asyncio exceptions

Extending asyncio

Writing a Custom Event Loop

asyncio is a Python module that provides support for asynchronous programming. An event loop is a central component of asyncio that manages the execution of coroutines.

To create a custom event loop, you can inherit from the asyncio.BaseEventLoop class. This class provides many common methods that you can use to implement your own event loop.

However, you will need to implement some private methods that are not provided by the asyncio.BaseEventLoop class. These methods are considered internal and are not documented.

Future and Task Private Constructors

asyncio.Future and asyncio.Task are classes that represent future results and tasks, respectively. These classes should not be created directly. Instead, you should use the loop.create_future and loop.create_task methods to create new instances.

However, third-party event loops may reuse the built-in future and task implementations to get a complex and highly optimized code for free.

For this purpose, the following private constructors are listed:

  • asyncio.Future.__init__

  • asyncio.Task.__init__

Real World Complete Code Implementations

Here is an example of how to write a custom event loop:

import asyncio

class MyEventLoop(asyncio.BaseEventLoop):

    def _make_socket_transport(self, sock, protocol, waiter=None,
                               extra=None, server=None):
        return MySocketTransport(sock, protocol, waiter, extra, server)

class MySocketTransport(asyncio.BaseTransport):

    def get_extra_info(self, name, default=None):
        return self.extra.get(name, default)

asyncio.set_event_loop(MyEventLoop())

You can use this custom event loop by calling asyncio.set_event_loop(MyEventLoop()) before running any asyncio code.

Potential Applications in Real World

Custom event loops can be used to improve the performance of asyncio applications in a number of ways. For example, a custom event loop could be used to:

  • Optimize the handling of I/O operations

  • Provide support for different types of I/O devices

  • Implement custom scheduling algorithms

Conclusion

Extending asyncio can be a powerful way to customize the behavior of asyncio applications. By writing a custom event loop, you can improve the performance and functionality of your applications.

asyncio-exceptions Module

The asyncio-exceptions module provides exception classes used by the asyncio module.

Exceptions

CancelledError:

  • Raised when a task is cancelled.

  • Child tasks of a cancelled task are also cancelled.

async def task_a():
    await asyncio.sleep(1)
    print("task_a completed")

async def task_b():
    task = asyncio.create_task(task_a())
    task.cancel()
    try:
        await task
    except CancelledError:
        print("task_a cancelled")

IncompleteReadError:

  • Raised when a StreamReader stream is closed before all bytes are read.

  • The remaining bytes can be retrieved using StreamReader.at_eof().

async def read_data():
    reader = asyncio.StreamReader()
    data = await reader.read(1024)
    if reader.at_eof():
        print("Incomplete read: expected 1024 bytes, got", len(data))

IncompleteWriteError:

  • Raised when a StreamWriter stream is closed before all bytes are written.

  • The remaining bytes can be retrieved using StreamWriter.get_extra_info("buffer").

async def write_data():
    writer = asyncio.StreamWriter()
    data = b"hello world"
    await writer.write(data)
    writer.close()
    if writer.get_extra_info("buffer"):
        print("Incomplete write: expected", len(data), "bytes, got", len(data) - len(writer.get_extra_info("buffer")))

InvalidStateError:

  • Raised when a Future or Task is in an invalid state, such as when it is cancelled after being completed.

async def task_c():
    task = asyncio.create_task("hello")
    task.cancel()
    try:
        await task
    except InvalidStateError:
        print("task_c cancelled after being completed")

LimitOverrunError:

  • Raised when a call to gather() or wait() exceeds the maximum number of simultaneous tasks.

  • The default limit is 1024, but can be adjusted using asyncio.set_event_loop_policy().

async def task_d():
    await asyncio.sleep(1)
    return "task_d completed"

async def main():
    await asyncio.gather(*[task_d() for _ in range(1025)])

Real-World Applications

  • CancelledError: Used to handle tasks that have been cancelled explicitly or due to an error.

  • IncompleteReadError: Used to handle situations where a network connection might be closed before all data is received.

  • IncompleteWriteError: Used to handle situations where a network connection might be closed before all data is sent.

  • InvalidStateError: Used to handle unexpected states in asyncio tasks.

  • LimitOverrunError: Used to prevent overloading the event loop with too many simultaneous tasks.

