Extend taggable-mixin to support different Tag models.
Usage is pretty simple. Tag model is default in Taggable constructor but you
can call it with different model like GHOPTaskType that inherits from Tag model.
Both Taggable and Tag models have been updated and they don't use hardcoded Tag
model anymore and instead use cls of class methods or self.__class__. In case
of Taggable it's self.__tag_model.
"""
Providing iterator functions that are not in all version of Python we support.
Where possible, we try to use the system-native version and only fall back to
these implementations if necessary.
"""
import itertools
def compat_tee(iterable):
"""
Return two independent iterators from a single iterable.
Based on http://www.python.org/doc/2.3.5/lib/itertools-example.html
"""
# Note: Using a dictionary and a list as the default arguments here is
# deliberate and safe in this instance.
def gen(next, data={}, cnt=[0]):
dpop = data.pop
for i in itertools.count():
if i == cnt[0]:
item = data[i] = next()
cnt[0] += 1
else:
item = dpop(i)
yield item
next = iter(iterable).next
return gen(next), gen(next)
def groupby(iterable, keyfunc=None):
"""
Taken from http://docs.python.org/lib/itertools-functions.html
"""
if keyfunc is None:
keyfunc = lambda x:x
iterable = iter(iterable)
l = [iterable.next()]
lastkey = keyfunc(l[0])
for item in iterable:
key = keyfunc(item)
if key != lastkey:
yield lastkey, l
lastkey = key
l = [item]
else:
l.append(item)
yield lastkey, l
# Not really in itertools, since it's a builtin in Python 2.4 and later, but it
# does operate as an iterator.
def reversed(data):
for index in xrange(len(data)-1, -1, -1):
yield data[index]
if hasattr(itertools, 'tee'):
tee = itertools.tee
else:
tee = compat_tee
if hasattr(itertools, 'groupby'):
groupby = itertools.groupby
def is_iterable(x):
"A implementation independent way of checking for iterables"
try:
iter(x)
except TypeError:
return False
else:
return True
def sorted(in_value):
"A naive implementation of sorted"
out_value = in_value[:]
out_value.sort()
return out_value