controller.py

import base64
from contextlib import asynccontextmanager
import logging
import time
import uuid
import os
import re
import asyncio
import multiprocessing
import hashlib
import json
import psutil
from typing import List, Optional, Dict, Any, TypeVar, Generic
from urllib.parse import urlparse, parse_qs, urlencode, urlunparse
from threading import Lock

# --- FastAPI & Core ---
from fastapi import FastAPI, HTTPException, Depends
from fastapi.encoders import jsonable_encoder
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
from fastapi.middleware.cors import CORSMiddleware
from starlette.concurrency import run_in_threadpool
from anyio import to_thread
from dotenv import load_dotenv
from pydantic import BaseModel

# --- Database Drivers ---
from bson import ObjectId
import mysql.connector
from mysql.connector import pooling
import psycopg2
from psycopg2 import pool as pg_pool
from psycopg2.extras import RealDictCursor
import uvicorn

# --- Existing Services ---
from csv_analysis_service import execute_analysis_logic
from csv_chart_service import execute_python_code
from csv_metadata_service import CsvDataRequest, CsvInfoRequest, CsvInfoResponse, PythonExecutionRequest, PythonExecutionResponse, execute_python_logic, get_csv_basic_info, get_robust_csv_rows
from mongo_service import execute_mongo_operation, parse_query_input
from pydantic_csv_analysis_model import AnalysisRequest, AnalysisResponse
from pydantic_csv_charts_model import ChartExecutionPayload, ChartExecutionResponse
from pydantic_mongo_executor_model import ExecutorPayload, ExecutorResponse
from report_service import FileBoxProps, ReportRequest, execute_report_generation
from supabase_service import upload_bytes_to_supabase

# --- Configuration & Setup ---
load_dotenv()

logging.basicConfig(
    format="%(asctime)s - %(name)s - %(levelname)s - %(message)s",
    level=logging.INFO
)
logger = logging.getLogger("API_Controller")

def get_dynamic_thread_limit():
    """Calculates a safe thread limit based on available RAM."""
    try:
        total_ram_bytes = psutil.virtual_memory().total
        total_cores = multiprocessing.cpu_count()
        num_workers = max(1, total_cores - 2)
        ram_per_worker = total_ram_bytes / num_workers
        safe_ram_pool = ram_per_worker * 0.70
        BYTES_PER_THREAD = 8 * 1024 * 1024 
        calculated_limit = int(safe_ram_pool / BYTES_PER_THREAD)
        final_limit = max(100, min(calculated_limit, 3000))
        
        logger.info(f"Dynamic Limit Config: {total_ram_bytes/(1024**3):.2f}GB RAM / {num_workers} Workers. Limit: {final_limit}")
        return final_limit
    except Exception as e:
        logger.warning(f"Failed to calculate dynamic threads ({e}). Fallback to 1000.")
        return 1000

@asynccontextmanager
async def lifespan(app: FastAPI):
    safe_limit = get_dynamic_thread_limit()
    to_thread.current_default_thread_limiter().total_tokens = safe_limit
    logger.info(f"Worker Process Started: Thread pool capacity set to {safe_limit}.")
    yield

app = FastAPI(title="Unified Data Executor API", lifespan=lifespan)

# ==============================================================================
# BATCH MODELS
# ==============================================================================
T = TypeVar("T")

class BatchRequest(BaseModel, Generic[T]):
    requests: List[T]

class BatchResponse(BaseModel, Generic[T]):
    responses: List[T]

# --- Directory & CORS ---
CHART_DIR = "generated_charts"
os.makedirs(CHART_DIR, exist_ok=True)

origins_env = os.getenv("ALLOWED_ORIGINS", "*")
ORIGINS = [origin.strip() for origin in origins_env.split(",")]

app.add_middleware(
    CORSMiddleware,
    allow_origins=ORIGINS,
    allow_credentials=True,
    allow_methods=["*"],
    allow_headers=["*"],
)

# --- Security ---
security = HTTPBearer()
API_SECRET_TOKEN = os.getenv("API_BEARER_TOKEN")

async def validate_token(credentials: HTTPAuthorizationCredentials = Depends(security)):
    if credentials.credentials != API_SECRET_TOKEN:
        raise HTTPException(status_code=403, detail="Invalid Authentication Token")
    return credentials.credentials

