import csv
from typing import Dict, List
import os
import logging

logger = logging.getLogger(__name__)

class CSVHandler:
    def __init__(self):
        self.clusters_file = 'clusters.csv'
        self.completed_posts_file = 'completed_posts.csv'

    def get_cluster_data(self) -> Dict:
        try:
            with open(self.clusters_file, 'r', newline='') as file:
                reader = csv.DictReader(file)
                for i, row in enumerate(reader, start=2):  # start=2 because row 1 is header
                    if row['Status'].lower() == 'no':
                        return {
                            'Keywords': row['Keywords'],
                            'Intent': row['Intent'],
                            'Primary Keyword': row['Primary Keyword'],
                            'row_number': i
                        }
            return None
        except Exception as e:
            print(f"Error reading clusters CSV: {e}")
            return None

    def get_previous_posts(self) -> List[Dict]:
        try:
            posts = []
            with open(self.completed_posts_file, 'r', newline='') as file:
                reader = csv.DictReader(file)
                for row in reader:
                    posts.append({
                        'title': row['Title'],
                        'keywords': row['Keywords'],
                        'summary': row['Meta Description'],
                        'url': row['URL']
                    })
            return posts
        except Exception as e:
            print(f"Error reading completed posts CSV: {e}")
            return []

    def mark_cluster_complete(self, row_number: int):
        try:
            # Read all rows
            rows = []
            with open(self.clusters_file, 'r', newline='', encoding='utf-8') as file:
                reader = csv.reader(file)
                header = next(reader)  # Get header row
                
                # Find Status column index, default to last column if not found
                status_index = header.index('Status') if 'Status' in header else -1
                if status_index == -1:
                    header.append('Status')
                    status_index = len(header) - 1
                
                rows = [header]
                rows.extend(list(reader))

            # Update status to 'completed' for the specified row
            if row_number < len(rows):
                # Ensure row has enough columns
                while len(rows[row_number]) <= status_index:
                    rows[row_number].append('')
                rows[row_number][status_index] = 'completed'

            # Write back all rows
            with open(self.clusters_file, 'w', newline='', encoding='utf-8') as file:
                writer = csv.writer(file)
                writer.writerows(rows)

        except Exception as e:
            logger.error(f"Error updating cluster status: {e}")
            raise

    def log_completed_post(self, metadata: Dict):
        try:
            with open(self.completed_posts_file, 'a', newline='') as file:
                writer = csv.writer(file)
                writer.writerow([
                    metadata['title'],
                    metadata['keywords'],
                    metadata['meta_description'],
                    f"https://yourblog.com/{metadata['slug']}"
                ])
        except Exception as e:
            print(f"Error logging completed post: {e}")

    def get_all_clusters(self):
        """Get all uncompleted clusters from the CSV file."""
        clusters = []
        try:
            with open(self.clusters_file, 'r', newline='', encoding='utf-8') as file:
                reader = csv.DictReader(file)
                for row_number, row in enumerate(reader, start=1):
                    # Check if Status column exists, if not or empty, treat as not completed
                    status = row.get('Status', '').lower()
                    if status != 'completed':
                        cluster_data = {
                            'Keywords': row.get('Keywords', ''),
                            'Intent': row.get('Intent', ''),
                            'Primary Keyword': row.get('Primary Keyword', ''),
                            'row_number': row_number,
                            'Status': status
                        }
                        # Validate required fields
                        if all(cluster_data[field] for field in ['Keywords', 'Intent', 'Primary Keyword']):
                            clusters.append(cluster_data)
                        else:
                            logger.warning(f"Row {row_number}: Missing required fields, skipping")
                return clusters
        except Exception as e:
            logger.error(f"Error reading clusters file: {e}")
            raise

    def process_uploaded_csv(self, csv_content: str) -> List[Dict]:
        """
        Process an uploaded CSV content string and return cluster data for blog generation.
        
        Args:
            csv_content (str): The decoded CSV content as a string
            
        Returns:
            List[Dict]: List of cluster data dictionaries
        """
        clusters = []
        try:
            # Split the content into lines and process as CSV
            from io import StringIO
            csv_file = StringIO(csv_content)
            reader = csv.DictReader(csv_file)
            
            for row_number, row in enumerate(reader, start=1):
                # Validate required columns
                required_columns = ['Keywords', 'Intent', 'Primary Keyword']
                if not all(col in row for col in required_columns):
                    logger.error(f"Row {row_number}: Missing required columns. Required: {required_columns}")
                    continue
                    
                cluster_data = {
                    'Keywords': row['Keywords'],
                    'Intent': row['Intent'],
                    'Primary Keyword': row['Primary Keyword'],
                    'row_number': row_number
                }
                clusters.append(cluster_data)
                
            logger.info(f"Successfully processed {len(clusters)} clusters from uploaded CSV")
            return clusters
            
        except Exception as e:
            logger.error(f"Error processing uploaded CSV: {e}")
            raise

    def process_csv_text(self, csv_text: str) -> List[Dict]:
        """
        Process CSV content provided as a text string and return cluster data for blog generation.
        
        Args:
            csv_text (str): The CSV content as a string
            
        Returns:
            List[Dict]: List of cluster data dictionaries
        """
        clusters = []
        try:
            # Split the text into lines
            from io import StringIO
            csv_file = StringIO(csv_text.strip())
            reader = csv.DictReader(csv_file)
            
            for row_number, row in enumerate(reader, start=1):
                # Validate required columns
                required_columns = ['Keywords', 'Intent', 'Primary Keyword']
                if not all(col in row for col in required_columns):
                    logger.error(f"Row {row_number}: Missing required columns. Required: {required_columns}")
                    continue
                    
                cluster_data = {
                    'Keywords': row['Keywords'],
                    'Intent': row['Intent'],
                    'Primary Keyword': row['Primary Keyword'],
                    'row_number': row_number
                }
                clusters.append(cluster_data)
                
            logger.info(f"Successfully processed {len(clusters)} clusters from CSV text")
            return clusters
            
        except Exception as e:
            logger.error(f"Error processing CSV text: {e}")
            raise