Generators are very easy to implement, but a bit difficult to understand.

Generators are used to create iterators, but with a different approach. Generators are simple functions which return an iterable set of items, one at a time, in a special way.

When an iteration over a set of item starts using the for statement, the generator is run. Once the generator's function code reaches a "yield" statement, the generator yields its execution back to the for loop, returning a new value from the set. The generator function can generate as many values (possibly infinite) as it wants, yielding each one in its turn.

Here is a simple example of a generator function which returns 7 random integers:

import random

def lottery():
    # returns 6 numbers between 1 and 40
    for i in xrange(6):
        yield random.randint(1, 40)

    # returns a 7th number between 1 and 15
    yield random.randint(1,15)

for random_number in lottery():
    print "And the next number is... %d!" % random_number

This function decides how to generate the random numbers on its own, and executes the yield statements one at a time, pausing in between to yield execution back to the main for loop.

Write a generator function which returns the Fibonacci series. They are calculated using the following formula: The first two numbers of the series is always equal to 1, and each consecutive number returned is the sum of the last two numbers. Hint: Can you use only two variables in the generator function? Remember that assignments can be done simultaneously. The code

a = 1
b = 2
a, b = b, a

will simultaneously switch the values of a and b.

# fill in this function
def fib():
    pass #this is a null statement which does nothing when executed, useful as a placeholder.

# testing code
import types
if type(fib()) == types.GeneratorType:
    print "Good, The fib function is a generator."

    counter = 0
    for n in fib():
        print n
        counter += 1
        if counter == 10:
            break

Good, The fib function is a generator.
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