# ==============================================================================
# CONNECTION POOL MANAGER (With Keepalives)
# ==============================================================================
class ConnectionPoolManager:
    def __init__(self):
        self._mysql_pools = {}
        self._pg_pools = {}
        self._lock = Lock() 

    def get_mysql_connection(self, db_url: str):
        with self._lock:
            if db_url not in self._mysql_pools:
                logger.info(f"Creating new MySQL pool for: {db_url}")
                parsed = urlparse(db_url)
                db_config = {
                    "user": parsed.username,
                    "password": parsed.password,
                    "host": parsed.hostname,
                    "port": parsed.port or 3306,
                    "database": parsed.path.lstrip("/"),
                    "connect_timeout": 5,
                    "pool_reset_session": True  # Validates connection on checkout
                }
                self._mysql_pools[db_url] = pooling.MySQLConnectionPool(
                    pool_name=str(uuid.uuid4()), 
                    pool_size=10, 
                    **db_config
                )
        return self._mysql_pools[db_url].get_connection()

    def get_postgres_connection(self, db_url: str):
        with self._lock:
            if db_url not in self._pg_pools:
                logger.info(f"Creating new Postgres pool for: {db_url}")
                parsed = urlparse(db_url)
                qs = parse_qs(parsed.query)
                sslmode = qs.get('sslmode', ['require'])[0] if 'sslmode' in qs else 'prefer'
                
                db_config = {
                    "host": parsed.hostname,
                    "port": parsed.port or 5432,
                    "database": parsed.path.lstrip("/"),
                    "user": parsed.username,
                    "password": parsed.password,
                    "sslmode": sslmode,
                    "connect_timeout": 5,
                    # --- TCP Keepalives (Prevents SSL Closed Unexpectedly) ---
                    "keepalives": 1,
                    "keepalives_idle": 30,
                    "keepalives_interval": 10,
                    "keepalives_count": 5
                }
                self._pg_pools[db_url] = pg_pool.ThreadedConnectionPool(1, 10, **db_config)
        return self._pg_pools[db_url].getconn()

    def return_postgres_connection(self, db_url, conn, close=False):
        """Returns connection to pool. If close=True, discards it."""
        if db_url in self._pg_pools and conn:
            self._pg_pools[db_url].putconn(conn, close=close)

pool_manager = ConnectionPoolManager()

# ==============================================================================
# REQUEST COALESCER
# ==============================================================================
class RequestCoalescer:
    def __init__(self):
        self._active_requests: Dict[str, asyncio.Future] = {}
        self._lock = asyncio.Lock()

    def _generate_key(self, prefix: str, data: dict) -> str:
        json_str = json.dumps(data, sort_keys=True, default=str)
        raw_str = f"{prefix}:{json_str}"
        return hashlib.md5(raw_str.encode()).hexdigest()

    async def execute(self, prefix: str, unique_params: dict, func, *args, **kwargs):
        key = self._generate_key(prefix, unique_params)
        async with self._lock:
            if key in self._active_requests:
                return await self._active_requests[key]
            loop = asyncio.get_running_loop()
            future = loop.create_future()
            self._active_requests[key] = future

        try:
            result = await func(*args, **kwargs)
            if not future.done(): future.set_result(result)
            return result
        except Exception as e:
            if not future.done(): future.set_exception(e)
            raise e
        finally:
            async with self._lock:
                if key in self._active_requests:
                    del self._active_requests[key]

coalescer = RequestCoalescer()

