What Does Python\'s \'send\' Function Do in Generators?

Understanding the Utility of "send" in Python Generators

While the concept of "yield" in Python generators is widely grasped, the purpose of the "send" function remains ambiguous. To clarify, the "send" function allows for the transmission of values into a generator that has recently yielded a value.

Consider the following simplistic example:

<code class="python">def double_inputs():
    while True:
        x = yield
        yield x * 2</code>

Upon creating a generator instance (gen), executing the next(gen) statement initializes the generator and suspends execution at the first "yield" occurrence. Subsequently, invoking gen.send(10) injects the value of 10 into the "yield" variable. The generator then proceeds to return the value 20, representing the result of the multiplication operation.

This ability to pass values into generators using "send" distinguishes it from "yield" which primarily delivers values out of a generator.

A significant application of "send" lies in Twisted's "@defer.inlineCallbacks" decorator. It enables the seamless execution of functions such as:

<code class="python">@defer.inlineCallbacks
def doStuff():
    result = yield takesTwoSeconds()
    nextResult = yield takesTenSeconds(result * 10)
    defer.returnValue(nextResult / 10)</code>

In this example, "takesTwoSeconds" initially returns a "Deferred" object. Twisted assigns this computation to a background thread, and upon completion, the result is injected into the waiting doStuff generator through "send." This mechanism simplifies code structure, allowing for a more linear and comprehensible flow when dealing with asynchronous operations.

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