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  1. Practice
  2. Python
  3. Basic Data Types
  4. Find the Runner-Up Score!
  5. Discussions

Find the Runner-Up Score!

  • vartaks + 5 comments

    Even more Pythonic way to do it would be as follows:

    N = int(raw_input())

    arr = map(int, raw_input().split())

    print max([x for x in arr if x != max(arr)])

    • paul_schmeida + 2 comments

      I think "pythonic" is an overused word :) Anyways I did a profile on those two implementations:

      from profilehooks import profile


@profile
def snd_largest_0():
    n, a = int(raw_input()), list(set([int(x) for x in raw_input().split()]))
    return sorted(a)[len(a)-2]


@profile
def snd_largest_1():
    n = int(raw_input())
    arr = map(int, raw_input().split())
    return max([x for x in arr if x != max(arr)])


print snd_largest_0()
print snd_largest_1()

      *** PROFILER RESULTS ***
snd_largest_0 (E:/python_projects/hello_world/second_largest.py:6)
function called 1 times

         7 function calls in 1.633 seconds

   Ordered by: cumulative time, internal time, call count

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    1.633    1.633 second_largest.py:6(snd_largest_0)
        2    1.633    0.816    1.633    0.816 {raw_input}
        1    0.000    0.000    0.000    0.000 {sorted}
        1    0.000    0.000    0.000    0.000 {method 'split' of 'str' objects}
        1    0.000    0.000    0.000    0.000 {len}
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
        0    0.000             0.000          profile:0(profiler)


*** PROFILER RESULTS ***
snd_largest_1 (E:/python_projects/hello_world/second_largest.py:12)
function called 1 times

         12 function calls in 1.862 seconds

   Ordered by: cumulative time, internal time, call count

   ncalls  tottime  percall  cumtime  percall filename:lineno(function)
        1    0.000    0.000    1.862    1.862 second_largest.py:12(snd_largest_1)
        2    1.862    0.931    1.862    0.931 {raw_input}
        1    0.000    0.000    0.000    0.000 {map}
        6    0.000    0.000    0.000    0.000 {max}
        1    0.000    0.000    0.000    0.000 {method 'split' of 'str' objects}
        1    0.000    0.000    0.000    0.000 {method 'disable' of '_lsprof.Profiler' objects}
        0    0.000             0.000          profile:0(profiler)


Process finished with exit code 0

      My code read everything in one go then just returns and every function or method is called only once (total of 7 function calls).

      Your code on the other hand has 12 function calls and calls max() for every element in the list. Also, according to PEP, variable names should start with lowercase, so N should be n.

      I suppose I could use map to change list elements to int, but in this case list comprehension is almost as fast.

      • vartaks + 0 comments

        Thanks for the clear and concise comparison!

      • tarathedev + 0 comments

        Is there a reason you wouldn't just store max(arr) in a separate variable first and use that in the list comprehension so that it's not called multiple times? Seems like a simple solution to reduce the number of calls.

    • gabrielsuprememe + 0 comments

      I did mine similarly, but with filter.

      input()
a = map(int, raw_input().split())
max_value = max(a)
a = filter(lambda x: x != max_value, a)
print max(a)

    • vjay_b5 + 0 comments

      This wont work in python 3 , but works in python 2

    • Duboyal2 + 0 comments
      [deleted]

    • Midge + 2 comments

      Does anybody know why this doesn't work in Python 3?

      When you put in 6 instead of max(arr) it works, but not if you put max(arr):

      N = int(raw_input())
arr = map(int, raw_input().split())
print max([x for x in arr if x != 6])

      ^ works