I'm working with a big dictionary and for some reason I also need to work on small random samples from that dictionary. How can I get this small sample (for example of length 2)?
Here is a toy-model:
dy={'a':1, 'b':2, 'c':3, 'd':4, 'e':5}
I need to perform some task on dy which involves all the entries. Let us say, to simplify, I need to sum together all the values:
s=0
for key in dy.key:
s=s+dy[key]
Now, I also need to perform the same task on a random sample of dy; for that I need a random sample of the keys of dy. The simple solution I can imagine is
sam=list(dy.keys())[:1]
In that way I have a list of two keys of the dictionary which are somehow random. So, going back to may task, the only change I need in the code is:
s=0
for key in sam:
s=s+dy[key]
The point is I do not fully understand how dy.keys is constructed and then I can't foresee any future issue
Given your example of:
dy = {'a':1, 'b':2, 'c':3, 'd':4, 'e':5}
Then the sum of all the values is more simply put as:
s = sum(dy.values())
Then if it's not memory prohibitive, you can sample using:
import random
values = list(dy.values())
s = sum(random.sample(values, 2))
Or, since random.sample
can take a set
-like object, then:
from operator import itemgetter
import random
s = sum(itemgetter(*random.sample(dy.keys(), 2))(dy))
Or just use:
s = sum(dy[k] for k in random.sample(dy.keys(), 2))
An alternative is to use a heapq
, eg:
import heapq
import random
s = sum(heapq.nlargest(2, dy.values(), key=lambda L: random.random()))