I have two large files. Their contents looks like this:

134430513
125296589
151963957
125296589

The file contains an unsorted list of ids. Some ids may appear more than one time in a single file.

Now I want to find the intersection part of two files. That is the ids appear in both files.

I just read the two files into 2 sets, s1 and s2. And get the intersection by s1.intersection(s2) . But it consumes a lot of memory and seems slow.

So is there any better or pythonic way to do this? If the file contains so many ids that can not be read into a set with limited memory, what can I do?

EDIT: I read the file into 2 sets using a generator:

def id_gen(path):for line in open(path):tmp = line.split()yield int(tmp[0])c1 = id_gen(path)
s1 = set(c1)

All of the ids are numeric. And the max id may be 5000000000. If use bitarray, it will consume more memory.

Others have shown the more idiomatic ways of doing this in Python, but if the size of the data really is too big, you can use the system utilities to sort and eliminate duplicates, then use the fact that a File is an iterator which returns one line at a time, doing something like:

import os
os.system('sort -u -n s1.num > s1.ns')
os.system('sort -u -n s2.num > s2.ns')
i1 = open('s1.ns', 'r')
i2 = open('s2.ns', 'r')
try:d1 = i1.next()d2 = i2.next()while True:if (d1 < d2):d1 = i1.next()elif (d2 < d1):d2 = i2.next()else:print d1,d1 = i1.next()d2 = i2.next()
except StopIteration:pass

This avoids having more than one line at a time (for each file) in memory (and the system sort should be faster than anything Python can do, as it is optimized for this one task).