# src/transformers/sensor_data.py
from typing import Dict, Any
import pandas as pd
import numpy as np
from datetime import datetime
from uuid import UUID, uuid4
from config import config


class WoDataTransformer:
    def transform(self, df: pd.DataFrame) -> pd.DataFrame:
        """
        Transform sensor data according to business rules
        """
        # Create a copy to avoid modifying original data
        transformed = df.copy()

        # 1. Add UUID
        transformed['id'] = uuid4()

        # # 5. Drop unnecessary columns
        # columns_to_drop = self.config.get('columns_to_drop', [])
        # if columns_to_drop:
        #     transformed = transformed.drop(columns=columns_to_drop, errors='ignore')

        return transformed

    def validate(self, df: pd.DataFrame) -> bool:
        """
        Validate transformed data
        """
        if df.empty:
            return False

        # Check required columns
        if not all(col in df.columns for col in config.get('columns')):
            return False

        # check id column and id is UUID
        if 'id' not in df.columns:
            return False

        if not all(isinstance(val, UUID) for val in df['id']):
            return False

        return True