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import os
import sys
from src.exception import CustomException
from src.logger import logging
import pandas as pd
from sklearn.model_selection import train_test_split
from dataclasses import dataclass
from src.components.data_transformation import DataTransformation
from src.components.data_transformation import DataTransformationConfig
from src.components.model_trainer import ModelTrainer
from src.components.model_trainer import ModelTrainerConfig
@dataclass
class DataIngestionConfig:
raw_data_path: str = os.path.join("artifacts", "data.csv")
train_data_path: str = os.path.join("artifacts", "train.csv")
test_data_path: str = os.path.join("artifacts", "test.csv")
class DataIngestion:
def __init__(self) -> None:
self.ingestion_config = DataIngestionConfig()
def initiate_data_ingestion(self):
logging.info("Entered data ingestion medthod or component")
try:
df = pd.read_csv("notebook/data/stud.csv")
logging.info("Read the dataset as dataframe")
os.makedirs(
os.path.dirname(self.ingestion_config.train_data_path), exist_ok=True
)
df.to_csv(self.ingestion_config.raw_data_path, index=False, header=True)
logging.info("Train test split initiated")
train_set, test_set = train_test_split(df, test_size=0.2, random_state=42)
train_set.to_csv(
self.ingestion_config.train_data_path, index=False, header=True
)
test_set.to_csv(
self.ingestion_config.test_data_path, index=False, header=True
)
logging.info("Ingestion of the data is completed")
return (
self.ingestion_config.train_data_path,
self.ingestion_config.test_data_path,
)
except Exception as e:
raise CustomException(e, sys)
if __name__ == "__main__":
obj = DataIngestion()
train_data, test_data = obj.initiate_data_ingestion()
data_transformation = DataTransformation()
train_arr, test_arr, _ = data_transformation.initiate_data_transformation(
train_data, test_data
)
model_trainer = ModelTrainer()
print(model_trainer.initiate_model_trainer(train_arr, test_arr))
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