On 06Sep2019 22:48, Ralf M. <ral...@t-online.de> wrote:
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?
As you'd imagine, it depends on what yuou're doing.
If (key1,key2) are a Cartesian-like "space" of value, for example the
domain of key2 values it the same regardless of key1, I lean toward
(key1,key2).
If (key1,key2) are a tree like structure such as the clause names and
field values form a .ini config file:
[clause1]
field1 = 1
field2 = 3
[clause2]
field2 = 9
I lean towards the ddd_b[key1][key2] approach.
So: are they a "flat" space or a tree structure? The is my normal rule
of thumb for deciding how to key things.
In particular, if you need to ask "what are the key2 values for
key1==x?" then you might want a tree structure.
The ddd_a (key1,key2) approach is easier to manage in terms of creating
new nodes. OTOH, using a nested defaultdict can handle that work for
you:
ddd_d = defaultdict(lambda: defaultdict(int))
(Pick a suitable type in place of "int" maybe.)
Cheers,
Cameron Simpson <c...@cskk.id.au>
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