python asyncio 协程库的使用

1. Introduction to Python asyncio

Python asyncio is a library that provides a way to write concurrent code using coroutines, multiplexing I/O access over sockets and other resources.

With asyncio, you can write concurrent code using the async/await syntax, which allows you to write sequential-looking code that actually runs asynchronously.

In this article, we will explore the usage of the Python asyncio library in detail.

2. Getting Started

To use Python asyncio, you need to be running Python 3.5 or above, as the async/await syntax was introduced in Python 3.5.

You can install asyncio using pip by running the following command:

pip install asyncio

Once you have installed asyncio, you can import it into your Python script using the following line:

import asyncio

3. Creating and Running an Async Function

To create an async function, you simply need to use the "async def" syntax before the function definition. Let's see an example:

import asyncio

async def my_async_function():
    # Some asynchronous code here
    await asyncio.sleep(1)
    print("Async function completed")

In the example above, we define an async function called "my_async_function". Inside this function, we have some asynchronous code that waits for 1 second using the "await asyncio.sleep(1)" statement.

To run an async function, you can use the "asyncio.run()" function. Here's an example:

import asyncio

async def my_async_function():
    await asyncio.sleep(1)
    print("Async function completed")
asyncio.run(my_async_function())

In the example above, we use the "asyncio.run()" function to run the "my_async_function". This function will run the async function until it completes and then exit the program.

4. Working with Multiple Async Functions

One of the main benefits of using asyncio is the ability to call multiple async functions concurrently. This can greatly improve the performance of your program.

To call multiple async functions concurrently, you can use the "asyncio.gather()" function. Let's see an example:

import asyncio

async def async_function_1():
    await asyncio.sleep(1)
    print("Async function 1 completed")
async def async_function_2():
    await asyncio.sleep(2)
    print("Async function 2 completed")
async def main():
    await asyncio.gather(
        async_function_1(),
        async_function_2()
    )
asyncio.run(main())

In the example above, we define two async functions: "async_function_1" and "async_function_2". These functions simulate some asynchronous workflows by waiting for different amounts of time. We then use the "asyncio.gather()" function to run both functions concurrently.

By using "asyncio.gather()", the two async functions will run in parallel, resulting in a faster execution time compared to running them sequentially.

It's important to note that the order of execution is not guaranteed when using asyncio.gather(). The functions will complete in an order determined by the event loop.

5. Controlling Tasks with the Event Loop

5.1. The Event Loop

The event loop is the core of asyncio and is responsible for executing coroutines and scheduling callbacks.

You can access the event loop using the "asyncio.get_event_loop()" function:

import asyncio

loop = asyncio.get_event_loop()

Once you have the event loop object, you can run a coroutine using the "loop.run_until_complete()" method:

import asyncio

async def my_async_function():
    await asyncio.sleep(1)
    print("Async function completed")
loop = asyncio.get_event_loop()
loop.run_until_complete(my_async_function())
loop.close()

In the example above, we create an event loop using "asyncio.get_event_loop()". We then run the "my_async_function()" coroutine using "loop.run_until_complete()". Finally, we close the event loop using "loop.close()".

Remember to always close the event loop when you are done with it to free up system resources.

5.2. Working with Tasks

In asyncio, a Task is a high-level object that wraps a coroutine and can be scheduled by the event loop.

To create a Task, you can use the "asyncio.create_task()" function:

import asyncio

async def my_async_function():
    await asyncio.sleep(1)
    print("Async function completed")
loop = asyncio.get_event_loop()
task = loop.create_task(my_async_function())
loop.run_until_complete(task)
loop.close()

In the example above, we create a Task using "loop.create_task()". We then pass the Task to "loop.run_until_complete()" to schedule it with the event loop.

You can also gather multiple Tasks using "asyncio.gather()" as shown in the previous section. This allows you to run multiple Tasks concurrently.

6. Conclusion

In this article, we explored the basics of using Python asyncio for writing concurrent code using coroutines. We learned how to create and run async functions, work with multiple async functions concurrently, and control tasks with the event loop.

Asyncio is a powerful library that can greatly improve the performance of your Python programs by allowing them to run asynchronously. It is especially useful for I/O-bound tasks and can be combined with other Python libraries such as aiohttp for building efficient web applications.

By using asyncio, you can write efficient and scalable code that takes full advantage of the capabilities of modern computer systems. It is definitely worth exploring and incorporating into your Python projects.