# ==============================================================================
# DB EXECUTION LOGIC (WITH RETRY & SELF-HEALING)
# ==============================================================================

def is_aggregate_query(query: str) -> bool:
    query_lower = query.lower()
    aggregate_patterns = [r'\bcount\s*\(', r'\bsum\s*\(', r'\bavg\s*\(', r'\bmin\s*\(', r'\bmax\s*\(', r'\bgroup\s+by\b', r'\bdistinct\b', r'\bhaving\b']
    for pattern in aggregate_patterns:
        if re.search(pattern, query_lower):
            return True
    return False

def normalize_mysql_uri(uri: str) -> str:
    try:
        parsed_uri = urlparse(uri)
        query_params = parse_qs(parsed_uri.query)
        query_params.pop('ssl-mode', None)
        new_query = urlencode(query_params, doseq=True)
        parsed_uri = parsed_uri._replace(query=new_query)
        return urlunparse(parsed_uri)
    except Exception:
        return uri

def normalize_postgres_uri(uri: str) -> str:
    try:
        parsed_uri = urlparse(uri)
        if parsed_uri.scheme == 'postgres':
            parsed_uri = parsed_uri._replace(scheme='postgresql')
        return urlunparse(parsed_uri)
    except Exception:
        return uri

# --- SELF-HEALING MYSQL EXECUTION ---
def _run_mysql_synchronously(db_url: str, sql_query: str, max_rows: int = 20, limited: bool = False) -> dict:
    start_time = time.time()
    
    # Retry Loop: If connection is dead, we retry once
    for attempt in range(2):
        connection = None
        cursor = None
        try:
            connection = pool_manager.get_mysql_connection(db_url)
            cursor = connection.cursor(dictionary=True)
            
            clean_query = sql_query.strip()
            query_lower = clean_query.lower()

            if not query_lower.startswith("select"):
                cursor.execute(clean_query)
                connection.commit()
                return {"success": True, "message": "Query executed successfully (Non-SELECT).", "executionTime": time.time() - start_time}

            if not limited:
                cursor.execute(clean_query)
                results = cursor.fetchall()
                is_aggregate = is_aggregate_query(clean_query)
                message = f"Raw query executed. Returned {len(results)} row(s)."
                is_limited_result = False
            else:
                if is_aggregate_query(clean_query):
                    cursor.execute(clean_query)
                    results = cursor.fetchall()
                    is_aggregate = True
                    message = f"Aggregate query completed. Returned {len(results)} row(s)."
                    is_limited_result = False
                else:
                    final_query = clean_query.rstrip(';').strip()
                    if not re.search(r'\blimit\s+\d+', query_lower):
                        final_query = f"{final_query} LIMIT {max_rows}"
                    cursor.execute(final_query)
                    results = cursor.fetchall()
                    is_limited_result = (len(results) == max_rows)
                    message = f"Showing first {max_rows} rows only." if is_limited_result else f"Returned {len(results)} rows."
                    is_aggregate = False

            columns = [col[0] for col in cursor.description] if cursor.description else []
            return {
                "success": True, "results": jsonable_encoder(results), "columns": columns, 
                "rowCount": len(results), "executionTime": time.time() - start_time,
                "is_aggregate": is_aggregate, "limited": is_limited_result, "message": message, "error": None
            }

        except (mysql.connector.errors.OperationalError, mysql.connector.errors.DatabaseError) as e:
            # Fatal connection error
            if connection:
                try: connection.close() # Close properly so pool knows it's bad (or discards it)
                except: pass
            
            # If this was the first attempt, try again with a fresh connection
            if attempt == 0:
                logger.warning(f"MySQL connection lost. Retrying... Error: {e}")
                continue 
            
            return {"success": False, "error": f"MySQL Error: {str(e)}", "executionTime": 0.0}
            
        except Exception as e:
            # Logic error (Syntax, etc). Do not retry.
            if connection: connection.close()
            return {"success": False, "error": str(e), "executionTime": 0.0}
            
        finally:
            if cursor: 
                try: cursor.close()
                except: pass
            # Connection close handled in blocks above to handle "poisoned" logic correctly

# --- SELF-HEALING POSTGRES EXECUTION ---
def _run_postgres_synchronously(db_url: str, sql_query: str, max_rows: int = 20, limited: bool = False) -> dict:
    start_time = time.time()
    
    # Retry Loop for Dead Connections
    for attempt in range(2):
        connection = None
        cursor = None
        try:
            connection = pool_manager.get_postgres_connection(db_url)
            cursor = connection.cursor(cursor_factory=RealDictCursor)
            
            clean_query = sql_query.strip()
            query_lower = clean_query.lower()
            
            if not query_lower.startswith(("select", "show", "explain", "with")):
                cursor.execute(clean_query)
                connection.commit()
                # Return Success
                pool_manager.return_postgres_connection(db_url, connection)
                return {"success": True, "message": "Query executed successfully (Non-SELECT).", "executionTime": time.time() - start_time}
            
