What is a faster way of merging the values of this Python structure into a single dictionary?
- by jcoon
I've refactored how the merged-dictionary (all_classes) below is created, but I'm wondering if it can be more efficient.
I have a dictionary of dictionaries, like this:
groups_and_classes = {'group_1': {'class_A': [1, 2, 3],
'class_B': [1, 3, 5, 7],
'class_c': [1, 2], # ...many more items like this
},
'group_2': {'class_A': [11, 12, 13],
'class_C': [5, 6, 7, 8, 9]
}, # ...and many more items like this
}
A function creates a new object from groups_and_classes like this (the function to create this is called often):
all_classes = {'class_A': [1, 2, 3, 11, 12, 13],
'class_B': [1, 3, 5, 7, 9],
'class_C': [1, 2, 5, 6, 7, 8, 9]
}
Right now, there is a loop that does this:
all_classes = {}
for group in groups_and_classes.values():
for c, vals in group.iteritems():
for v in vals:
if all_classes.has_key(c):
if v not in all_classes[c]:
all_classes[c].append(v)
else:
all_classes[c] = [v]
So far, I changed the code to use a set instead of a list since the order of the list doesn't matter and the values need to be unique:
all_classes = {}
for group in groups_and_classes.values():
for c, vals in group.iteritems():
try:
all_classes[c].update(set(vals))
except KeyError:
all_classes[c] = set(vals)
This is a little nicer, and I didn't have to convert the sets to lists because of how all_classes is used in the code.
Question: Is there a more efficient way of creating all_classes (aside from building it at the same time groups_and_classes is built, and changing everywhere this function is called)?
