yield Keyword - Python

Last Updated : 07 Apr, 2025

In Python, the yield keyword is used to create generators, which are special types of iterators that allow values to be produced lazily, one at a time, instead of returning them all at once. This makes yield particularly useful for handling large datasets efficiently, as it allows iteration without storing the entire sequence in memory.

Example:

Python

def fun(m):
    for i in range(m):
        yield i  

# call the generator function
for n in fun(5):
    print(n)

Output

Explanation: fun(m) generates numbers from 0 to m-1 using yield. Calling fun(5) returns a generator, which the for loop iterates over, yielding values one by one until completion.

Syntax

def gen_func(m):
for i in range(m):
yield i # Produces values one at a time

Examples of yield in Python

Example 1: Generator functions and yield

Generator functions behave like normal functions but use yield instead of return. They automatically create the __iter__() and __next__() methods, making them iterable objects.

Python

def my_generator():
    yield "Hello world!!"
    yield "GeeksForGeeks"

g = my_generator()
print(type(g))  
print(next(g)) 
print(next(g))

Output

<class 'generator'>
Hello world!!
GeeksForGeeks

Explanation: my_generator() is a generator that yields "Hello world!!" and "GeeksForGeeks", returning a generator object without immediate execution, which is stored in gen.

Example 2: Generating an Infinite Sequence

Here, we generate an infinite sequence of numbers using yield. Unlike return, execution continues after yield.

Python

def infinite_sequence():
    n = 0
    while True:
        yield n
        n += 1

g = infinite_sequence()
for _ in range(10):
    print(next(g), end=" ")

Output

0 1 2 3 4 5 6 7 8 9

Explanation: infinite_sequence() is an infinite generator that starts at 0, yielding increasing numbers. The for loop calls next(gen) 10 times, printing numbers from 0 to 9.

Example 3: Extracting even numbers from list

Here, we are extracting the even number from the list.

Python

def fun(a):
    for n in a:
        if n % 2 == 0:
            yield n

a = [1, 4, 5, 6, 7]
print(list(fun(a)))

Output

[4, 6]

Explanation: fun(a) iterates over the list a, yielding only even numbers. It checks each element and if it's even (num % 2 == 0), it yields the value.

Example 4: Using yield as a boolean expression

yield can be useful in handling large data and searching operations efficiently without requiring repeated scans.

Python

def fun(text, keyword):
    w = text.split()
    for n in w:
        if n == keyword:
            yield True

txt = "geeks for geeks"
s = fun(txt, "geeks")
print(sum(s))

Output

Explanation: fun(text, keyword) is a generator that splits text into words and checks if each word matches keyword. If a match is found, it yields True.

Advantages of using yield

Memory Efficiency: Since the function doesn’t store the entire result in memory, it is useful for handling large data sets.
State Retention: Variables inside the generator function retain their state between calls.
Lazy Evaluation: Values are generated on demand rather than all at once.

Disadvantages of Using yield

Complexity: Using yield can make the code harder to understand and maintain, especially for beginners.
State Management: Keeping track of the generator’s state requires careful handling.
Limited Use Cases: Generators do not support indexing or random access to elements.