Wine-Quality-Prediction/main.py

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


if __name__ == '__main__':

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

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

    # third stage
    STAGE_NAME = "Data Tranformation Stage"
    try:
        logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
        obj = DataTransformationTrainingPipeline()
        obj.main()
        logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
    except Exception as e:
        logger.exception(e)
        raise e
    
    # forth stage
    STAGE_NAME = "Data Training Stage"
    try:
        logger.info(f">>>>>> stage {STAGE_NAME} started <<<<<<")
        obj = ModelTrainerTrainingPipeline()
        obj.main()
        logger.info(f">>>>>> stage {STAGE_NAME} completed <<<<<<\n\nx==========x")
    except Exception as e:
        logger.exception(e)
        raise e

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