from sqlalchemy.orm import Session
from datetime import datetime
from typing import Optional
from fastapi import HTTPException
from app.modules.edos.models import EDOS
from app.modules.edos.schema import EdosResponse, EdosUpload, messageResponse
from app.helpers.csv_mapper import CSVMapper
from app.helpers.db_adapter import DBAdapter
from app.helpers.extractCsv import CSVExtractor

class XMACSVService:
    """Orchestrator: extract, map, adapt pipeline"""

    @staticmethod
    def process_csv_from_url(
        csv_url: str,
        dry_run: bool = False,
        max_rows: int = None
    ) -> dict:
        """Flow: download CSV, parse, map to schema, insert into database"""

        try:
            # =========================================================
            # X - EXTRACT: Download and parse CSV
            # =========================================================
            print(f"Downloading CSV: {csv_url}")
            
            content, encoding = CSVExtractor.download_csv(csv_url)
            print(f"   Downloaded {len(content)} bytes, encoding: {encoding}")

            # Debug: show first lines
            print("First 10 lines of CSV:")
            lines = content.split('\n')
            for i, line in enumerate(lines[:10]):
                print(f"Line {i}: {repr(line[:200])}")
            
            # Parse CSV to raw rows
            raw_rows = CSVExtractor.read_csv(content)
            print(f"   Parsed {len(raw_rows)} rows")
            
            if not raw_rows:
                return {
                    'total_extracted': 0,
                    'total_mapped': 0,
                    'inserted': 0,
                    'dry_run': dry_run,
                    'errors': ['No data found in CSV']
                }
            
            print(f"   Columns: {list(raw_rows[0].keys())}")
            
            # =========================================================
            # M - MAP: Transform CSV rows to database schema
            # =========================================================
            mapped_rows = CSVMapper.map_rows(raw_rows)
            print(f"   Mapped {len(mapped_rows)} rows to database schema")
            
            if max_rows:
                mapped_rows = mapped_rows[:max_rows]
                print(f"   Limited to {max_rows} rows")
            
            # =========================================================
            # A - ADAPT: Insert into database
            # =========================================================
            inserted_count = 0
            errors = []
            
            if not dry_run:
                print(f"   Inserting {len(mapped_rows)} rows into database")
                adapter = DBAdapter()
                result = adapter.insert_filtered_data(mapped_rows)
                inserted_count = result.get('inserted', 0)
                errors = result.get('errors', [])
                print(f"   Inserted: {inserted_count}")
                print(f"   Duplicates skipped: {result.get('duplicates_skiped', 0)}")
                if errors:
                    print(f"   Errors: {len(errors)}")
            else:
                print(f"   DRY RUN - No data inserted")
            
            # =========================================================
            # Return response
            # =========================================================
            return {
                'total_extracted': len(raw_rows),
                'total_mapped': len(mapped_rows),
                'inserted': inserted_count,
                'dry_run': dry_run,
                'columns': list(raw_rows[0].keys()) if raw_rows else [],
                'sample': mapped_rows[:2] if mapped_rows else [],
                'errors': errors[:10] if errors else []  # Limit errors in response
            }
            
        except Exception as e:
            print(f"Error: {str(e)}")
            import traceback
            traceback.print_exc()
            raise