What Is Asynchronous Programming?
To understand what Async io Python is, let us first understand what asynchronous programming is: When a program is running asynchronously, it can do multiple things at once. For example, it can download a file while also processing some data. It doesn’t have to wait for one task to finish before starting another.
Asynchronous programming is helpful because it makes programs more efficient. Instead of waiting for one thing to complete, they can keep doing other tasks which makes the program multitasking.
Example of Asynchronous Programming
Still confused what asynchronous programming is? Let us understand it more clearly with a daily life example:
Imagine you’re cooking dinner while also doing your homework. You start cooking pasta, then while it’s boiling, you switch to doing some math problems. You don’t wait for the pasta to finish before doing your homework, Hence, you did two tasks at the same time.
Hope this helps you to understand what basically Asynchronous programming is.
Asynchronous Programming In Python
Asynchronous Programming is also used a lot in Python as it adds on several benefit to the python program:
- Asynchronous programming allows Python programs to execute multiple tasks concurrently. This leads to improved performance, especially when dealing with I/O-bound operations like network requests or file reading/writing. Asynchronous code generally starts a task and moves on to other tasks while waiting for the first task to complete.
- Asynchronous programming also allows you to write non-blocking code. This means that your program doesn’t get stuck while waiting for slow tasks to complete. Instead, it can continue executing other tasks in the meantime while waiting for operations like network requests or database queries to finish.
- Asynchronous programming in Python is well-suited for building scalable applications, especially in server-side programming and web development. It allows servers to handle many concurrent connections without getting stuck while waiting for I/O operations to complete.
- Asynchronous programming enables concurrency, which is the ability to run multiple tasks concurrently that too with a single thread.
- Asynchronous programming in Python is used to write efficient, non-blocking, and scalable code that can handle concurrent tasks effectively.
What Is Asyncio Python
Asyncio stands for Asynchronous I/O. It is basically a Python library that uses Async or Await syntax to write concurrent codes. This library allows developers to write concurrent programming code that can handle multiple tasks simultaneously.
By using Asyncio developers can manage tasks more efficiently leading to improved performance.
How To Import Asyncio In Python Program
The Asyncio library in Python program is imported by using <import Asyncio> syntax. Importing this library helps you to write Asynchronous, efficient, Non-blocking, and scalable code.
Also importing this library helps developers to use the Async and Await functions in the Python program.
Coroutines In Python
Coroutines are an important part of the Python programming language used to make code Asynchronous, so let us understand what coroutines are, how they are used, and a basic syntax to implement Coroutines.
What Is A Coroutine ?
A coroutine in Python is a special type of function that can pause its execution and allow other code to run, making it useful for tasks that involve waiting, like reading from a file or waiting for data from the internet.
Many coroutines can be created and executed at the same time. They have control over when the tasks will be suspended and resumed, allowing them to execute concurrent tasks smoothly.
Functions Used In Coroutine
A coroutine is defined with a asyncio.coroutine function that used the decorator
Apart from this other functions used in Coroutine include:
- <async def> – It is used to define coroutine functions in the program.
- <Await> – This keyword is used with <async def> function to pause the execution of a particular coroutine until a specific task is completed.
- <Async with>- <Async with> is often used within <async def>functions to handle asynchronous resource management. It ensures that the resource is properly managed in an asynchronous environment.
- <Async for> – It is used with <async def> function to form a loop in a Python program.
How To Run A Coroutine In A Python Program
To run a coroutine in a Python program, you need to use an event loop, especially if you’re working with asynchronous programming then using event loop is a must. The event loop is considered as a core of every Asyncio python program.
Let us understand with an example of code how to use an event loop and how to run the coroutine function in a python program.
import asyncio
async def my_name():
print(“hello”)
await asyncio.sleep(2)
print(“My name is Sahil.”)
loop = asyncio.get_event_loop()
loop.run_until_complete(my_coroutine())
So in the above code, The my_name coroutine will print “Hello,” then wait for 2 seconds asynchronously using await asyncio.sleep(2) function, and then will finally print “My name is Sahil.
When you run this code using an event loop (loop.run_until_complete(my_name())), it will execute the coroutine, and you’ll see the output with the delay between the two messages due to the asynchronous sleep operation.
What Is An Event Loop
An event loop in Python is like a traffic controller that manages the flow of tasks and events within an asynchronous program. It’s responsible for handling and coordinating various operations, such as executing coroutines, waiting for I/O operations, and responding to events like user input or timers
Let us understand event loop with a daily life example for better clarity:
Suppose, you have various tasks to complete during the day, such as cooking meals, doing laundry and working on projects.
Just like an event loop manages tasks in a program, you prioritize and schedule these tasks, ensuring they progress without conflicts or delays.
How To Start An Event Loop In Asyncio Python
An Event loop plays an important role in Asyncio Python programming as it manages the flow of events and tasks, preventing conflicts and delays and ensuring the smooth flow of multiple tasks at the same time.
To start an event loop in Asyncio python Programming, asyncio.newevent_loop() function is used.
Why To Get Access To An Event Loop-
There are many reasons why we may want access to the event loop. Let us talk about some important points about why access to the event loop is necessary.
- The event loop is responsible for scheduling and executing asynchronous tasks efficiently. Accessing the event loop allows you to add tasks to the loop and control their execution flow.
- Event loops are essential for handling events triggered by external sources, such as user interactions and network events. Accessing the event loop enables you to respond to events in an asynchronous manner.
- In scenarios requiring concurrency, such as handling multiple I/O-bound tasks simultaneously, the event loop manages task concurrency efficiently. Accessing the event loop allows you to control and coordinate concurrent tasks within your program.
