What is the fastest way to find common elements at the beginning of two python lists? I coded it using for loop but I think that writing it with list comprehensions would be faster... unfortunately I don't know how to put a break in a list comprehension. This is the code I wrote:
import datetime
list1=[1,2,3,4,5,6]
list2=[1,2,4,3,5,6]
#This is the "for loop" version, and takes about 60 ms on my machine
start=datetime.datetime.now()
out=[]
for (e1, e2) in zip(list1, list2):
if e1 == e2:
out.append(e1)
else:
break
end=datetime.datetime.now()
print out
print "Execution time: %s ms" % (float((end - start).microseconds) / 1000)
#This is the list-comprehension version, it takes about 15 ms to run,
#but unfortunately returns the wrong result because I can't break the loop.
start=datetime.datetime.now()
out = [ e1 for (e1, e2) in zip(list1, list2) if e1 == e2 ]
end=datetime.datetime.now()
print out
print "Execution time: %s ms" % (float((end - start).microseconds) / 1000)
Are there good solutions also without list comprehensions?
>>> from operator import ne
>>> from itertools import count, imap, compress
>>> list1[:next(compress(count(), imap(ne, list1, list2)), 0)]
[1, 2]
Timings:
from itertools import *
from operator import ne
def f1(list1, list2, enumerate=enumerate, izip=izip):
out = []
out_append = out.append
for e1, e2 in izip(list1, list2):
if e1 == e2:
out_append(e1)
else:
break
return out
def f2(list1, list2, list=list, takewhile=takewhile, izip=izip):
return [i for i, j in takewhile(lambda (i,j):i==j, izip(list1, list2))]
def f3(list1, list2, next=next, compress=compress, count=count, imap=imap,
ne=ne):
return list1[:next(compress(count(), imap(ne, list1, list2)), 0)]
def f4(list1, list2):
out = []
out_append = out.append
i = 0
end = min(len(list1), len(list2))
while i < end and list1[i]==list2[i]:
out_append(list1[i])
i+=1
return out
def f5(list1, list2, len=len, enumerate=enumerate):
if len(list1) > len(list2):
list1, list2 = list2, list1
for i, e in enumerate(list1):
if list2[i] != e:
return list1[:i]
return list1[:]
def f6(list1, list2, enumerate=enumerate):
result = []
append = result.append
for i,e in enumerate(list1):
if list2[i] == e:
append(e)
continue
break
return result
from timeit import timeit
list1 =[1,2,3,4,5,6];list2=[1,2,4,3,5,6]
sol = f3(list1, list2)
for func in 'f1', 'f2', 'f3', 'f4', 'f5', 'f6':
assert eval(func + '(list1, list2)') == sol, func + " produces incorrect results"
print func
print timeit(stmt=func + "(list1, list2)", setup='from __main__ import *')
f1
1.52226996422
f2
2.44811987877
f3
2.04677891731
f4
1.57675600052
f5
1.6997590065
f6
1.71103715897
For list1=[1]*100000+[1,2,3,4,5,6]; list2=[1]*100000+[1,2,4,3,5,6]
with timeit
customized to 100
timings, timeit(stmt=func + "(list1, list2)", setup='from __main__ import list1, list2, f1,f2,f3,f4', number=1000)
f1
14.5194740295
f2
29.8510630131
f3
12.6024291515
f4
24.465034008
f5
12.1111371517
f6
16.6644029617
So this solution by @ThijsvanDien is the fastest, this comes a close second but I still like it for its functional style ;)
But numpy
always wins (you should always use numpy
for things like this)
>>> import numpy as np
>>> a, b = np.array([1,2,3,4,5,6]), np.array([1,2,4,3,5,6])
>>> def f8(a, b, nonzero=np.nonzero):
return a[:nonzero(a!=b)[0][0]]
>>> f8(a, b)
array([1, 2])
>>> timeit(stmt="f8(a, b)", setup='from __main__ import *')
6.50727105140686
>>> a, b = np.array([1]*100000+[1,2,3,4,5,6]), np.array([1]*100000+[1,2,4,3,5,6])
>>> timeit(stmt="f8(a, b)", setup='from __main__ import *', number=1000)
0.7565150260925293
There may be a faster numpy
solution but this shows how fast it is.
>>> from itertools import izip, takewhile
>>> list1=[1,2,3,4,5,6]
>>> list2=[1,2,4,3,5,6]
>>> list(takewhile(lambda (i,j):i==j, izip(list1, list2)))
[(1, 1), (2, 2)]
or
>>> list(takewhile(lambda i,j=iter(list2):i==next(j), list1))
[1, 2]
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