Adds to Melange a tags framework based on taggable-mixin.
The taggable-mixin allowed only tag per Datastore model. This is extended
framework allows any arbitrary number of tags per Datastore model. Also,
now one can define different models for different Tag types which are all
inherited from the base Tag model provided by taggable-mixin.
The GHOPTask model makes use of 2 tags per model, one for difficulty and the
other for task_type, both using the tags framework.
Reviewed by: Paweł Sołyga
"""
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