No loop!
Well at least, no explicit looping...
import itertools
def process(lst):
# Guard clause against empty lists
if len(lst) < 1:
return lst
# use a dictionary here to work around closure limitations
state = { 'prev': lst[0], 'n': 0 }
def grouper(x):
if x < state['prev']:
state['n'] += 1
state['prev'] = x
return state['n']
return [ list(g) for k, g in itertools.groupby(lst, grouper) ]
Usage (work both with Python 2 & Python 3):
>>> data = [45,78,120,47,58,50,32,34]
>>> print (list(process(data)))
[[45, 78, 120], [47, 58], [50], [32, 34]]
Joke apart, if you need to group items in a list itertools.groupby
deserves a little bit of attention. Not always the easiest/best answer -- but worth to make a try...
EDIT: If you don't like closures -- and prefer using an object to hold the state, here is an alternative:
class process:
def __call__(self, lst):
if len(lst) < 1:
return lst
self.prev = lst[0]
self.n = 0
return [ list(g) for k, g in itertools.groupby(lst, self._grouper) ]
def _grouper(self, x):
if x < self.prev:
self.n += 1
self.prev = x
return self.n
data = [45,78,120,47,58,50,32,34]
print (list(process()(data)))
EDIT2: Since I prefer closures ... but @torek don't like the dictionary syntax, here a third variation around the same solution:
import itertools
def process(lst):
# Guard clause against empty lists
if len(lst) < 1:
return lst
# use an object here to work around closure limitations
state = type('State', (object,), dict(prev=lst[0], n=0))
def grouper(x):
if x < state.prev:
state.n += 1
state.prev = x
return state.n
return [ list(g) for k, g in itertools.groupby(lst, grouper) ]
data = [45,78,120,47,58,50,32,34]
print (list(process(data)))