Generators are one of those little things that I love about Python. Never heard of generators? Well, this is all much better explained here, but in a nutshell:
def squares( size ): for x in xrange( size ): yield x * x return
The above code returns a generator object. This object is iterable, and each item is returned by the yield statement. The return statement ends the iteration.
>>> list( squares( 10 ) ) [0, 1, 4, 9, 16, 25, 36, 49, 64, 81] >>> for value in squares( 5 ): ... print value ... 0 1 4 9 16
Now, there’s a little problem I found… I wanted an object than, when iterated, returned a certain sequence of objects. No problem so far. But here’s the catch: once it finished returning the list, I wanted to be able to reuse the generator.
>>> gen = squares( 5 ) >>> list( gen ) # Works the first time... [0, 1, 4, 9, 16] >>> list( gen ) # But not the second! 
So I came up with this solution:
class Regenerator(object): """ Calls a generator and iterates it. When it's finished iterating, the generator is called again. This allows you to iterate a generator more than once (well, sort of, since the generator is actually recreated). """ def __iter__(self): return self def __init__(self, g_function, *v_args, **d_args): self.__g_function = g_function self.__v_args = v_args self.__d_args = d_args self.__g_object = None def next(self): if self.__g_object is None: self.__g_object = self.__g_function( *self.__v_args, **self.__d_args ) try: return self.__g_object.next() except StopIteration: self.__g_object = None raise
So, in the example we presented, this is what we’d do to be able to iterate the list of numbers more than once:
def _squares( size ): for x in xrange( size ): yield x * x return def squares( size ): return Regenerator( _squares, size )
And alas, it works! 🙂
>>> gen = squares( 10 ) >>> list( gen ) [0, 1, 4, 9, 16, 25, 36, 49, 64, 81] >>> list( gen ) [0, 1, 4, 9, 16, 25, 36, 49, 64, 81] >>> list( gen ) [0, 1, 4, 9, 16, 25, 36, 49, 64, 81]