Python asyncio coroutine access one shared object

Published: 30 November 2023
on channel: CodeShare
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Asynchronous programming in Python is becoming increasingly popular, especially with the introduction of the asyncio module. Asynchronous programming allows you to write concurrent code that is more efficient and responsive. In this tutorial, we'll explore how to use Python's asyncio module to implement coroutines that access a shared object concurrently.
Make sure you have Python 3.5 or above installed on your system, as asyncio is introduced in Python 3.4.
In Python's asyncio framework, a coroutine is a special type of function that can be paused and resumed. It allows non-blocking, asynchronous code execution. To define a coroutine, you use the async def syntax.
The await keyword is used to pause the execution of the coroutine until the awaited task completes. In the example above, we use asyncio.sleep(2) to simulate an asynchronous operation that takes 2 seconds.
Let's create a simple shared object that multiple coroutines will access. In this example, we'll use a counter as our shared object.
Now, let's create coroutines that will increment the counter and retrieve its value. We'll use the asyncio.Lock to ensure that only one coroutine can access the shared object at a time.
In this example, we create two coroutines (increment_counter and get_counter_value) that use the asyncio.Lock to synchronize access to the shared object. The asyncio.gather function is used to run multiple coroutines concurrently.
Save the code in a file (e.g., asyncio_shared_object_example.py) and run it:
You should see output indicating that coroutines are incrementing and retrieving the counter value in a coordinated manner.
This tutorial provides a basic example of using asyncio coroutines to access a shared object concurrently. As your understanding of asynchronous programming grows, you can explore more advanced features of asyncio and build more complex asynchronous applications.
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