Introduction to Aiosignal

Aiosignal is a powerful Python library designed to provide asynchronous signal handling and execution of callbacks. It’s widely used for creating event-driven systems and efficiently handling various asynchronous operations. In this comprehensive guide, we will explore the versatile APIs of aiosignal and provide detailed code examples to help you master its usage.

Key APIs and Examples

Creating a Signal

First, let’s look at how to create a signal:

  import aiosignal

  signal = aiosignal.Signal()

Connecting to a Signal

To respond to a signal, you need to connect a callback function. Here’s how you can do that:

  async def callback(sender, **kwargs):
      print("Signal received from:", sender)
      print("Additional arguments:", kwargs)

  signal.connect(callback)

Sending a Signal

To send a signal and notify all connected callbacks, use the send method:

  await signal.send(sender="example_sender", arg1="value1", arg2="value2")

Disconnecting from a Signal

If you need to disconnect a callback from a signal:

  signal.disconnect(callback)

Using Context Managers

Aiosignal also allows using context managers for automatically connecting and disconnecting callbacks:

  async with signal.connected(callback):
      await signal.send(sender="context_sender")

Checking if a Callback is Connected

You can check whether a callback is already connected to a signal:

  is_connected = signal.is_connected(callback)

Real-world Application Example

Let’s put it all together into a practical application example. Assume we are building an event-driven application that processes user actions:

  import asyncio
  import aiosignal

  class UserActionProcessor:
      def __init__(self):
          self.action_signal = aiosignal.Signal()

      async def process_action(self, action):
          print(f"Processing action: {action}")
          await self.action_signal.send(sender=self, action=action)

  async def log_action(sender, action):
      print(f"Logged action: {action}")

  async def notify_user(sender, action):
      print(f"Notification sent for action: {action}")

  async def main():
      processor = UserActionProcessor()
      processor.action_signal.connect(log_action)
      processor.action_signal.connect(notify_user)

      await processor.process_action("user_login")
      await processor.process_action("user_logout")

  asyncio.run(main())

This example demonstrates how to use aiosignal to process user actions and respond with multiple callbacks, offering a robust and asynchronous approach to handling complex workflows.

By leveraging aiosignal’s APIs, you can efficiently manage asynchronous operations and build scalable event-driven systems with ease.

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