We can create functions that do not just return one result but rather an entire sequence of results, by using the yield statement. These functions are called generators. Python contains generator functions, which are an easy way to create iterators and are especially useful as a replacement for unworkably long lists. A generator yields items rather than builds lists. For example, the following code shows why we might choose to use a generator, as opposed to creating a list:

#compares the running time of a list compared to a generator 
import time
#generator function creates an iterator of odd numbers between n and m 
def oddGen(n,m):
    while n<m:
      yield n
      n+=2

#builds a list of odd numbers between n and m 
def oddLst(n,m):
     lst=[]
     while n<m:
        lst.append(n)
        n+=2
     return lst

#the time it takes to perform sum on an iterator
t1=time.time()
sum(oddGen(1,1000000))
print("Time to sum an iterator: %f" % (time.time() - t1))
#the time it takes to build and sum a list
t1=time.time()
sum(oddLst(1,1000000))
print("Time to build and sum a list: %f" % (time.time() - t1))

This prints out the following:

As we can see, building a list to do this calculation takes significantly longer. The performance improvement as a result of using generators is because the values are generated on demand, rather than saved as a list in memory. A calculation can begin before all the elements have been generated and elements are generated only when they are needed.

In the preceding example, the sum method loads each number into memory when it is needed for the calculation. This is achieved by the generator object repeatedly calling the __next__ () special method. Generators never return a value other than None.

Typically, generator objects are used in for loops. For example, we can make use of the oddLst generator function created in the preceding code to print out odd integers between 1 and 10:

for i in oddLst (1,10):print(i)

We can also create a generator expression, which, apart from replacing square brackets with parentheses, uses the same syntax and carries out the same operation as list comprehensions. Generator expressions, however, do not create a list; they create a generator object. This object does not create the data, but rather creates that data on demand. This means that generator objects do not support sequence methods such as append() and insert().

You can, however, change a generator into a list using the list() function: