First common element from two lists

Question

x = [8,2,3,4,5]
y = [6,3,7,2,1]

How to find out the first common element in two lists (in this case, "2") in a concise and elegant way? Any list can be empty or there can be no common elements - in this case None is fine.

I need this to show python to someone who is new to it, so the simpler the better.

UPD: the order is not important for my purposes, but let's assume I'm looking for the first element in x that also occurs in y.

Answer 1

A sort is not the fastest way of doing this, this gets it done in O(N) time with a set (hash map).

>>> x = [8,2,3,4,5]
>>> y = [6,3,7,2,1]
>>> set_y = set(y)
>>> next((a for a in x if a in set_y), None)
2

Or:

next(ifilter(set(y).__contains__, x), None)

This is what it does:

>>> def foo(x, y):
        seen = set(y)
        for item in x:
            if item in seen:
                return item
        else:
            return None


>>> foo(x, y)
2

To show the time differences between the different methods (naive approach, binary search an sets), here are some timings. I had to do this to disprove the suprising number of people that believed binary search was faster...:

from itertools import ifilter
from bisect import bisect_left

a = [1, 2, 3, 9, 1, 1] * 100000
b = [44, 11, 23, 9, 10, 99] * 10000

c = [1, 7, 2, 4, 1, 9, 9, 2] * 1000000 # repeats early
d = [7, 6, 11, 13, 19, 10, 19] * 1000000

e = range(50000) 
f = range(40000, 90000) # repeats in the middle

g = [1] * 10000000 # no repeats at all
h = [2] * 10000000

from random import randrange
i = [randrange(10000000) for _ in xrange(5000000)] # some randoms
j = [randrange(10000000) for _ in xrange(5000000)]

def common_set(x, y, ifilter=ifilter, set=set, next=next):
    return next(ifilter(set(y).__contains__, x), None)
    pass

def common_b_sort(x, y, bisect=bisect_left, sorted=sorted, min=min, len=len):
    sorted_y = sorted(y)
    for a in x:
        if a == sorted_y[min(bisect_left(sorted_y, a),len(sorted_y)-1)]:
            return a
    else:
        return None

def common_naive(x, y):
    for a in x:
        for b in y:
            if a == b: return a
    else:
        return None

from timeit import timeit
from itertools import repeat
import threading, thread

print 'running tests - time limit of 20 seconds'

for x, y in [('a', 'b'), ('c', 'd'), ('e', 'f'), ('g', 'h'), ('i', 'j')]:
    for func in ('common_set', 'common_b_sort', 'common_naive'):        
        try:
            timer = threading.Timer(20, thread.interrupt_main)   # 20 second time limit
            timer.start()
            res = timeit(stmt="print '[', {0}({1}, {2}), ".format(func, x, y),
                         setup='from __main__ import common_set, common_b_sort, common_naive, {0}, {1}'.format(x, y),
                         number=1)
        except:
            res = "Too long!!"
        finally:
            print '] Function: {0}, {1}, {2}. Time: {3}'.format(func, x, y, res)
            timer.cancel()

The test data was:

a = [1, 2, 3, 9, 1, 1] * 100000
b = [44, 11, 23, 9, 10, 99] * 10000

c = [1, 7, 2, 4, 1, 9, 9, 2] * 1000000 # repeats early
d = [7, 6, 11, 13, 19, 10, 19] * 1000000

e = range(50000) 
f = range(40000, 90000) # repeats in the middle

g = [1] * 10000000 # no repeats at all
h = [2] * 10000000

from random import randrange
i = [randrange(10000000) for _ in xrange(5000000)] # some randoms
j = [randrange(10000000) for _ in xrange(5000000)]

Results:

running tests - time limit of 20 seconds
[ 9 ] Function: common_set, a, b. Time: 0.00569520707241
[ 9 ] Function: common_b_sort, a, b. Time: 0.0182240340602
[ 9 ] Function: common_naive, a, b. Time: 0.00978832505249
[ 7 ] Function: common_set, c, d. Time: 0.249175872911
[ 7 ] Function: common_b_sort, c, d. Time: 1.86735751332
[ 7 ] Function: common_naive, c, d. Time: 0.264309220865
[ 40000 ] Function: common_set, e, f. Time: 0.00966861710078
[ 40000 ] Function: common_b_sort, e, f. Time: 0.0505980508696
[ ] Function: common_naive, e, f. Time: Too long!!
[ None ] Function: common_set, g, h. Time: 1.11300018578
[ None ] Function: common_b_sort, g, h. Time: 14.9472068377
[ ] Function: common_naive, g, h. Time: Too long!!
[ 5411743 ] Function: common_set, i, j. Time: 1.88894859542
[ 5411743 ] Function: common_b_sort, i, j. Time: 6.28617268396
[ 5411743 ] Function: common_naive, i, j. Time: 1.11231867458

This gives you an idea of how it will scale for larger inputs, O(N) vs O(N log N) vs O(N^2)