Async io in Python is a Python package that can be used to write concurrent codes. What is concurrency? Concurrency is a process where multiple tasks can run in an overlapping manner and can be paused and resumed as they can save their state during these intervals. It is a slightly broader term than parallelism.
What is Async IO in Python?
Async io is a library package in Python that can be used to write concurrent and asynchronous code using async and wait syntax. It can be imported in Python code using ‘import asyncio’. A function introduced using async is a coroutine. It can use await, yield, return, etc in the function.
Highlights:
- Understanding Concurrency: Concurrency is explained as a process where multiple tasks can run in an overlapping manner, allowing them to be paused and resumed while saving their state. It’s highlighted as a broader concept than parallelism.
- Introduction to Async IO in Python: Async IO is introduced as a library package in Python that enables the writing of concurrent and asynchronous code using the
asyncandawaitsyntax. The package can be imported usingimport asyncio, and functions introduced withasyncare termed coroutines.- Setting up Async IO Environment: The process of setting up Async IO in Python is outlined, including the requirement of Python version 3.7 or above and the creation of a virtual environment using tools like
venvorvirtualenv. The installation of async libraries likeaiohttpandaioredisis also demonstrated.- Understanding Coroutines: Coroutines are highlighted as an important aspect of Async IO in Python. They are described as functions that can suspend their execution and pass control to another coroutine task temporarily, allowing concurrent code execution without blocking.
- Utilizing Await/Async Keyword and Event Loop: The usage of
awaitkeyword to suspend coroutine execution until asynchronous operations are completed is explained. Additionally, the concept of an event loop in Async IO Python is demonstrated through an example, showcasing how tasks are executed concurrently.
Async IO in Python: Setting up your Environment
First step is setting up Async io in Python. For this you will need Python 3.7 version or above. You can create a virtual environment for your project to manage your dependencies. It can be created using ‘venv’ or ‘virtualenv’.
| Async IO in Python |
| Python -m venv myenv
myevn\Scripts\activate //for windows Source myenv/bin/activate //for uniX or macOS |
The following command will create a virtual environment named ‘myenv’ in your current directory. On windows you can activate your virtual environment using my env\Scripts\activate and for macOS you can use myenv/bin.activate to start your virtual environment. Now you can install async libraries using the command below.
| Async IO in Python |
| pip install aiohttp aioredis |
Here, ‘aiohttp’ is used for HTTP requests and ‘aioredis’ is used for redis operations and much more. Check a simple async io in the python example below.
| Async IO in Python |
| import asyncio
async def hello(): print(“Hello”) await asyncio.sleep(1) print(“World”) asyncio.run(hello()) |
In the following program the code runs and prints “Hello” and then waits for one second. And again it prints “World”.
Async IO in Python: Coroutines
With the help of Async IO in python, it can easily manage concurrent code which performs I/O operations concurrently without blocking. Coroutine is an important part of the Python async IO package.
A coroutine function can suspend its execution in between before reaching the return statement and pass the control to another coroutine task for the time being. We can define a coroutine function using the keyword ‘async def’ syntax.
| Async IO in Python |
| async def my_coroutine():
# Async code here |
Async in IO Python: await/async Keyword
The await keyword in Async IO is used to suspend the execution of the coroutine function. Here, the execution is paused until the result of the asynchronous operation is calculated. And in the meantime other tasks keep on running.
| Async IO in Python |
| async def demo():
# Execution will be paused here and return to demo() when demo1() is ready asy = await demo1() return asy |
Async IO in Python: Event Loop
Let us understand Async IO in the Python event loop with the help of an example below.
| Async IO in Python |
| import asyncio
async def task1(): print(“Event 1 started”) await asyncio.sleep(2) #I/O-bound operation print(“Event 1 completed”) async def task2(): print(“Event 2 started”) await asyncio.sleep(1) # Simulate some I/O-bound operation print(“Event 2 completed”) async def main(): await asyncio.gather(task1(), task2()) # Create and run the event loop asyncio.run(main()) |
Output
| Event 1 started
Event 2 started Event 2 completed Event 1 completed |
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Async IO in Python FAQs
What is Async IO in Python?
Async io is a library package in Python that can be used to write concurrent and asynchronous code using async and wait syntax. It can be imported in Python code using ‘import asyncio’.
What is async IO in Python used for?
Async IO is used when one coroutine function pauses its execution for some IO operation then other tasks can take over and use the CPU
When should I use async IO in Python?
Async IO in python can be used when you are performing some IO operation to help CPU reduce the idle time and make performance more effective.
What are the benefits of Async?
Async IO in Python helps you execute multiple tasks at the same time without blocking the execution of the current code. To use async in Python, functions must be declared with an async keyword.
