The yield statement in Python is used within a function to create a generator. A generator is a special type of iterator that allows you to iterate through a sequence of values, producing them one at a time, only when requested. This is different from returning all values at once.

Basics of yield

When a function includes the yield statement, it becomes a generator function. Calling this function does not execute its code immediately. Instead, it returns a generator object. You can then use the next() function on this generator to get the next value produced by the generator.

 

Example 1: Fixed Result Generator

Here’s a simple generator function that yields the same string every time:

def my_generator():     """Generator function that yields the same string when 'next' is called"""     yield "More research is needed…" def main():     # Use the generator and obtain its next value     print("I saved a bunch on the latest A.I.")     print("Unfortunately, all it replies with is", next(my_generator()))     print(next(my_generator()))     print(next(my_generator()))     print() if __name__=="__main__":     main()

 

Output:

I saved a bunch on the latest A.I. Unfortunately, all it replies with is More research is needed... More research is needed... More research is needed...

 

In this example, each call to next(myGenerator()) creates a new generator and yields "More research is needed…".

 

Example 2: Collection Generator

A more practical example of a generator function yields successive elements from a collection:

def my_generator2(my_aliaslist):     """Generator function that yields the same string when 'next' is called"""     yield from my_aliaslist def main():     alias_list = ["monty", "python", "lamer"]     it = my_generator2(alias_list)     print("So, what do you call yourself?")     print(next(it), "?")     print(next(it), "?")     print(next(it), "?") if __name__=="__main__":     main()

 

Output:

So, what do you call yourself? monty ? python ? lamer ?

 

In this example:

• The my_generator2 function takes a list (my_aliaslist) and yields each element one at a time.
• yield from my_aliaslist is a shorthand for yielding each element in my_aliaslist.

Key Points of yield

1. State Retention: Generators retain their state between calls. This means they remember where they left off in the iteration process.
2. Lazy Evaluation: Generators produce items only when requested, which is useful for handling large datasets efficiently.
3. Simplified Code: Using yield can make code more readable and maintainable compared to manually managing an iterator.