why is xrange able to go back to beginning in Python?

Question

I've encountered this code from Most pythonic way of counting matching elements in something iterable

r = xrange(1, 10) print sum(1 for v in r if v % 2 == 0) # 4 print sum(1 for v in r if v % 3 == 0) # 3 

r is iterated once. and then it's iterated again. I thought if an iterator is once consumed then it's over and it should not be iterated again.

Generator expressions can be iterated only once:

r = (7 * i for i in xrange(1, 10)) print sum(1 for v in r if v % 2 == 0) # 4 print sum(1 for v in r if v % 3 == 0) # 0 

enumerate(L) too:

r = enumerate(mylist) 

and file object too:

f = open(myfilename, 'r') 

Why does xrange behave differently?

Answer 1

Because xrange does not return a generator. It returns an xrange object.

>>> type(xrange(10)) <type 'xrange'> 

In addition to repeated iteration, xrange objects support other things that generators don't -- like indexing:

>>> xrange(10)[5] 5 

They also have a length:

>>> len(xrange(10)) 10 

And they can be reversed:

>>> list(reversed(xrange(10))) [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] 

In short, xrange objects implement the full sequence interface:

>>> import collections >>> isinstance(xrange(10), collections.Sequence) True 

They just do it without using up a lot of memory.

Note also that in Python 3, the range object returned by range has all the same properties.

Answer 2

Because the xrange object produced by calling xrange() specifies an __iter__ that provides a unique version of itself (actually, a separate rangeiterator object) each time it's iterated.

>>> x = xrange(3) >>> type(x) <type 'xrange'> >>> i = x.__iter__() >>> type(i) <type 'rangeiterator'>