19👍
I’d use itertools.groupby
to group the elements:
lst = sorted(itertools.chain(list_a,list_b), key=lambda x:x['user__id'])
list_c = []
for k,v in itertools.groupby(lst, key=lambda x:x['user__id']):
d = {}
for dct in v:
d.update(dct)
list_c.append(d)
#could also do:
#list_c.append( dict(itertools.chain.from_iterable(dct.items() for dct in v)) )
#although that might be a little harder to read.
If you have an aversion to lambda
functions, you can always use operator.itemgetter('user__id')
instead. (it’s probably slightly more efficient too)
To demystify lambda/itemgetter a little bit, Note that:
def foo(x):
return x['user__id']
is the same thing* as either of the following:
foo = operator.itemgetter('user__id')
foo = lambda x: x['user__id']
*There are a few differences, but they’re not important for this problem
6👍
from collections import defaultdict
from itertools import chain
list_a = [{'user__name': u'Joe', 'user__id': 1},
{'user__name': u'Bob', 'user__id': 3}]
list_b = [{'hours_worked': 25, 'user__id': 3},
{'hours_worked': 40, 'user__id': 1}]
collector = defaultdict(dict)
for collectible in chain(list_a, list_b):
collector[collectible['user__id']].update(collectible.iteritems())
list_c = list(collector.itervalues())
As you can see, this just uses another dict to merge the existing dicts. The trick with defaultdict is that it takes out the drudgery of creating a dict for a new entry.
There is no need to group or sort these inputs. The dict takes care of all of that.
A truly bulletproof solution would catch the potential key error in case the input does not have a ‘user__id’ key, or use a default value to collect up all of the dicts without such a key.