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A Python coroutine function is a specialized function defined using the async def syntax that enables asynchronous, non-blocking execution. Unlike standard synchronous functions, invoking a coroutine function does not immediately execute its internal block of code. Instead, it returns a coroutine object. This object is typically driven to completion by an asynchronous event loop, though at the language level, it is technically driven by calling its .send() method (e.g., .send(None)).

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Syntax and Instantiation

A coroutine function is declared using the async modifier before the def keyword. Inside the function body, the await keyword is used to declare suspension points. 
import asyncio


# This is a coroutine function
async def process_data():
    # The 'await' keyword yields control back to the event loop
    await asyncio.sleep(1)
    return "Success"


# Calling the function returns a coroutine object; it does NOT execute the body
coro_object = process_data()
print(type(coro_object))  # <class 'coroutine'>


# Cleanly discard the unawaited coroutine to prevent a RuntimeWarning

# when the object is garbage collected by the Python interpreter.
coro_object.close()

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Execution Mechanics

To execute the code within a coroutine function, the resulting coroutine object is usually awaited or scheduled as a Task within an event loop.
  1. The await Expression: When the Python interpreter encounters an await expression inside a coroutine function, it suspends the execution of that specific coroutine. Under the hood, await delegates to the .send() method of the awaited object.
  2. Yielding Control: The suspension yields control of the thread back to the caller (typically the event loop), allowing the loop to execute other pending coroutines or tasks.
  3. Resumption: Once the awaited operation resolves, the suspended coroutine function is resumed from the exact point it was paused, preserving its local state and variables.
import asyncio

async def compute_value():
    await asyncio.sleep(1) # Suspension point 1
    return 42

async def main():
    # Awaiting the coroutine object drives it to completion
    # and extracts the underlying return value.
    result = await compute_value() # Suspension point 2
    print(result)


# asyncio.run() initializes the event loop and executes the top-level coroutine
asyncio.run(main())

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Technical Rules and Constraints

  • Awaitables: The await keyword can only be applied to awaitable objects. In Python, the primary awaitables are coroutine objects, asyncio.Task objects, and asyncio.Future objects.
  • Scope Restriction: The await, async for, and async with keywords are syntactically restricted and can only be used within the body of an async def coroutine function. Using them in a standard def function raises a SyntaxError.
  • Return Behavior: While a standard function returns the value specified in its return statement, a coroutine function always returns a coroutine object. The value specified in the return statement becomes the result of the await expression when the coroutine object is eventually evaluated.
  • Generators vs. Coroutines: Under the hood, Python coroutines are built upon the generator infrastructure. However, async def strictly separates coroutines from standard generators (yield). A coroutine function cannot contain a yield statement unless it is specifically designed as an asynchronous generator.
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