Creando un iterador



In [5]:

    
class ThingIterator(object):
    def __init__(self, thing):
        self.thing = thing
        self.index = 0
    
    def __iter__(self):
        return self
    
    def next(self):
        if self.index >= len(self.thing.data):
            raise StopIteration
            
        retval = self.thing.data[self.index]
        self.index += 1
        return retval ** 2
    
    # python3 way
    __next__ = next 

class Thing(object):
    def __init__(self, data):
        self.data = data
        
    def __iter__(self):
        return ThingIterator(self)
    
    def iter_squares(self):
        return ThingIterator(self)
        
def iter_squares(x):
    return x.iter_squares()
    
t = Thing([1, 2, 3])
for x in t.iter_squares():
    print(x)

Generadores

Los generadores son funciones que se comportan como iteradores, evitando al programador escribir el código de soporte que hemos visto en la sección anterior. Esto es gracias a la palabra reservada yield que permite al generador emitir un valor sin terminar.



In [24]:

    
def more():
    yield 20
    yield 300
    yield 4000
    
for x in more():
    print(x)



In [7]:

    
def get_squares(seq):
    for x in seq:
        yield x ** 2
        
for x in get_squares([1, 2, 3]):
    print(x)



In [9]:

    
for x in get_squares(xrange(1, 4)):
    print(x)



In [14]:

    
gen = get_squares([1, 2, 3])
print(gen)
print(gen.next())
print(gen.next())









    



<generator object get_squares at 0x7f4db07f54b0>
1
4

generator expressions

Son equivalentes la comprensión de listas para generadores.



In [16]:

    
gen = (x ** 2 for x in [1, 2, 3])
print(gen)









    



<generator object <genexpr> at 0x7f4db07f54b0>



In [19]:

    
sum(x**2 for x in xrange(100) if x % 2)









    Out[19]:





166650

`itertools`

Es un módulo con unas cuantas utilidades interesantes implementadas como iteradores. Aquí vemos algunas:



In [4]:

    
import itertools as it



In [5]:

    
x = it.count(5, 3)
print(x.next())
print(x.next())
print(x.next())
print(x.next())



In [6]:

    
x = it.cycle([2, 4, 8])
print(x.next())
print(x.next())
print(x.next())
print(x.next())



In [7]:

    
for x in it.repeat("a", 5):
    print(x)









    



a
a
a
a
a



In [8]:

    
for x in it.chain("foo", "bar", "bizz"):
    print(x)









    



f
o
o
b
a
r
b
i
z
z

imap() e ifilter() son versiones lazy de map() y filter().



In [9]:

    
for x in it.takewhile(lambda x: x<5, [1,4,6,4,1]):
    print(x)

1
4



In [12]:

    
for x in it.dropwhile(lambda x: x<5, [1,4,6,4,1]):
    print(x)



In [16]:

    
print([str.join('', list(x)) for x in it.product('ABCD', repeat=2)])









    



['AA', 'AB', 'AC', 'AD', 'BA', 'BB', 'BC', 'BD', 'CA', 'CB', 'CC', 'CD', 'DA', 'DB', 'DC', 'DD']



In [17]:

    
for i,j in it.product(range(5), repeat=2):
    print(i, j)









    



(0, 0)
(0, 1)
(0, 2)
(0, 3)
(0, 4)
(1, 0)
(1, 1)
(1, 2)
(1, 3)
(1, 4)
(2, 0)
(2, 1)
(2, 2)
(2, 3)
(2, 4)
(3, 0)
(3, 1)
(3, 2)
(3, 3)
(3, 4)
(4, 0)
(4, 1)
(4, 2)
(4, 3)
(4, 4)



In [ ]: