Python memory management with list comprehensions

Question

I am trying to do some analytics against a large dictionary created by reading a file from disk. The read operation results in a stable memory footprint. I then have a method which performs some calculations based on data I copy out of that dictionary into a temporary dictionary. I do this so that all the copying and data use is scoped in the method, and would, I had hoped, disappear at the end of the method call.

Sadly, I am doing something wrong. The customerdict definition is as follows (defined at top of .py variable):

customerdict = collections.defaultdict(dict)

The format of the object is {customerid: dictionary{id: 0||1}}

There is also a similarly defined dictionary called allids.

I have a method for calculating the sim_pearson distance (modified code from Programming Collective Intelligence book), which is below.

def sim_pearson(custID1, custID2):
si = []

smallcustdict = {}
smallcustdict[custID1] = customerdict[custID1]
smallcustdict[custID2] = customerdict[custID2]

#a loop to round out the remaining allids object to fill in 0 values
for customerID, catalog in smallcustdict.iteritems():
    for id in allids:
        if id not in catalog:
            smallcustdict[customerID][asin] = 0.0

#get the list of mutually rated items
for id in smallcustdict[custID1]:
    if id in smallcustdict[custID2]:
        si.append(id) # = 1

#return 0 if there are no matches
if len(si) == 0: return 0

#add up all the preferences
sum1 = sum([smallcustdict[custID1][id] for id in si])
sum2 = sum([smallcustdict[custID2][id] for id in si])

#sum up the squares
sum1sq = sum([pow(smallcustdict[custID1][id],2) for id in si])
sum2sq = sum([pow(smallcustdict[custID2][id],2) for id in si])

#sum up the products
psum = sum([smallcustdict[custID1][id] * smallcustdict[custID2][id] for id in si])

#calc Pearson score
num = psum - (sum1*sum2/len(si))
den = sqrt((sum1sq - pow(sum1,2)/len(si)) * (sum2sq - pow(sum2,2)/len(si)))

del smallcustdict
del si
del sum1
del sum2
del sum1sq
del sum2sq
del psum

if den == 0:
    return 0

return num/den

Every loop through the sim_pearson method grows the memory footprint of python.exe unbounded. I tried using the "del" method to explicitly delete local scoped variables.

Looking at taskmanager, the memory is jumping up at 6-10Mb increments. Once the initial customerdict is setup, the footprint is 137Mb.

Any ideas why I am running out of memory doing it this way?

Answer 1

Try changing the following two lines:

smallcustdict[custID1] = customerdict[custID1]
smallcustdict[custID2] = customerdict[custID2]

to

smallcustdict[custID1] = customerdict[custID1].copy()
smallcustdict[custID2] = customerdict[custID2].copy()

That way the changes you make to the two dictionaries do not persist in customerdict when the sim_pearson() function returns.

Answer 2

I presume the issue is here:

smallcustdict[custID1] = customerdict[custID1]
smallcustdict[custID2] = customerdict[custID2]

#a loop to round out the remaining allids object to fill in 0 values
for customerID, catalog in smallcustdict.iteritems():
    for id in allids:
        if id not in catalog:
            smallcustdict[customerID][asin] = 0.0

The dictionaries from customerdict are being referenced in smallcustdict - so when you add to them, you they persist. This is the only point that I can see where you do anything that will persist out of scope, so I would imagine this is the problem.

Note you are making a lot of work for yourself in many places by not using list comps, doing the same thing repeatedly, and not making generic ways to do things, a better version might be as follows:

import collections
import functools
import operator

customerdict = collections.defaultdict(dict)

def sim_pearson(custID1, custID2):

    #Declaring as a dict literal is nicer.
    smallcustdict = {
        custID1: customerdict[custID1],
        custID2: customerdict[custID2],
    }

    # Unchanged, as I'm not sure what the intent is here.
    for customerID, catalog in smallcustdict.iteritems():
        for id in allids:
            if id not in catalog:
                smallcustdict[customerID][asin] = 0.0

    #dict views are set-like, so the easier way to do what you want is the intersection of the two.
    si = smallcustdict[custID1].viewkeys() & smallcustdict[custID2].viewkeys()

    #if not is a cleaner way of checking for no values.
    if not si:
        return 0

    #Made more generic to avoid repetition and wastefully looping repeatedly.
    parts = [list(part) for part in zip(*((value[id] for value in smallcustdict.values()) for id in si))]

    sums = [sum(part) for part in parts]
    sumsqs = [sum(pow(i, 2) for i in part) for part in parts]
    psum = sum(functools.reduce(operator.mul, part) for part in zip(*parts))

    sum1, sum2 = sums
    sum1sq, sum2sq = sumsqs

    #Unchanged.
    num = psum - (sum1*sum2/len(si))
    den = sqrt((sum1sq - pow(sum1,2)/len(si)) * (sum2sq - pow(sum2,2)/len(si)))

    #Again using if not.
    if not den:
        return 0
    else:
        return num/den

Note that this is entirely untested as the code you gave isn't a complete example. However, It should be easy enough to use as a basis for improvement.