            # Read Logic
            if not limited:
                cursor.execute(clean_query)
                results = cursor.fetchall()
                is_aggregate = is_aggregate_query(clean_query)
                message = f"Raw query executed. Returned {len(results)} row(s)."
                is_limited_result = False
            else:
                if is_aggregate_query(clean_query):
                    cursor.execute(clean_query)
                    results = cursor.fetchall()
                    is_aggregate = True
                    message = f"Aggregate query completed. Returned {len(results)} row(s)."
                    is_limited_result = False
                else:
                    final_query = clean_query.rstrip(';').strip()
                    if not re.search(r'\blimit\s+\d+', query_lower):
                        final_query = f"{final_query} LIMIT {max_rows}"
                    cursor.execute(final_query)
                    results = cursor.fetchall()
                    is_limited_result = (len(results) == max_rows)
                    message = f"Showing first {max_rows} rows only." if is_limited_result else f"Returned {len(results)} rows."
                    is_aggregate = False

            columns = [desc[0] for desc in cursor.description] if cursor.description else []
            clean_results = jsonable_encoder(results, custom_encoder={uuid.UUID: str, ObjectId: str})
            
            # Success! Return conn
            pool_manager.return_postgres_connection(db_url, connection)
            return {
                "success": True, "results": clean_results, "columns": columns, 
                "rowCount": len(results), "executionTime": time.time() - start_time,
                "is_aggregate": is_aggregate, "limited": is_limited_result, "message": message, "error": None
            }

        except (psycopg2.InterfaceError, psycopg2.OperationalError) as e:
            # Bad Connection. DISCARD IT.
            if connection:
                pool_manager.return_postgres_connection(db_url, connection, close=True)
            
            if attempt == 0:
                logger.warning(f"Postgres connection dead ({e}). Retrying with fresh connection...")
                continue
            return {"success": False, "error": f"DB Connection Failed: {str(e)}", "executionTime": 0.0}

        except Exception as e:
            # Logic/SQL Error. Rollback and return to pool.
            if connection:
                try: connection.rollback()
                except: pass # If rollback fails, pool.putconn might fail next, but we try
                pool_manager.return_postgres_connection(db_url, connection, close=False)
                
            return {"success": False, "error": str(e), "executionTime": 0.0}
            
        finally:
            if cursor: 
                try: cursor.close()
                except: pass

# ==============================================================================
# API ROUTES
# ==============================================================================

class SqlQueryRequest(BaseModel):
    database_url: str
    sql_query: str
    limit_rows: Optional[int] = 20
    limited: bool = False

class SqlQueryResponse(BaseModel):
    success: bool
    results: Optional[List[Dict[str, Any]]] = None
    columns: Optional[List[str]] = None
    rowCount: Optional[int] = 0
    executionTime: Optional[float] = 0.0
    error: Optional[str] = None
    request_id: str
    is_aggregate: bool = False
    limited: bool = False
    message: Optional[str] = None

class PgQueryRequest(BaseModel):
    database_url: str
    sql_query: str
    limit_rows: Optional[int] = 20
    limited: bool = False 

class PgQueryResponse(BaseModel):
    success: bool
    results: Optional[List[Dict[str, Any]]] = None
    columns: Optional[List[str]] = None
    rowCount: Optional[int] = 0
    executionTime: Optional[float] = 0.0
    error: Optional[str] = None
    request_id: str
    is_aggregate: bool = False
    limited: bool = False
    message: Optional[str] = None

