src/pipeline/predict_pipeline.py

import sys
from typing import Any
import pandas as pd

from src.exception import CustomException
from src.utils import load_object



class PredictPipeline:
    def __init__(self) -> None:
        pass

    def predict(self,features):
        try:
            model_path = "artifacts/model.pkl"
            preprocessor_path = 'artifacts/preprocessor.pkl'

            model = load_object(file_path = model_path)
            preprocessor = load_object(file_path=preprocessor_path)

            data_scaled = preprocessor.transform(features)

            preds = model.predict(data_scaled)

            return preds
        except Exception as e:
            raise CustomException(e, sys)


class CustomData:
    def __init__(self,
                 gender:str,
                 race_ethnicity:str,
                 parental_level_of_education,
                 lunch:str,
                 test_preparation_course:str,
                 reading_score:int,
                 writing_score:int,

                 ):
        self.gender = gender
        self.race_ethnicity = race_ethnicity
        self.parental_level_of_education = parental_level_of_education
        self.lunch = lunch
        self.test_preparation_course = test_preparation_course
        self.reading_score = reading_score
        self.writing_score = writing_score

    def get_data_as_data_frame(self):
        try:
            custom_data_input_data = {
                "gender":[self.gender],
                "race_ethnicity":[self.race_ethnicity],
                "parental_level_of_education":[self.parental_level_of_education],
                "lunch":[self.lunch],
                "test_preparation_course":[self.test_preparation_course],
                "reading_score":[self.reading_score],
                "writing_score":[self.writing_score]

            }
            return pd.DataFrame(custom_data_input_data)
        except Exception as e:
            raise CustomException(e, sys)