Recently I wrote a quick and dirty script to do some counting and
statistics. When I re-read it a bit later I noticed that I had been
using two different ways to create two-dimensional (default-)dicts. Now
I'm wondering whether one of them is "better" or more pythonic than the
other.
What I did:
ddd_a = collections.defaultdict(set)
ddd_a[(key1, key2)].add(foo)
ddd_b = collections.defaultdict(lambda: collections.defaultdict(set))
ddd_b[key1][key2].add(foo)
Both work as expected.
Trying to think about differences I only noticed that ddd_a more easily
generalises to more dimensions, and ddd_b has the benefit that
ddd_b[key1] is a dict, which might help if one "row" needs to be fed to
a function that expects a dict.
More general ddd_a looks more symmetric (key1 and key2 are exchangeable,
if done consistently) and ddd_b looks more hierarchic (like a tree
traversed from root to leaves where key1, key2 etc. determine which way
to go at each level). ddd_b also is more simmilar to how two-dimensional
lists are done in python.
Any recommendations / comments as to which to prefer?
--
https://mail.python.org/mailman/listinfo/python-list
