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Published May 4, 2022
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In Python, a generator is a function or expression that will process a given iterable one object at a time, on demand. A generator will return a generator object, which can be cast as a list or some other data structure as appropriate.


Generators are a convenient means of employing iterator functionality within the syntax of a function or expression. One of the main advantages of generators is that they evaluate items on demand, which means only one item is in memory at a time in lieu of the entire sequence (as with a list).

A Generator Function

The following code shows the creation of a generator function. In the function definition, the yield statement is used to return or include an item in the final generator object.

def return_evens(lst):
for l in lst:
if l % 2 == 0:
yield l
eggs = [x for x in range(20)]
# Output: [0, 2, 4, 6, 8, 10, 12, 14, 16, 18]

A Generator Expression

The functionality in the previous example can alternatively be defined as an expression. A generator expression utilizes the same syntax as a list comprehension with parentheses framing the statement instead of square brackets.

eggs = [x for x in range(20)] # a list comprehension
list((x for x in eggs if x % 2 == 0)) # a generator expression

Custom Iteration

A generator object can be incrementally advanced with the next() function. When next() is called the current item is returned and the state is saved.

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