"""
Step 1: Load and preprocess Signal CSV data.
"""

import pandas as pd
from typing import List
from pipeline.models.base import PipelineStep
from pipeline.common_defs import Message
from pipeline.utils.text_utils import normalize_text

class DataLoader(PipelineStep):
    """Load and preprocess Signal chat CSV"""
    
    def __init__(self, csv_path: str, output_dir: str = './pipeline_output'):
        super().__init__(output_dir)
        self.csv_path = csv_path
    
    def execute(self) -> pd.DataFrame:
        """
        Load CSV and preprocess messages.
        
        Returns:
            DataFrame with preprocessed messages
        """
        self.logger.info(f"Loading Signal chat CSV: {self.csv_path}")
        
        # Load CSV
        df = pd.read_csv(self.csv_path)
        df.columns = df.columns.str.lower().str.strip()
        
        # Add line numbers
        df['line_number'] = range(1, len(df) + 1)
        
        # Fill missing messages
        df['message'] = df['message'].fillna('')
        
        # Normalize text
        self.logger.info("Normalizing text...")
        df['message_normalized'] = df['message'].apply(normalize_text)
        
        self.logger.info(f"Loaded {len(df):,} messages")
        
        # Save preprocessed data
        output_file = 'preprocessed_messages.csv'
        df.to_csv(self.output_dir / output_file, index=False)
        self.logger.info(f"Saved preprocessed data to: {output_file}")
        
        return df
    
    def create_message_objects(self, df: pd.DataFrame) -> List[Message]:
        """
        Convert DataFrame rows to Message objects.
        
        Args:
            df: DataFrame with message data
            
        Returns:
            List of Message objects
        """
        messages = []
        for _, row in df.iterrows():
            msg = Message(
                line_number=int(row['line_number']),
                timestamp=str(row.get('timestamp', '')),
                sender=str(row.get('sender', '')),
                message=str(row.get('message', '')),
                message_normalized=str(row.get('message_normalized', ''))
            )
            messages.append(msg)
        
        return messages

if __name__ == "__main__":
    # Example usage
    loader = DataLoader("../_sources/signal_messages.csv")
    df = loader.execute()
    print(f"Loaded {len(df)} messages")