📘 Chapter 2: *Asyncio Basics* 🚀

Chapter 2 delves into the foundational aspects of asyncio in Python, focusing on how it enables single-threaded concurrency using coroutines, tasks, and event loops. Here’s a breakdown:


🌀 2.1 Introducing Coroutines
- Coroutines are special Python functions that can pause and resume execution when encountering a potentially long-running task.
- When a coroutine pauses to wait for an operation, other tasks can run concurrently, providing concurrency. 💡
- `async` and `await` are the two essential keywords:
- async defines a function as a coroutine.
- await pauses the coroutine until a result is available from an asynchronous operation.

⚙️ Example of Creating a Coroutine

async def my_coroutine() -> None:
    print("Hello world!")

This is similar to a normal Python function but can pause its execution.


⏳ 2.2 Introducing Long-Running Coroutines with `sleep`
- Asyncio’s sleep function allows us to pause execution, simulating real-world, long-running operations like web requests or database queries 🌐.
- When await asyncio.sleep() is called, other tasks can be executed during the pause.

⚙️ Example of Using asyncio.sleep

async def hello_world_message() -> str:
    await asyncio.sleep(1)
    return "Hello World!"

This coroutine pauses for 1 second before returning "Hello World!". During that second, other coroutines can run concurrently.


🔄 2.3 Running Concurrently with Tasks
- A task is a wrapper around a coroutine that schedules it to run on the event loop 🕑.
- Tasks allow coroutines to be run concurrently, as they don’t block the event loop, unlike await, which pauses until a result is returned.

⚙️ Example of Creating a Task

import asyncio
from util import delay

async def main():
    task = asyncio.create_task(delay(3))
    await task

Here, the task delay(3) runs concurrently, while other code can execute.


⛔ 2.4 Canceling Tasks and Setting Timeouts
- Tasks can be canceled using task.cancel(), raising a CancelledError within the task. If a task is taking too long, we can also set timeouts using asyncio.wait_for 🕒.

⚙️ Example of Cancelling a Task

async def cancel_task(task):
    task.cancel()
    try:
        await task
    except asyncio.CancelledError:
        print("Task was cancelled")

💼 2.5 Tasks, Coroutines, Futures, and Awaitables
- Futures represent a value that will be available in the future but might not exist yet. They are used internally in asyncio and can be awaited 🎯.
- Coroutines and tasks can both be used in await expressions.

⚙️ Example of Working with Futures

from asyncio import Future

my_future = Future()
my_future.set_result(42)
print(my_future.result())  # Outputs: 42

⏱️ 2.6 Measuring Coroutine Execution Time with Decorators
- By using decorators, we can measure the execution time of coroutines for performance analysis. ⌛


⚠️ 2.7 Pitfalls of Coroutines and Tasks
- Be cautious with CPU-bound code inside coroutines, as it will block the event loop.
- Avoid using blocking I/O APIs; use asyncio-compatible libraries to ensure the event loop runs smoothly 🛠️.


🔧 2.8 Accessing and Manually Managing the Event Loop
- You can access the event loop directly using asyncio.get_event_loop(), though asyncio.run() is recommended for running main coroutines.


🛠️ 2.9 Using Debug Mode
- Debug mode helps in identifying long-running coroutines or tasks that block the event loop 🧐. You can enable it with:

python3 -X dev program.py

Or by setting the PYTHONASYNCIODEBUG environment variable.

⚙️ Example of Running in Debug Mode

asyncio.run(main(), debug=True)

#PythonConcurrencyWithAsyncio
#Chapter_02
#Notes #Book