import base64 from contextlib import asynccontextmanager import logging import time import uuid import os import re import asyncio import multiprocessing import hashlib import json from typing import List, Optional, Dict, Any, TypeVar, Generic # --- 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 from psycopg2.extras import RealDictCursor from urllib.parse import urlparse, parse_qs, urlencode, urlunparse # --- Database Pool --- from mysql.connector import pooling from psycopg2 import pool as pg_pool from threading import Lock 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") @asynccontextmanager async def lifespan(app: FastAPI): # Startup logic to_thread.current_default_thread_limiter().total_tokens = 2000 logger.info("Worker Process Started: Thread pool capacity set to 2000.") yield app = FastAPI( title="Unified Data Executor API (Mongo, SQL, CSV)", lifespan=lifespan ) # ============================================================================== # HIGH-CONCURRENCY BATCH MODELS & STARTUP # ============================================================================== T = TypeVar("T") class BatchRequest(BaseModel, Generic[T]): requests: List[T] class BatchResponse(BaseModel, Generic[T]): responses: List[T] # --- Directory Setup --- CHART_DIR = "generated_charts" os.makedirs(CHART_DIR, exist_ok=True) # --- CORS --- 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") if not API_SECRET_TOKEN: logger.warning("WARNING: API_BEARER_TOKEN not set in .env file! Security is compromised.") 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 # ============================================================================== # PYDANTIC MODELS # ============================================================================== 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 # ============================================================================== # CONNECTION POOL MANAGER # ============================================================================== 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 } 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 } 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): if db_url in self._pg_pools and conn: self._pg_pools[db_url].putconn(conn) pool_manager = ConnectionPoolManager() # ============================================================================== # REQUEST COALESCER (SINGLEFLIGHT) # ============================================================================== 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: # Execute the function (run_in_threadpool) with args/kwargs 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 # ============================================================================== 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 def _run_mysql_synchronously(db_url: str, sql_query: str, max_rows: int = 20, limited: bool = False) -> dict: start_time = time.time() connection = None cursor = None response = {"success": False, "results": None, "columns": None, "rowCount": 0, "executionTime": 0.0, "error": None, "is_aggregate": False, "limited": False, "message": ""} 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() response.update({"success": True, "message": "Query executed successfully (Non-SELECT)."}) return response if not limited: cursor.execute(clean_query) results = cursor.fetchall() response["message"] = f"Raw query executed. Returned {len(results)} row(s)." response["limited"] = False response["is_aggregate"] = is_aggregate_query(clean_query) else: if is_aggregate_query(clean_query): cursor.execute(clean_query) results = cursor.fetchall() response["message"] = f"Aggregate query completed. Returned {len(results)} row(s)." response["is_aggregate"] = True 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) response["message"] = f"Showing first {max_rows} rows only." if is_limited_result else f"Returned {len(results)} rows." response["limited"] = is_limited_result response["is_aggregate"] = False columns = [col[0] for col in cursor.description] if cursor.description else [] response.update({"success": True, "results": jsonable_encoder(results), "columns": columns, "rowCount": len(results), "executionTime": time.time() - start_time}) return response except Exception as e: response["error"] = str(e) return response finally: if cursor: cursor.close() if connection: connection.close() # Returns to pool def _run_postgres_synchronously(db_url: str, sql_query: str, max_rows: int = 20, limited: bool = False) -> dict: start_time = time.time() connection = None cursor = None response = {"success": False, "results": None, "columns": None, "rowCount": 0, "executionTime": 0.0, "error": None, "is_aggregate": False, "limited": False, "message": ""} 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() response.update({"success": True, "message": "Query executed successfully (Non-SELECT)."}) return response if not limited: cursor.execute(clean_query) results = cursor.fetchall() response["message"] = f"Raw query executed. Returned {len(results)} row(s)." response["limited"] = False response["is_aggregate"] = is_aggregate_query(clean_query) else: if is_aggregate_query(clean_query): cursor.execute(clean_query) results = cursor.fetchall() response["message"] = f"Aggregate query completed. Returned {len(results)} row(s)." response["is_aggregate"] = True response["limited"] = 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) response["message"] = f"Showing first {max_rows} rows only." if is_limited_result else f"Returned {len(results)} rows." response["limited"] = is_limited_result response["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}) response.update({"success": True, "results": clean_results, "columns": columns, "rowCount": len(results), "executionTime": time.time() - start_time}) return response except Exception as e: if connection: connection.rollback() response["error"] = str(e) return response finally: if cursor: cursor.close() if connection: pool_manager.return_postgres_connection(db_url, connection) # ============================================================================== # API ROUTES # ============================================================================== @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: # Parse logic is fast, can stay outside threadpool parsed_query = parse_query_input(payload.generated_query) # --- COALESCING MAGIC --- # Create a unique signature for this request unique_params = { "uri": payload.mongo_uri, "db": payload.db_name, "col": payload.collection_name, "q": parsed_query, # parsed_query is a Dict or List, json.dumps handles it "lim": payload.limited, "lrows": payload.limit_rows } # Use the coalescer to prevent duplicate simultaneous DB hits result_data = await coalescer.execute( "mongo", # Prefix unique_params, # Unique params dict run_in_threadpool, # Runner execute_mongo_operation, # The function to run # Arguments for 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_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 ID for Coalescing unique_params = { "db": normalized_url, "q": query.sql_query, "l": limit_val, "lim": query.limited } # FIXED: Pass _run_mysql_synchronously as the first POSITIONAL argument after run_in_threadpool result_dict = await coalescer.execute( "mysql", # Prefix unique_params, # Unique Params run_in_threadpool, # Runner _run_mysql_synchronously, # Arg 1 (The Function) db_url=normalized_url, # Kwargs 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: # If run_in_threadpool fails (e.g. TypeError) it ends up here logger.error(f"MySQL Endpoint Error: {str(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 } # FIXED: Pass _run_postgres_synchronously as the first POSITIONAL argument result_dict = await coalescer.execute( "postgres", unique_params, run_in_threadpool, _run_postgres_synchronously, # Arg 1 (The Function) 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: logger.error(f"Postgres Endpoint Error: {str(e)}") raise HTTPException(status_code=500, detail={"success": False, "error": str(e), "request_id": request_id}) # ... (CSV and Report endpoints remain unchanged) ... @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 --- # ============================================================================== # KEEP-ALIVE ROUTE # ============================================================================== @app.get("/") async def root(): return {"message": "Python Code Execution Server is running"} @app.get("/ping") async def ping(): return {"message": "I am alive!"} # ============================================================================== # HIGH PERFORMANCE SERVER EXECUTION # ============================================================================== if __name__ == "__main__": host = os.getenv("HOST", "0.0.0.0") port = int(os.getenv("PORT", 7860)) # Calculate workers (save 2 cores for system overhead) # Ensure at least 1 worker exists num_workers = max(1, multiprocessing.cpu_count() - 2) print(f"Starting production server on {host}:{port} with {num_workers} workers...") print("Using 'asyncio' loop to prevent Pandas/Numpy segfaults.") uvicorn.run( "controller:app", host=host, port=port, workers=num_workers, loop="asyncio", )