解决Discord机器人斜杠命令超时问题：长耗时任务的异步处理与并发策略

import discord
from discord.ext import commands
import asyncio
import aiohttp # 假设需要进行异步网络请求

# 异步版本的 test_function
async def test_function_async():
    """
    一个模拟异步耗时操作的函数。
    实际应用中会替换为异步I/O操作，例如使用aiohttp进行网络请求。
    """
    print("test_function_async started...")
    # 模拟异步网络请求
    async with aiohttp.ClientSession() as session:
        async with session.get('https://api.example.com/data') as response:
            _ = await response.json() # 假设获取JSON数据
            print(f"Fetched data (simulated): {_}")

    # 模拟异步延迟
    await asyncio.sleep(2) # 替换 time.sleep()
    print("test_function_async finished.")
    return "some_result" # 返回一些结果，例如文件路径或数据

# Discord bot setup
intents = discord.Intents.default()
bot = commands.Bot(command_prefix="!", intents=intents)
tree = bot.tree

@bot.event
async def on_ready():
    print(f'Logged in as {bot.user}')
    await tree.sync() # 同步斜杠命令

@tree.command(name="example_async_command", description="Example of an asynchronous command")
async def example_async_command(interaction: discord.Interaction):
    # 立即响应 defer，防止超时
    await interaction.response.defer()
    try:
        # 调用异步版本的 test_function
        result = await test_function_async()

        # 假设 test_function_async 最终生成了一个文件
        # 这里模拟生成一个文件并发送
        # 注意：如果文件生成本身是同步耗时，也需要考虑异步化或使用线程池
        with open('nba_ev.png', 'wb') as f:
            f.write(b'dummy image data') # 实际应是生成图像数据

        d_file = discord.File('nba_ev.png')
        await interaction.followup.send(content=f"Command completed successfully! Result: {result}", 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)

# bot.run("YOUR_BOT_TOKEN")

import discord
from discord.ext import commands
import asyncio
import concurrent.futures # 用于创建自定义线程池，如果需要的话

# 同步版本的 test_function
def test_function_sync():
    """
    一个模拟同步耗时操作的函数。
    它会阻塞当前线程，例如进行CPU密集型计算。
    """
    print("test_function_sync started...")
    # 模拟CPU密集型计算或同步文件操作
    total = 0
    for i in range(5_000_000):
        total += i * i
    import time
    time.sleep(2) # 模拟其他同步阻塞
    print("test_function_sync finished.")
    return f"Calculated sum: {total}"

# Discord bot setup (同上)
intents = discord.Intents.default()
bot = commands.Bot(command_prefix="!", intents=intents)
tree = bot.tree

@bot.event
async def on_ready():
    print(f'Logged in as {bot.user}')
    await tree.sync()

@tree.command(name="example_thread_command", description="Example of a command using threads for sync tasks")
async def example_thread_command(interaction: discord.Interaction):
    await interaction.response.defer() # 立即响应 defer
    try:
        # 获取当前事件循环
        loop = asyncio.get_event_loop()

        # 在默认的线程池中运行同步函数
        # None 表示使用默认的 ThreadPoolExecutor
        result = await loop.run_in_executor(None, test_function_sync)

        # 假设 test_function_sync 最终生成了一个文件
        with open('nba_ev.png', 'wb') as f:
            f.write(b'dummy image data') 

        d_file = discord.File('nba_ev.png')
        await interaction.followup.send(content=f"Command completed successfully! Result: {result}", 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)

# bot.run("YOUR_BOT_TOKEN")