python generators 2 send and yield

certainly! in python, generators are a special kind of iterator that allow you to iterate over data without storing the entire dataset in memory. they are defined using functions with the yield keyword, which provides a way to produce a series of values lazily.
generators in python can be quite flexible, and two of their more advanced features are the send() method and the yield expression. here’s an overview of how they work:
purpose: the yield expression is used to produce a value from a generator function. when a generator function calls yield, it produces a value and pauses the execution of the generator, saving its state.
how it works: when the generator function is resumed, it continues execution right after the last yield statement. this allows it to produce a sequence of values over time, rather than computing them all at once and storing them in memory.
flow: each time a value is yielded, the generator’s state is preserved, which means it can continue where it left off when requested for the next value.
purpose: the send() method is used to send a value back into a generator that is currently paused at a yield statement. this allows for more interactive communication with the generator.
how it works: when you call send() on a generator, it resumes the generator’s execution from the point where it was paused. the value you send is then received by the yield expression in the generator function.
interaction: this method can be used to send data into the generator and use it within the generator’s execution. it’s useful for scenarios where you need to communicate or update the generator’s state based on external inputs.
bidirectional communication: using send() and yield together allows for bidirectional communication between the generator and the caller. this means that not only can the generator yield values to the caller, but it can also receive values from the caller.
example use case: consider a situation where a generator is used to manage a sequence of ...

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