Optimize function similiar to dict.update() but adds common values

[Gregory Piñero]

Hey guys,

I thought I'd throw this out there since everyone loves optimization
questions (it's true, check out the number of replies to those type of
questions!)

Right now I have a function shown below.  I want to combine two
dictionaries and add the values together where-ever there is overlap. 
I figured this function would be reasonably fast, but I have around 1
million keys in each dictionary (~80% overlap) and it just runs all
night.

So maybe my function is not O(n)?  I really figured it was but maybe
dictionary lookups are O(nlogn)?

Anyway here is the function.  Any ideas on doing this task a lot
faster would be appriciated.

Thanks!

<code apology=sorry if gmail kills my tabs>

def add_freqs(freq1,freq2):
    """Add two word freq dicts"""
    newfreq={}
    for key,value in freq1.items():
        newfreq[key]=value+freq2.get(key,0)
    for key,value in freq2.items():
        newfreq[key]=value+freq1.get(key,0)
    return newfreq

freq1={
'dog':1,
'cat':2,
'human':3
}
freq2={
'perro':1,
'gato':1,
'human':2
}
print add_freqs(freq1,freq2)

answer_I_want={
'dog':1,
'cat':2,
'perro':1,
'gato':1,
'human':5
}
</code>


--
Gregory Piñero
Chief Innovation Officer
Blended Technologies
(www.blendedtechnologies.com)