfernandoagottani/end-to-end-data-engineer.git


  
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            from src.mlProject import logger
from src.mlProject.pipeline.stage_01_data_ingestion import DataIngestionTrainingPipeline
from src.mlProject.pipeline.stage_02_data_validation import DataValidationTrainingPipeline
from src.mlProject.pipeline.stage_03_data_transformation import DataTransformationTrainingPipeline
from src.mlProject.pipeline.stage_04_model_trainer import ModelTrainerTrainingPipeline
from src.mlProject.pipeline.stage_05_model_evaluation import ModelEvaluationTrainingPipeline


STAGE_NAME = "Data Ingestion stage"
try:
   logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<") 
   data_ingestion = DataIngestionTrainingPipeline()
   data_ingestion.main()
   logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
        logger.exception(e)
        raise e

STAGE_NAME = "Data Validation stage"
try:
   logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<") 
   data_ingestion = DataValidationTrainingPipeline()
   data_ingestion.main()
   logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
        logger.exception(e)
        raise e

STAGE_NAME = "Data Transformation stage"
try:
   logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<") 
   data_ingestion = DataTransformationTrainingPipeline()
   data_ingestion.main()
   logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
        logger.exception(e)
        raise e

STAGE_NAME = "Model Trainer stage"
try:
   logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<") 
   data_ingestion = ModelTrainerTrainingPipeline()
   data_ingestion.main()
   logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
except Exception as e:
        logger.exception(e)
        raise e

# STAGE_NAME = "Model evaluation stage"
# try:
#    logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<") 
#    data_ingestion = ModelEvaluationTrainingPipeline()
#    data_ingestion.main()
#    logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
# except Exception as e:
#         logger.exception(e)
#         raise e