@app.post("/api/execute_sql_query", response_model=SqlQueryResponse)
async def execute_mysql_endpoint(query: SqlQueryRequest, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    try:
        normalized_url = normalize_mysql_uri(query.database_url)
        limit_val = query.limit_rows if query.limit_rows is not None else 20
        unique_params = {
            "db": normalized_url, "q": query.sql_query, "l": limit_val, "lim": query.limited
        }
        result_dict = await coalescer.execute(
            "mysql", unique_params, run_in_threadpool, _run_mysql_synchronously, 
            db_url=normalized_url, sql_query=query.sql_query, max_rows=limit_val, limited=query.limited
        )
        final_result = result_dict.copy()
        final_result["request_id"] = request_id
        return SqlQueryResponse(**final_result)
    except Exception as e:
        raise HTTPException(status_code=500, detail={"success": False, "error": str(e), "request_id": request_id})

@app.post("/api/execute_postgres_query", response_model=PgQueryResponse)
async def execute_postgres_endpoint(query: PgQueryRequest, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    try:
        clean_url = normalize_postgres_uri(query.database_url)
        limit_val = query.limit_rows if query.limit_rows is not None else 20
        unique_params = {
            "db": clean_url, "q": query.sql_query, "l": limit_val, "lim": query.limited
        }
        result_dict = await coalescer.execute(
            "postgres", unique_params, run_in_threadpool, _run_postgres_synchronously, 
            db_url=clean_url, sql_query=query.sql_query, max_rows=limit_val, limited=query.limited
        )
        final_result = result_dict.copy()
        final_result["request_id"] = request_id
        return PgQueryResponse(**final_result)
    except Exception as e:
        raise HTTPException(status_code=500, detail={"success": False, "error": str(e), "request_id": request_id})

@app.post("/api/execute_mongo", response_model=ExecutorResponse)
async def execute_mongo_endpoint(payload: ExecutorPayload, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    start_time = time.time()
    try:
        parsed_query = parse_query_input(payload.generated_query)
        unique_params = {
            "uri": payload.mongo_uri, "db": payload.db_name, "col": payload.collection_name, 
            "q": parsed_query, "lim": payload.limited, "lrows": payload.limit_rows
        }
        result_data = await coalescer.execute(
            "mongo", unique_params, run_in_threadpool, execute_mongo_operation, 
            mongo_uri=payload.mongo_uri, db_name=payload.db_name, collection_name=payload.collection_name, 
            query=parsed_query, limited=payload.limited, limit_rows=payload.limit_rows
        )
        return ExecutorResponse(status="success", count=len(result_data), data=jsonable_encoder(result_data, custom_encoder={ObjectId: str}), duration_seconds=round(time.time() - start_time, 4), request_id=request_id)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/api/execute_chart", response_model=ChartExecutionResponse)
async def execute_chart_endpoint(payload: ChartExecutionPayload, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    try:
        image_bytes, error_msg, logs = await run_in_threadpool(execute_python_code, code=payload.code, csv_url=payload.csv_url)
        if error_msg: return ChartExecutionResponse(status="error", error=error_msg, output_log=logs, request_id=request_id)
        if payload.return_base64:
            base64_str = base64.b64encode(image_bytes).decode('utf-8')
            return ChartExecutionResponse(status="success", base64_image=base64_str, output_log=logs, request_id=request_id)
        else:
            unique_name = f"{uuid.uuid4()}.png"
            public_url = await run_in_threadpool(upload_bytes_to_supabase, image_bytes=image_bytes, file_name=unique_name, chat_id=payload.chat_id)
            return ChartExecutionResponse(status="success", image_url=public_url, output_log=logs, request_id=request_id)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.post("/api/execute_csv_analysis", response_model=AnalysisResponse)
async def execute_analysis_endpoint(payload: AnalysisRequest, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    try:
        result = await run_in_threadpool(execute_analysis_logic, code=payload.code, csv_url=payload.csv_url)
        return AnalysisResponse(success=result["success"], output_log=result["output_log"], results=result["results"], error=result["error"], request_id=request_id)
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
    
@app.post("/api/generate_report", response_model=FileBoxProps)
async def generate_report_endpoint(payload: ReportRequest, token: str = Depends(validate_token)):
    try:
        result = await execute_report_generation(code=payload.code, csv_url=payload.csv_url, chat_id=payload.chat_id)
        return result
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))
    
