"""
Simple Moving Average (SMA) indicator implementation.
"""

from typing import List
import pandas as pd

from ..base import BaseIndicator
from ..result import IndicatorResult


class SMAIndicator(BaseIndicator):
    """
    Simple Moving Average (SMA) technical indicator.
    
    Calculates the unweighted mean of previous n periods.
    Handles sparse data appropriately without interpolation.
    """
    
    def calculate(self, df: pd.DataFrame, period: int = 20,
                 price_column: str = 'close') -> List[IndicatorResult]:
        """
        Calculate Simple Moving Average (SMA).
        
        Args:
            df: DataFrame with OHLCV data
            period: Number of periods for moving average (default: 20)
            price_column: Price column to use ('open', 'high', 'low', 'close')
            
        Returns:
            List of indicator results with SMA values
        """
        # Validate input data
        if not self.validate_dataframe(df, period):
            return []
        
        try:
            # Calculate SMA using pandas rolling window
            df['sma'] = df[price_column].rolling(window=period, min_periods=period).mean()
            
            # Convert results to IndicatorResult objects
            results = []
            for timestamp, row in df.iterrows():
                if not pd.isna(row['sma']):
                    result = IndicatorResult(
                        timestamp=timestamp,
                        symbol=row['symbol'],
                        timeframe=row['timeframe'],
                        values={'sma': row['sma']},
                        metadata={'period': period, 'price_column': price_column}
                    )
                    results.append(result)
            
            return results
            
        except Exception as e:
            if self.logger:
                self.logger.error(f"Error calculating SMA: {e}")
            return []