Awaiting a non async function in python

When working with Python, it is common to come across situations where you need to wait for a non-async function to complete before proceeding with the rest of your code. In this article, we will explore three different ways to solve this problem.

Option 1: Using the threading module

One way to solve this problem is by using the threading module in Python. This module allows you to create and manage threads, which can run concurrently with the main thread of your program.

import threading

def non_async_function():
    # Perform some time-consuming task
    pass

# Create a new thread for the non-async function
thread = threading.Thread(target=non_async_function)

# Start the thread
thread.start()

# Wait for the thread to complete
thread.join()

# Continue with the rest of your code
print("Non-async function has completed")

This approach creates a new thread for the non-async function and starts it. The join() method is then used to wait for the thread to complete before proceeding with the rest of the code.

Option 2: Using the concurrent.futures module

Another way to solve this problem is by using the concurrent.futures module, which provides a high-level interface for asynchronously executing callables.

import concurrent.futures

def non_async_function():
    # Perform some time-consuming task
    pass

# Create a thread pool executor
executor = concurrent.futures.ThreadPoolExecutor()

# Submit the non-async function to the executor
future = executor.submit(non_async_function)

# Wait for the future to complete
future.result()

# Continue with the rest of your code
print("Non-async function has completed")

In this approach, a thread pool executor is created using the ThreadPoolExecutor class. The non-async function is then submitted to the executor using the submit() method, which returns a future object. The result() method is used to wait for the future to complete.

Option 3: Using the asyncio module

If you are already working with asynchronous code using the asyncio module, you can also solve this problem by wrapping the non-async function in a coroutine and using the run_in_executor() function.

import asyncio

def non_async_function():
    # Perform some time-consuming task
    pass

async def main():
    loop = asyncio.get_event_loop()
    await loop.run_in_executor(None, non_async_function)
    print("Non-async function has completed")

# Run the main coroutine
asyncio.run(main())

In this approach, the non-async function is wrapped in a coroutine called main(). The run_in_executor() function is then used to run the non-async function in a separate executor. The asyncio.run() function is used to run the main coroutine.

After exploring these three options, it is clear that the best approach depends on the specific requirements of your code. If you are already working with asynchronous code, option 3 using the asyncio module may be the most suitable. However, if you are not using asynchronous code, options 1 and 2 using the threading and concurrent.futures modules respectively can provide effective solutions.

Ultimately, the choice between these options will depend on factors such as the complexity of your code, performance requirements, and personal preference. It is recommended to carefully consider these factors and choose the option that best fits your specific use case.

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12 Responses

  1. Option 3: Using the asyncio module sounds like a cool way to handle non-async functions. Cant wait to try it out! 🚀

    1. I totally disagree! Option 1 is just a recipe for disaster. Its risky and unnecessary. Stick with Option 3 for a safer and more practical approach. Adding spice might sound exciting, but its not worth the potential complications. Trust me on this one.

  2. Option 1: Threading? Option 2: Concurrent.futures? Option 3: Asyncio? So many options, my brain is fried! 😵 #PythonProblems

    1. Option 3: Asyncio is the way to go! Its a powerful tool that can handle concurrent tasks efficiently and make your code more scalable. Dont let it fry your brain, embrace the challenge and dive into the world of asynchronous programming! 💪🐍 #PythonPower

  3. Option 1: Threading? No thanks, Id rather not deal with those pesky race conditions!
    Option 2: Concurrent.futures? Sounds fancy, but will it make my code run faster?
    Option 3: Asyncio, you beautiful beast! Lets embrace the async-await goodness! 🚀

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