In [12]:

    

# generators are iterables that produce items on demand


    

In [13]:

    

# generators are defined by functions that use yield. the general term for this is "coroutine"


    

In [14]:

    

# yielding can be done anywhere in a function
from random import random

def gen():
    yield 1
    if random() > 0.5:
        yield 2
    yield 3
    
for i in gen():
    print i


    

    




1
3

In [15]:

    

# to get items from a generator, you can iterate over it
g = gen()

for a in g:
    print a


    

    




1
2
3

In [16]:

    

# you can also use next
g = gen()
g.next()


    

    
Out[16]:





1

In [17]:

    

g.next()


    

    
Out[17]:





3

In [18]:

    

g.next()


    

    




---------------------------------------------------------------------------
StopIteration                             Traceback (most recent call last)
<ipython-input-18-d7e53364a9a7> in <module>()
----> 1 g.next()

StopIteration: 

In [19]:

    

# generators don't ever have to terminate
def gen():
    while True:
        yield 0
        yield 1

# this notebook does not run the following code,
# which would go into an infinite loop

g = gen()
[g.next() for i in range(10)]


    

    
Out[19]:





[0, 1, 0, 1, 0, 1, 0, 1, 0, 1]

In [ ]:

    

# generators cannot be reset to an earlier state (e.g., their initial state)
# so you can only iterate over a generator once
# but you can call the coroutine as many times as you want