Generator functions, iterators, and the yield keyword are fundamental concepts in Python that enable you to generate data incrementally.
Iterators are objects that return one value from a collection at a time. To access each subsequent value, you call the next() method repetitively.
Generator functions create iterators. They are similar to regular functions but contain yield statements. yield behaves like return, but instead of terminating the function, it pauses execution and returns the value.
The yield keyword is used within generator functions. Each time yield is called, the generator function returns the specified value and pauses execution. When the generator is called again, execution resumes from the point where the last yield statement left off.
Consider the following code:
def generate_numbers(): for i in range(5): yield i
This code defines a generator function that yields integers from 0 to 4. When called with next(), the function returns 0, 1, 2, 3, and 4 sequentially.
Generator functions are commonly used:
Generator functions can be controlled to avoid premature exhaustion. For example:
class Bank: def create_atm(self): while True: yield "0"
This code creates an infinite ATM generator. However, you can terminate it by assigning True to self.crisis. This approach is useful for controlling resource availability.
The itertools module provides additional tools for manipulating iterables, such as permutations(), which can generate all possible permutations from a list.
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