优化Discord斜杠命令响应：异步处理与并发策略

@tree.command(name = "example_command", description = "Example")
async def example_command(interaction):
    await interaction.response.defer() # 延迟响应
    try:
        file = test_function() # 这是一个同步的、耗时操作
        d_file = discord.File('nba_ev.png')
        await interaction.followup.send(file=d_file)
    except Exception as e:
        print(f"An error occurred: {e}")
        error_message = "An error occurred while processing your request. Please try again."
        await interaction.followup.send(content=error_message, ephemeral=True)

import requests
import time

def test_function():
    print("Starting synchronous operation...")
    response = requests.get("https://api.example.com/data", timeout=10) # 耗时网络请求
    time.sleep(2) # 模拟其他处理
    print("Synchronous operation finished.")
    return response.json()

import aiohttp
import asyncio

async def async_test_function():
    print("Starting asynchronous operation...")
    async with aiohttp.ClientSession() as session:
        async with session.get("https://api.example.com/data") as response:
            data = await response.json()
    await asyncio.sleep(2) # 模拟其他异步处理
    print("Asynchronous operation finished.")
    return data

@tree.command(name = "example_command", description = "Example")
async def example_command(interaction):
    await interaction.response.defer() # 确保在3秒内响应
    try:
        # 调用异步版本的test_function
        result_data = await async_test_function()
        # 假设 result_data 可以用来生成文件或直接发送
        # d_file = discord.File('nba_ev.png') # 如果文件是预先存在的
        await interaction.followup.send(content=f"Operation complete: {result_data['some_key']}")
    except Exception as e:
        print(f"An error occurred: {e}")
        error_message = "An error occurred while processing your request. Please try again."
        await interaction.followup.send(content=error_message, ephemeral=True)

import asyncio
import concurrent.futures # 用于线程池或进程池

# 假设这是无法或难以转换为异步的同步函数
def blocking_cpu_bound_function():
    print("Starting blocking CPU-bound operation...")
    # 模拟一个非常耗时的计算
    result = sum(i * i for i in range(10**7))
    print("Blocking CPU-bound operation finished.")
    return result

@tree.command(name = "example_command", description = "Example")
async def example_command(interaction):
    await interaction.response.defer() # 确保在3秒内响应
    try:
        loop = asyncio.get_running_loop()
        # 在默认的ThreadPoolExecutor中运行同步函数
        # 默认executor是ThreadPoolExecutor，适用于I/O和CPU密集型任务
        result = await loop.run_in_executor(None, blocking_cpu_bound_function)

        await interaction.followup.send(content=f"CPU-bound task completed with result: {result}")
    except Exception as e:
        print(f"An error occurred: {e}")
        error_message = "An error occurred while processing your request. Please try again."
        await interaction.followup.send(content=error_message, ephemeral=True)