generators-python

Generators | Python

In this article, we will learn how to use generators in our programs using python.

Introduction:

Python generators are a simple way of creating iterators. All the work we mentioned above is automatically handled by generators in Python.

Simply speaking, a generator is a function that returns an object (iterator) that we can iterate over (one value at a time).

It is a lengthy process to create iterators. That’s why the generator plays an essential role in simplifying this process. If there is no value found in iteration, it raises StopIteration exception.

Create a generator function:

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

Example:

# A generator function that yields 1 for first time,
# 2 second time and 3 third time
def simpleGeneratorFun():
	yield 1			
	yield 2			
	yield 3			

# Driver code to check above generator function
for value in simpleGeneratorFun():
	print(value)

Generators with a loop:

Normally, generator functions are implemented with a loop having a suitable terminating condition.

Let’s take an example of a generator that reverses a string.

Example:

def rev_str(my_str):
    length = len(my_str)
    for i in range(length - 1, -1, -1):
        yield my_str[i]


# For loop to reverse the string
for char in rev_str("hello"):
    print(char)

Output:

o
l
l
e
h

In this example, we have used the range() function to get the index in reverse order using the for-loop.

See also  Track Phone Number Using Python

Generator Expression:

We can easily create a Generator expression without using any user-defined functions, it is similar to creation of anonymous functions with list comprehension.

Example:

list = [1,2,3,4,5,6]  
  
z = (x**3 for x in list)  
  
print(next(z))  
  
print(next(z))  
  
print(next(z))  
  
print(next(z))  

Output

1
8
27
64
Note:- When we call the next(), Python calls __next__() on the function in which we have passed it as a parameter.

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