How can I get the sum of all values in a list?

FAQ Python FAQ
49 
if sum1 >= sum2:
    return lst1

Same result.

Create a function named larger_sum() that takes two lists of numbers as parameters named lst1 and lst2 .

The function should return the list whose elements sum to the greater number. If the sum of the elements of each list are equal, return lst1 .

50

Ah, yes, I couldn’t see the instructions and my memory of the lesson involved returning something different if the sums were the same. I’ll take the post down.

51

You don’t have to remove your post. It was a valid question.

1 Like
52

In fact, if there is a mistake in that ‘else’ block, our function will not fail if not tested thoroughly.

    return lst1
  else:
    return lst997 # this list is not defined, but the function didn't complain when run our test example

#Uncomment the line below when your function is done
print(larger_sum([1, 9, 5], [2, 3, 7]))
Output:
[1, 9, 5]

My solution is recursive: I had stuck trying to mimic sum() for an unknown me reason:

def larger_sum(lst1, lst2):
  def additionx(lst1): # defining a helper function of my custom sum()
    while len(lst1) > 0: #set the rule of allowed run
      first_element = next(iter(lst1)) #a trick to find 1st element of the list, for..in works too
      if len(lst1) == 1: # set the exit of recursion
        return lst1[0]
      return first_element + additionx(lst1[1:]) #recurse
  if additionx(lst1) >= additionx(lst2): #compare by call of a custom sum()
    return lst1 
  return lst2 #no need of else, due to only one other way out
53

Wow! That is a mountain of code. I hope you were trying to emulate the C program for the sum() function. It’s extreme for Python, to say the least. What, if I may ask is the lesson in that much code?

Well, d’uh? Recursion, of course. Use case analysis would be a good appendix.

55

Right. The recursion is another relative of the for… in loops. The very distant relative who drives Bently and drinks Rooibos tea at 420p.m. So, this sophisticated ‘madam’ who could be as simple as the:

f(n) = 1 + 2 + 3 +………+ n

would look like the:

f(n) = 1 n=1
f(n) = n + f(n-1) n>1

The main difference is that the function “ f( ) ” itself is being called inside the function, so this phenomenon is named as recursion and the function containing recursion is called recursive function, at the end this is a great tool in our hand.

56

Okay, but what of use case analysis? When is it a good time to use it, and when not?

Bottom line, a linear sum is not a use case scenario. Prove this supposition wrong.

1 Like
58

@mtf
I have to say this example had me tracing the control flow for awhile to actually see what was happening. Kudos for the example.

1 Like
59

I was overthinking the solution haha it worked in the end but at times im trying to put everything in ive learned so far instead of keeping it simple and clean.

def larger_sum(lst1, lst2):
  if sum(a for a in lst1) >= sum(b for b in lst2):
    return [a for a in lst1]
  else:
    return [b for b in lst2]

#Uncomment the line below when your function is done
print(larger_sum([1, 9, 5], [2, 3, 7]))
60

the last return is outside so if none of what is true then it runs the outside return