VoltaCode™ - Python Documentation

Generators in Python

Generators in Python are a simple way of creating iterators. They are written like regular functions but use the yield statement instead of return. Generators allow you to generate items only one at a time and only when you ask for it, which is memory efficient for large data sets.

Basic Concept

A generator function is defined like a normal function, but whenever it needs to generate a value, it does so with the yield keyword rather than return. If the body of a def contains yield, the function automatically becomes a generator function.

Simple Generator Example


                    def countdown(n):

                    ㅤwhile n > 0:

                    ㅤㅤyield n

                    ㅤㅤn -= 1



                    for i in countdown(5):

                    ㅤprint(i)



                    # Output:

                    # 5

                    # 4

                    # 3

                    # 2

                    # 1

Generator Expression

Generator expressions are a high performance, memory efficient generalization of list comprehensions and generators.


                    squares = (x**2 for x in range(10))



                    forsquare in squares:

                    ㅤprint(square)



                    # Output: 0, 1, 4, 9, 16, 25, 36, 49, 64, 81

Benefits of Generators

Memory Efficient: They generate items one at a time and only when you ask for it, so they are memory friendly.
Represent Infinite Stream: Generators can represent an infinite stream of data.
Pipelining Generators: You can use multiple generators in a pipeline, which is both memory and CPU efficient.

Pipelining Generators Example


                    def fibonacci():

                    ㅤa, b = 0, 1

                    ㅤwhile True:

                    ㅤㅤyield a

                    ㅤㅤa, b = b, a + b



                    def square(nums):

                    ㅤfor num in nums:

                    ㅤㅤyield num ** 2



                    fib_squares = square(fibonacci())



                    for iin range(10):

                    ㅤprint(next(fib_squares))



                    # Output: 0, 1, 1, 4, 9, 25, 64, 169, 441, 1156

Generators are a powerful feature in Python that provide an efficient way to work with large or infinite sequences of data. They are widely used in data processing, file I/O operations, and in scenarios where memory efficiency is crucial.