- With access to the event loop, you can control the execution of tasks, including starting and stopping tasks as needed. This level of control is beneficial for managing complex asynchronous workflows.
What Is An Asyncio Task
An Asyncio Task is like a manager for an asynchronous function which is defined by <Async def> in Python. Asyncio tasks are responsible for pausing and continuing their work. It helps asynchronous functions run smoothly and without blocking other tasks, making programs faster and more efficient.
Asyncio Tasks are like a container that holds a coroutine and manages its execution within the Asyncio framework.
How To Create A Task?
To create a task in Asyncio Python you can use the asyncio.create_task() function.
The asyncio.create_task() function accepts a coroutine function and then creates a Task object from this coroutine and returns it.
When Does A Task Run?
A common question after creating a task is how does the task run?
So the answer to this question will be:
When you create a Task in Asyncio for an async function, the event loop knows that it needs to run that job at the right time. The event loop starts executing the coroutine, If the coroutine has an `await` statement, it tells the event loop to pause there and do something else while waiting.
While the coroutine is paused, the event loop switches to run other tasks. This switching allows your program to do multiple things at once. When the awaited operation in the coroutine is done the event loop resumes running the coroutine from where it left off. The Task is considered completed when the coroutine finishes running.
Task Life Cycle
In the Asyncio Python Program, the task life cycle is divided into four parts, which include:
- Created
- Scheduled
- Running
- Completed
How To Check Task Status
After the task is created, you can also check the current status of the task which will tell you whether the task is running, Completed or canceled.
Let us understand how to check the status of each task with an example of code.
- To check if the Task is done-
To check the status of completed tasks you can use done() method which will give output as true or false.
If the task is completed successfully it will return True, otherwise False.
- Check if the Task is canceled:
To check whether the task is canceled or not you can use cancel() method.
The Code will return true if the task is canceled otherwise it will return false.
How To Get A Task Result
For getting the result of the task we can use the Result() method.
For Example:
- If the task was canceled then while using Result() method it will return with the output: CanceledError.
- If the task is not completed yet and in a running state the Result() method will return with InvalidStateError output.
How To Cancel A Task
To cancel a task in the Asyncio Python Program We can use Task.Cancel() method which will cancel the defined task.
The cancel method will return True if the task is canceled successfully otherwise it will return with a False statement.
The task can only be canceled if they are not completed yet, once the Task is completed we cannot cancel it then.
How To Get A Task Name
Assigning a task name becomes important when you have too many tasks defined in a single coroutine.
Task name basically helps us to avoid confusion and enable the seamless flow of tasks.
There are basically two methods to set task names:
- We can set task names while creating a task from the coroutine using the Name function.
For example –
For creating a task from a coroutine we can use the following code:
task = asyncio.create_task(task_coroutine(), name=’MyTask’
The highlighted red part is used after creating a task in a coroutine for creating a task name.
- We can also set the Task name afterwards using Set name() method.
For example:
For creating a Task using Set name() function we can use the below code.
task.set_name(‘MyTask’)
How To Get List Of All Tasks
To get a list of all the tasks in an Asyncio Python program you can simply use Asyncio.All_Task function, which will provide the list of all the tasks in the Asyncio Program.
You can use the below code for getting all the tasks available.
tasks = asyncio.all_tasks()
Run Many Coroutines Concurrently
In Asyncio Python, we can run multiple Coroutines simultaneously; we just have to store all the Coroutines in a single group and then can execute them all together at the same time.
All this can be achieved by using Asyncio.gather() function.
What Is Asyncio.Gather() Function:
asyncio.gather() is a helpful utility function in Asyncio Python that allows the developer to group and run multiple coroutines together at the same time.
Let’s take an example of a code for your better understanding.
asyncio.gather(coro1(), coro2(), coro3())
Here in the above example, asyncio.gather function is used to group and gather all three coroutines together.
What Are Asynchronous Generators
An asynchronous generator in Asyncio Python is a special type of generator that allows you to yield values asynchronously. This means you can use `async for` to iterate over the values produced by the generator, and each value can be generated asynchronously using `await` function.
Let us understand it more clearly with the help of a code:
import asyncio
async def async_counter(limit):
count = 0
while count < limit:
await asyncio.sleep(1)
yield count
count += 1
async def main():
async for value in async_counter(5):
print(value)
asyncio.run(main())
Here, async_counter is an asynchronous generator function that generates numbers from 0 up to a specified limit.
The async for loop in the main function iterates over the values produced by async_counter.
Each value is generated asynchronously with a delay of 1 second between each iteration using await asyncio.sleep(1).
What Are Asynchronous Iterators
An asynchronous iterator in Asyncio Python is an object that implements a specific interface.
An asynchronous iterator must implement the __aiter__() and __anext__() methods.
The __aiter__() method is like a factory that creates an iterator object.
The __anext__() This method is used in asynchronous iterators and is called when you want to move to the next item in the iteration.
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Asyncio Python FAQs
How do you iterate over an asynchronous generator in asyncio?
You can use async for to iterate over values produced by an asynchronous generator in asyncio. For example:
async for items in async_generator().
What is the purpose of asyncio.wait() in Python?
asyncio.wait() is used to wait for a collection of coroutines or for Tasks to complete asynchronously. It is defined by asyncio.wait command.
What is the Global Interpreter Lock (GIL) and how does it affect asyncio?
The Global Interpreter Lock (GIL) in Python limits the execution of multiple threads simultaneously. asyncio works around the GIL by using cooperative multitasking and using single thread, allowing coroutines to switch between tasks efficiently.
