Iterators & Generators -1

Iterators

We use for statement for looping over a list.

>>> for i in [1, 2, 3, 4]:
...     print i,
...
1
2
3
4

If we use it with a string, it loops over its characters.

>>> for c in "python":
...     print c
...
p
y
t
h
o
n

If we use it with a dictionary, it loops over its keys.

>>> for k in {"x": 1, "y": 2}:
...     print k
...
y
x

If we use it with a file, it loops over lines of the file.

>>> for line in open("a.txt"):
...     print line,
...
first line
second line

So there are many types of objects which can be used with a for loop. These are called iterable objects.
There are many functions which consume these iterables.

>>> ",".join(["a", "b", "c"])
'a,b,c'
>>> ",".join({"x": 1, "y": 2})
'y,x'
>>> list("python")
['p', 'y', 't', 'h', 'o', 'n']
>>> list({"x": 1, "y": 2})
['y', 'x'] 

The Iteraton Protocol

The built-in function iter takes an iterable object and returns an iterator.

>>> x = iter([1, 2, 3])
>>> x
<listiterator object at 0x1004ca850>
>>> x.next()
1
>>> x.next()
2
>>> x.next()
3
>>> x.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration

Each time we call the next method on the iterator gives us the next element. If there are no more elements, it raises a StopIteration.
Iterators are implemented as classes. Here is an iterator that works like built-in xrange function.

class yrange:
    def __init__(self, n):
        self.i = 0
        self.n = n

    def __iter__(self):
        return self

    def next(self):
        if self.i < self.n:
            i = self.i
            self.i += 1
            return i
        else:
            raise StopIteration()

The __iter__ method is what makes an object iterable. Behind the scenes, the iter function calls __iter__ method on the given object.
The return value of __iter__ is an iterator. It should have a next method and raise StopIteration when there are no more elements.
Lets try it out:

>>> y = yrange(3)
>>> y.next()
0
>>> y.next()
1
>>> y.next()
2
>>> y.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 14, in next
StopIteration

Many built-in functions accept iterators as arguments.

>>> list(yrange(5))
[0, 1, 2, 3, 4]
>>> sum(yrange(5))
10

In the above case, both the iterable and iterator are the same object. Notice that the __iter__ method returned self. It need not be the case always.

class zrange:
    def __init__(self, n):
        self.n = n

    def __iter__(self):
        return zrange_iter(self.n)

class zrange_iter:
    def __init__(self, n):
        self.i = 0
        self.n = n

    def __iter__(self):
        # Iterators are iterables too.
        # Adding this functions to make them so.
        return self

    def next(self):
        if self.i < self.n:
            i = self.i
            self.i += 1
            return i
        else:
            raise StopIteration()

If both iteratable and iterator are the same object, it is consumed in a single iteration.

>>> y = yrange(5)
>>> list(y)
[0, 1, 2, 3, 4]
>>> list(y)
[]
>>> z = zrange(5)
>>> list(z)
[0, 1, 2, 3, 4]
>>> list(z)
[0, 1, 2, 3, 4]

Problem 1: Write an iterator class reverse_iter, that takes a list and iterates it from the reverse direction. ::

>>> it = reverse_iter([1, 2, 3, 4])
>>> it.next()
4
>>> it.next()
3
>>> it.next()
2
>>> it.next()
1
>>> it.next()
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
StopIteration