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xrange(stop) -> xrange object
xrange(start, stop[, step]) -> xrange object

Like range(), but instead of returning a list, returns an object that
generates the numbers in the range on demand.  For looping, this is 
slightly faster than range() and more memory efficient.

src/n/a/natsort-3.1.1/natsort/natsort.py   natsort(Download)
import sys
 
from .py23compat import u_format, py23_basestring, py23_range, py23_str, py23_zip
 
__doc__ = u_format(__doc__) # Make sure the doctest works for either python2 or python3
    # Now convert the numbers to numbers, and leave strings as strings
    s = remove_empty(s)
    for i in py23_range(len(s)):
        try:
            s[i] = numconv(s[i])
    item1 = itemgetter(1)
    # Pair the index and sequence together, then sort by
    index_seq_pair = [[x, key(y)] for x, y in py23_zip(py23_range(len(seq)), seq)]
    index_seq_pair.sort(key=lambda x: natsort_key(item1(x), 
                                                  number_type=number_type,

src/n/a/natsort-HEAD/natsort/natsort.py   natsort(Download)
import sys
 
from .py23compat import u_format, py23_basestring, py23_range, py23_str, py23_zip
 
__doc__ = u_format(__doc__) # Make sure the doctest works for either python2 or python3
    # Now convert the numbers to numbers, and leave strings as strings
    s = remove_empty(s)
    for i in py23_range(len(s)):
        try:
            s[i] = numconv(s[i])
    item1 = itemgetter(1)
    # Pair the index and sequence together, then sort by
    index_seq_pair = [[x, key(y)] for x, y in py23_zip(py23_range(len(seq)), seq)]
    index_seq_pair.sort(key=lambda x: natsort_key(item1(x), 
                                                  number_type=number_type,