Though I like python very much, When I need to get multiple integer inputs in the same line, I prefer C/C++. If I use python, I use:
a = map(int, raw_input().split())
Is this the only way or is there any pythonic way to do it? And does this cost much as far as time is considered?
Intuitive and pythonic:
a = [int(i) for i in raw_input().split()]
Check out this discussion here: Python List Comprehension Vs. Map
If you're using map with built-in function then it can be slightly faster than LC:
>>> strs = " ".join(str(x) for x in xrange(10**5))
>>> %timeit [int(x) for x in strs.split()]
1 loops, best of 3: 111 ms per loop
>>> %timeit map(int, strs.split())
1 loops, best of 3: 105 ms per loop
With user-defined function:
>>> def func(x):
... return int(x)
>>> %timeit map(func, strs.split())
1 loops, best of 3: 129 ms per loop
>>> %timeit [func(x) for x in strs.split()]
1 loops, best of 3: 128 ms per loop
Python 3.3.1 comparisons:
>>> strs = " ".join([str(x) for x in range(10**5)])
>>> %timeit list(map(int, strs.split()))
10 loops, best of 3: 59 ms per loop
>>> %timeit [int(x) for x in strs.split()]
10 loops, best of 3: 79.2 ms per loop
>>> def func(x):
return int(x)
...
>>> %timeit list(map(func, strs.split()))
10 loops, best of 3: 94.6 ms per loop
>>> %timeit [func(x) for x in strs.split()]
1 loops, best of 3: 92 ms per loop
From Python performance tips page:
The only restriction is that the "loop body" of map must be a function call. Besides the syntactic benefit of list comprehensions, they are often as fast or faster than equivalent use of map.
map returns an iterator in py3x.
mix all these?[e+1 for e in foo if e%3] is the same than map(lambda e: e+1, filter(lambda e: e%3, foo)) but LC are faster in that case (and more Pythonic, isn't it?)You can use this:
s = raw_input().split()
s = [int(i) for i in s]
def pairs(a,k):
answer = 0
s = set(a)
for v in s:
if v+k in s:
answer += 1
return answer
n, k = map(int, raw_input().split())
b = map(int, raw_input().split())
print pairs(b, k)
