Several Solutions for Calling an Asynchronous Method in Python Synchronous Method Not Blocking the Main Process

If you want toSynchronization methodCalling asynchronous methodsave_category_icon,andDo not block the main thread, can be usedasyncio.create_task()orthreading/To achieve it.

Solution 1: Use asyncio.create_task() (recommended)

If your codeRun in event loop(likeFlask + QuartorFastAPI), can be used:

import asyncio

async def save_category_icon(category_id=0, category_name=None):
    await (2)  # Simulate asynchronous tasks    print(f"Icon saved for category {category_id} - {category_name}")

def edit_category():
    loop = asyncio.get_event_loop()
    loop.create_task(save_category_icon(category_id=1, category_name="Test"))
    print("Main process continues...")  # Will not wait for the asynchronous task to complete
edit_category()

✅ advantage：

• It won't block the main thread
• Tasks will be executed in the background
• Suitable for runningasyncioEvent loop (FastAPI, Quart, etc.)

Solution 2: Use threading (suitable for Flask synchronization environment)

If your code isFlask(Synchronous framework) is recommended to usethreadingRunning asynchronous method:

import threading
import asyncio

def run_async_task():
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)
    loop.run_until_complete(save_category_icon(category_id=1, category_name="Test"))

def edit_category():
    (target=run_async_task, daemon=True).start()
    print("Main process continues...")  # Will not wait for the asynchronous task to complete
edit_category()

✅ advantage：

• The Flask main process will not be blocked
• Asynchronous tasks can still be run in synchronous environments such as Flask
• daemon=TrueEnsure that the thread is automatically closed when the process exits

Solution 3: Use (suitable for high concurrency situations)

If your asynchronous task isCPU intensiveOr better thread pool management is needed, you can use：

import asyncio
from  import ThreadPoolExecutor

executor = ThreadPoolExecutor()

def run_async_task():
    loop = asyncio.new_event_loop()
    asyncio.set_event_loop(loop)
    loop.run_until_complete(save_category_icon(category_id=1, category_name="Test"))

def edit_category():
    (run_async_task)  # Submit tasks to thread pool    print("Main process continues...")

edit_category()

✅ advantage：

• Suitable for high concurrency tasks
• You can reuse ThreadPoolExecutor to improve performance
• Don't block the main process

Which plan should I choose?

Recommend the best solution

• FastAPI、Quart：✅ Useasyncio.create_task()
• Flask, Django (synchronous):✅ Use()
• High concurrency tasks:✅ Use

soAsynchronous tasks will run in the background and will not block the main process!

Summarize

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