This solution is really bad, read it in as a dataframe and use a groupby...
I have a nagging feeling there is an easier way to do this, but my quick and dirty solution was
def merge_list1(l):
other_dict = defaultdict(lambda: 0)
for t, c in ((i['thing'], i['count']) for i in l):
other_dict[t] += c
return ({'thing': k, 'count': other_dict[k]} for k in other_dict)
Possibly not even then, it depends on how much you're doing and I feel like the topic at hand might be around that tipping point. We have some rather slow code that, profiling it, turned out to spend something like 60-70% of its time just converting between python types and native types when moving data in and out of the dataframe.