Method: Future.init

Simplified Explanation:

A future is a placeholder for a value that will be available in the future. When you create a future, you can specify an event loop, which is like a thread that waits for events and performs actions. Without an event loop, the future will not be able to complete.

Code Snippet:

# Example 1: Create a future without an event loop
future = asyncio.Future()

# Example 2: Create a future with an event loop
loop = asyncio.new_event_loop()
future = asyncio.Future(loop=loop)

Real-World Example:

Suppose you are downloading a file. You can create a future to represent the file. When the download is complete, you can set the future's value to the downloaded file. This allows other parts of your program to wait for the file to become available without blocking.

Potential Applications:

  • Waiting for the completion of asynchronous operations, such as network requests or database queries.

  • Coordinating work between different parts of a program.

asyncio-exceptions

asyncio-exceptions is a module in the asyncio library that defines exceptions related to asynchronous programming.

Exception Classes

  • IncompleteReadError: Raised when an incomplete read operation is attempted.

  • IncompleteWriteError: Raised when an incomplete write operation is attempted.

  • CancelledError: Raised when an asyncio task is cancelled.

  • TimeoutError: Raised when an asyncio operation times out.

  • ConnectionResetError: Raised when a network connection is reset.

  • ConnectionAbortedError: Raised when a network connection is aborted.

  • ConnectionRefusedError: Raised when a network connection is refused.

  • ConnectionClosedError: Raised when a network connection is closed.

Usage

You can use these exceptions to handle errors in your asynchronous code. For example:

async def my_async_function():
    try:
        # Do some asynchronous operations
        pass
    except asyncio.IncompleteReadError:
        # Handle incomplete read error
        pass
    except asyncio.TimeoutError:
        # Handle timeout error
        pass

Real-World Examples

  • IncompleteReadError: This exception can be raised when reading from a socket or file descriptor that doesn't have enough data available.

  • TimeoutError: This exception can be raised when a network operation takes too long to complete.

  • ConnectionResetError: This exception can be raised when a network connection is abruptly terminated.

Potential Applications

These exceptions can be used to handle a variety of errors that can occur in asynchronous programming, such as:

  • Identifying and handling incomplete or timed-out network operations

  • Detecting and handling network connection issues

  • Handling unexpected errors during asynchronous operations

Improved Examples

Below are some improved code snippets that demonstrate how to use asyncio exceptions:

async def read_data_from_socket():
    try:
        data = await asyncio.read(socket, 1024)
        if len(data) == 0:
            raise asyncio.IncompleteReadError("Socket closed")
    except asyncio.IncompleteReadError as e:
        # Handle incomplete read error
        print(f"Incomplete read: {e}")
    except asyncio.TimeoutError as e:
        # Handle timeout error
        print(f"Timeout: {e}")

async def make_network_request():
    try:
        response = await asyncio.get(url, timeout=10)
    except asyncio.TimeoutError:
        # Handle timeout error
        print("Timeout while making network request")
    except asyncio.ConnectionResetError:
        # Handle connection reset error
        print("Connection reset while making network request")

Creating a Task

A task is a way to run a coroutine (a Python function that can be paused and resumed) in a separate thread. You can create a task using the Task constructor, passing in the coroutine you want to run.

import asyncio

async def my_coroutine():
    # Do something

# Create a task to run the coroutine
task = asyncio.Task(my_coroutine())

# Run the event loop
asyncio.run(task)

You can also specify the event loop you want to use with the loop parameter, and the name of the task with the name parameter.

Task Lifetime Support

If you're using a third-party task implementation, you need to call the following functions to keep the task visible to asyncio.all_tasks() and asyncio.current_task().

def set_task_name(task, name):
    # Set the name of the task

def set_task_context(task, context):
    # Set the context of the task

def get_task_name(task):
    # Get the name of the task

def get_task_context(task):
    # Get the context of the task

Real World Applications

Tasks are used in a variety of real-world applications, including:

  • Web servers: Tasks can be used to handle incoming HTTP requests.

  • Databases: Tasks can be used to execute database queries.

  • Background tasks: Tasks can be used to perform long-running operations in the background.

Potential Applications

Here are some potential applications for tasks:

  • Creating a web server that can handle multiple requests at the same time.

  • Running a database that can execute queries concurrently.

  • Performing a long-running operation in the background, such as sending an email or downloading a file.

_register_task(task)

Purpose:

Registers a new task that will be managed by asyncio. This function is called by task constructors.

