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main.py
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main.py
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from fetchSearch.logging import logger
logger.info("This Project uses custom logger.\n")
logger.info("#################################\n")
from fetchSearch.pipeline.stage_01_data_ingestion import DataIngestionTrainingPipeline
from fetchSearch.pipeline.stage_02_data_validation import DataValidationTrainingPipeline
from fetchSearch.pipeline.stage_03_data_transformation import DataTransformationTrainingPipeline
from fetchSearch.pipeline.stage_04_model_trainer import ModelTrainerTrainingPipeline
from fetchSearch.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\n################################################")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Data Validation Stage"
try:
logger.info(f"######## Stage {STAGE_NAME} started. ########")
data_validation = DataValidationTrainingPipeline()
data_validation.main()
logger.info(f"######## Stage {STAGE_NAME} completed. ########\n\n################################################")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Data Transformation Stage"
try:
logger.info(f"######## Stage {STAGE_NAME} started. ########")
data_transformation = DataTransformationTrainingPipeline()
data_transformation.main()
logger.info(f"######## Stage {STAGE_NAME} completed. ########\n\n################################################")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Model Trainer stage"
try:
logger.info(f"######## Stage {STAGE_NAME} started. ########")
model_trainer = ModelTrainerTrainingPipeline()
model_trainer.main()
logger.info(f"######## Stage {STAGE_NAME} completed. ########\n\n################################################")
except Exception as e:
logger.exception(e)
raise e
STAGE_NAME = "Model Evaluation stage"
try:
logger.info(f"######## Stage {STAGE_NAME} started. ########")
model_evaluation = ModelEvaluationTrainingPipeline()
model_evaluation.main()
logger.info(f"######## Stage {STAGE_NAME} completed. ########\n\n################################################")
except Exception as e:
logger.exception(e)
raise e