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⚙️ How async / await Works Internally (Python – Deep Dive)

This explanation is how Python actually executes async code, not just how to use it.

🧠 FIRST: THE BIG TRUTH

async/await is NOT magic, NOT threads, NOT parallelism.

It is:

• State machines

• Generators

• Event loop scheduling

• Cooperative multitasking

Python rewrites your async code into a controlled pause–resume machine.

1️⃣ What async def REALLY CREATES

async def foo():
    return 42

What you think:

This is a function.

What Python actually does:

This creates a coroutine object, NOT a function call.

coro = foo()
print(type(coro))
# <class 'coroutine'>

⚠️ Nothing runs yet.

2️⃣ Coroutine = Generator on Steroids

Internally, a coroutine behaves like a generator.

Normal generator:

def gen():
    yield 1
    yield 2

Coroutine:

async def coro():
    await something()

Behind the scenes:

• await ≈ yield control back to event loop

• Python converts async def into a state machine

Each await = checkpoint

3️⃣ What Happens at await (CRITICAL)

await asyncio.sleep(1)

Internally:

1. Coroutine pauses execution

2. It yields:

   • “I’m waiting for this future”

3. Event loop:

   • Registers callback

   • Suspends coroutine

4. Event loop switches to another task

👉 No blocking
👉 No sleeping
👉 No thread

4️⃣ Awaitable Objects (The Contract)

You can only await things that are awaitable.

Awaitable types:

• Coroutine

• Task

• Future

All of them implement:

__await__()

Example:

future.__await__()

This returns an iterator that the event loop drives.

5️⃣ Event Loop: The Real Boss 🌀

The event loop runs something like this:

while True:
    ready_tasks = get_ready_tasks()
    for task in ready_tasks:
        run_until_next_await(task)

What “run” means:

• Resume coroutine

• Execute until:

  • It finishes OR

  • Hits await

6️⃣ Task Internals (asyncio.Task)

When you do:

task = asyncio.create_task(coro())

Internally:

• Task wraps coroutine

• Registers it with event loop

• Tracks state

Task states:

• PENDING

• RUNNING

• SUSPENDED (awaiting)

• DONE

Task = coroutine + scheduler metadata

7️⃣ Futures: Promise of a Result

A Future represents:

“A value that will exist later.”

future = loop.create_future()

• Coroutine waits on Future

• Event loop sets result later

• Coroutine resumes

This is how:

• Network I/O

• Timers

• File descriptors
  work internally.

8️⃣ asyncio.sleep() Internals (Example)

await asyncio.sleep(1)

Internally:

1. Create a Future

2. Register timer with event loop

3. Suspend coroutine

4. After 1 second:

   • Event loop sets future result

5. Coroutine resumes

👉 No sleeping thread
👉 No CPU waste

9️⃣ Why Blocking Code BREAKS Async

async def bad():
    time.sleep(2)  # ❌

What happens:

• Event loop cannot switch tasks

• Whole program freezes

Because:

Blocking code never yields control.

Async only works if you cooperate.

🔁 How Multiple Coroutines Run Together

await asyncio.gather(a(), b(), c())

Execution flow:

a starts → awaits
b starts → awaits
c starts → awaits
event loop resumes whichever is ready

⚠️ Only one coroutine runs at a time
⚠️ Switching happens only at await

🔬 Bytecode-Level Insight (Advanced)

Python compiles async functions into:

• GET_AWAITABLE

• SEND

• YIELD_VALUE

Each await becomes:

• Save state

• Yield to loop

• Resume later

This is why async is fast and lightweight.

🧠 Mental Model (Best One)

Think of async as:

A single-threaded CPU running many paused programs, switching only when they agree to pause.

⚖️ Async vs Threads (Internals)

🟨 One-Line Core Truth

async/await is a structured way to pause execution, hand control to an event loop, and resume later without blocking.

🎯 Interview-Grade Answer

Internally, async/await works by transforming coroutines into state machines that cooperatively yield control to an event loop, which schedules and resumes them based on I/O readiness.