How it works:

When a task is created, it needs to be registered with asyncio so that it can be tracked and managed. This function does the registration.

Simplified Example:

async def my_task():
    pass

 asyncio._register_task(my_task())

Potential Applications:

  • Handling asynchronous tasks in web servers or network applications

  • Implementing custom asynchronous schedulers or job queues

  • Creating custom event loops or managing tasks across multiple event loops

Real-World Example:

Asynchronous Web Server:

In an asynchronous web server, tasks are created to handle incoming requests. These tasks need to be registered with asyncio so that the server can track their progress and perform cleanup when necessary. The _register_task() function is used to accomplish this.

import asyncio

async def handle_request(request):
    # Process the request asynchronously...
    pass

async def main():
    server = await asyncio.start_server(handle_request, '127.0.0.1', 8080)

    # Register all tasks created by the server
    for task in asyncio.all_tasks():
        asyncio._register_task(task)

    await server.serve_forever()

asyncio.run(main())

Unregistering a Task from asyncio

When a task in asyncio is about to finish, it needs to be unregistered from the asyncio internal structures. This is done using the _unregister_task() function.

How does it work?

Inside asyncio, tasks are tracked using a data structure called the task queue. When a task is created, it is added to the task queue. When the task finishes, it is removed from the task queue.

The _unregister_task() function is called when a task is about to finish. It removes the task from the task queue and updates other internal structures to reflect that the task has finished.

Why is it important?

Unregistering a task is important because it allows asyncio to keep track of the tasks that are currently running. This information is used to manage the event loop and to ensure that all tasks are completed before the event loop exits.

Real-World Example

A simple example of how to use the _unregister_task() function is shown below:

import asyncio

async def main():
    task = asyncio.create_task(do_something())
    await task
    _unregister_task(task)

async def do_something():
    await asyncio.sleep(1)

asyncio.run(main())

In this example, the main() function creates a task and waits for it to finish. Once the task is finished, the _unregister_task() function is called to remove the task from the asyncio internal structures.

Potential Applications

The _unregister_task() function can be used in a variety of applications, including:

  • Managing the event loop

  • Tracking the progress of tasks

  • Canceling tasks

  • Debugging asyncio applications

_enter_task function:

  • Simplified explanation: It switches the current task to the given task.

  • Detailed explanation: In asyncio, a task is a unit of work that is executed concurrently. The _enter_task function is called just before executing a portion of embedded coroutine (a function that yields control using yield keyword). It sets the current task to the given task, so that any awaitable objects (e.g., I/O operations) scheduled within the coroutine will be executed on behalf of the given task.

Code snippet:

async def my_coroutine():
    await asyncio.sleep(1)  # This I/O operation will be executed on behalf of the task that calls my_coroutine()

async def main():
    task = asyncio.create_task(my_coroutine())
    await _enter_task(task)
    # Execute a portion of my_coroutine() on behalf of the task
    await _leave_task(task)

Real-world applications:

  • Executing I/O operations in a non-blocking manner.

  • Running multiple tasks concurrently and coordinating their execution.

Additional notes:

  • The _leave_task function is used to switch back to the previous task.

  • The asyncio.current_task() function can be used to get the current task.

  • Tasks can be cancelled using the asyncio.Task.cancel() method.

Simplified Explanation of _leave_task() Function:

Imagine you have hired a group of people to work on different tasks. One person, called the "current task," is responsible for doing a specific task at the moment.

The _leave_task() function is like telling the "current task" to stop working and hand over the control to another task. This is useful when the "current task" has finished its job or if it needs to be paused for some reason.

Code Snippet:

def _leave_task(loop, task):
    """Switch the current task back from *task* to ``None``."""

Parameters:

  • loop: The event loop that is managing the tasks.

  • task: The task that is currently being executed.

Real-World Applications:

  • Task Management: In a web server, each incoming HTTP request can be handled by a different task. When the server receives a new request, it can create a new task and assign it to handle the request. The _leave_task() function would be used when the task has finished processing the request, allowing the server to move on to the next request.

  • Error Handling: If a task encounters an error, it can use the _leave_task() function to hand over control to a special error-handling task. This allows the error to be logged or an appropriate response to be generated.

Conclusion:

The _leave_task() function is a critical part of asynchronous programming in Python. It allows the event loop to efficiently switch between tasks and handle errors gracefully.

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