@app.post("/api/get_csv_info", response_model=CsvInfoResponse)
async def get_csv_info_endpoint(payload: CsvInfoRequest, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    start_time = time.time()
    try:
        info_result = await run_in_threadpool(get_csv_basic_info, csv_path=payload.csv_url)
        if "error" in info_result:
            return CsvInfoResponse(success=False, error=info_result["error"], request_id=request_id, duration=time.time() - start_time)
        return CsvInfoResponse(success=True, data=info_result, request_id=request_id, duration=time.time() - start_time)
    except Exception as e:
        raise HTTPException(status_code=500, detail={"success": False, "error": str(e), "request_id": request_id})
        
@app.post("/api/csv_data")
async def get_csv_data_endpoint(payload: CsvDataRequest, token: str = Depends(validate_token)):
    try:
        result = await run_in_threadpool(get_robust_csv_rows, csv_url=payload.csv_url)
        if isinstance(result, dict) and "error" in result: raise HTTPException(status_code=400, detail=result["error"])
        return result
    except Exception as e:
        raise HTTPException(status_code=500, detail=f"Internal server error: {str(e)}")

@app.post("/api/execute_python", response_model=PythonExecutionResponse)
async def execute_python_endpoint(payload: PythonExecutionRequest, token: str = Depends(validate_token)):
    request_id = str(uuid.uuid4())[:8]
    try:
        execution_result = await run_in_threadpool(execute_python_logic, code=payload.code, custom_context=payload.context)
        return PythonExecutionResponse(success=execution_result['error'] is None, output=execution_result['output'], result=jsonable_encoder(execution_result['result']), isStructured=execution_result['isStructured'], error=execution_result['error'], request_id=request_id)
    except Exception as e:
        raise HTTPException(status_code=500, detail={"success": False, "error": str(e), "request_id": request_id})

# --- Batch Handlers ---
async def batch_parallel_handler(func, requests: List[Any], token: str):
    tasks = [func(req, token) for req in requests]
    results = await asyncio.gather(*tasks, return_exceptions=True)
    return [res if not isinstance(res, Exception) else {"success": False, "error": str(res)} for res in results]

@app.post("/api/batch/execute_sql_query", response_model=BatchResponse[SqlQueryResponse])
async def batch_execute_sql(payload: BatchRequest[SqlQueryRequest], token: str = Depends(validate_token)):
    responses = await batch_parallel_handler(execute_mysql_endpoint, payload.requests, token)
    return BatchResponse(responses=responses)

@app.post("/api/batch/execute_postgres_query", response_model=BatchResponse[PgQueryResponse])
async def batch_execute_pg(payload: BatchRequest[PgQueryRequest], token: str = Depends(validate_token)):
    responses = await batch_parallel_handler(execute_postgres_endpoint, payload.requests, token)
    return BatchResponse(responses=responses)

@app.post("/api/batch/execute_mongo", response_model=BatchResponse[ExecutorResponse])
async def batch_execute_mongo(payload: BatchRequest[ExecutorPayload], token: str = Depends(validate_token)):
    responses = await batch_parallel_handler(execute_mongo_endpoint, payload.requests, token)
    return BatchResponse(responses=responses)

# --- Test Endpoint ---
class TestCalcRequest(BaseModel):
    value: int

def _heavy_calculation_task(value: int) -> int:
    time.sleep(0.1)
    return value * 2

@app.post("/api/test/parallel_calc_no_auth")
async def test_parallel_calc_endpoint(payload: TestCalcRequest):
    try:
        result = await run_in_threadpool(_heavy_calculation_task, value=payload.value)
        return {"success": True, "result": result, "process_id": os.getpid()}
    except Exception as e:
        raise HTTPException(status_code=500, detail=str(e))

@app.get("/")
async def root():
    return {"message": "Python Code Execution Server is running"}

@app.get("/ping")
async def ping():
    return {"message": "I am alive!"}

if __name__ == "__main__":
    host = os.getenv("HOST", "0.0.0.0")
    port = int(os.getenv("PORT", 7860))
    num_workers = max(1, multiprocessing.cpu_count() - 2)
    print(f"Starting production server on {host}:{port} with {num_workers} workers...")
    uvicorn.run("controller:app", host=host, port=port, workers=num_workers, loop="asyncio")