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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 data_transformation import Data_transformation
from model_tranier import Model_training_config,Model_trainer
@dataclass
class Data_ingestion_config:
train_data_path: str = os.path.join("artifact","train.csv")
test_data_path: str = os.path.join("artifact","test.csv")
raw_data_path: str = os.path.join("artifact","raw.csv")
class Data_ingestion:
def __init__(self):
self.ingestion_config = Data_ingestion_config()
def intiate_data_ingestion(self):
logging.info("Entered the data ingestation method or component")
try:
NAMES = []
df = pd.read_csv(filepath_or_buffer="data.csv")
logging.info("Read the dataset as dataframe")
df = df.c
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 intiated")
train_set,test_set = train_test_split(df,test_size=0.2,random_state= 1)
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 data is done")
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 = Data_ingestion()
train_data,test_data = obj.intiate_data_ingestion()
data_trans = Data_transformation()
train_arr,test_arr,_ = data_trans.initiate_data_transformation(train_data,test_data)
modeltrainer = Model_trainer()
print(modeltrainer.intiate_model_trainer(train_arr,test_arr))
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