advanced patterns when Using Async with Flask and SQLAlchemy on Query Execution
Does anyone know how to I'm experiencing unexpected behavior when trying to use async functionality in my Flask application with SQLAlchemy... Specifically, I have an endpoint that queries the database for user data, but it seems to hang or return incomplete results when accessed concurrently. Here’s a snippet of the code: ```python from flask import Flask, jsonify from flask_sqlalchemy import SQLAlchemy import asyncio app = Flask(__name__) app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///test.db' db = SQLAlchemy(app) class User(db.Model): id = db.Column(db.Integer, primary_key=True) name = db.Column(db.String(50), nullable=False) @app.route('/users') async def get_users(): loop = asyncio.get_event_loop() users = await loop.run_in_executor(None, db.session.query(User).all) return jsonify([{'id': user.id, 'name': user.name} for user in users]) ``` The scenario arises when I access the `/users` endpoint concurrently from multiple clients. Sometimes it returns partial data or an empty list, and I see the following warning in my console: ``` RuntimeError: Task <Task pending name='Task-1' coro=<get_users() running at ...>> got Future <Future pending> attached to a different loop ``` I’ve tried several approaches, including using Flask’s built-in async capabilities and ensuring that my SQLAlchemy session is used correctly, but I still encounter these issues. I've also experimented with `asyncpg` for direct async database connections, but I prefer keeping SQLAlchemy for ORM functionality. Any insights on how to properly manage async with Flask and SQLAlchemy in this context would be greatly appreciated! I'm working in a Windows 10 environment. What's the best practice here?