I'm really learning a lot by reading the discussion boards after submitting each of my near-optimal solutions -- especially, optimization. I'm also noticing holes in my toolset. E.g., bitwise -- as we'll see in just a second.

This Leetcode series started after I felt like I wasn't getting that much practical knowledge going over algorithm lectures and books. I knew enough of the basics to start putting solving and basic analysis into practise .. so I did. Solving three problems everyday increase my producivity as well which is a huge bonus.

The most beneficial path to me at this point is to use both types of resources.

Since I have a fixed number that I aim for each day, I am finding myself shying away to the more simple problems but this isn't nesscarily a bad thing. The problems, the research, and the post-solve reading serve as building blocks for taking on the harder ones.

- Single Number II

Problem: Given an array of integers, find the only element that doesn't appear three times.

I knew that the most optimal solution to this problem was going to be by bitwise methods but it wasn't coming to me. My bitwise capabilities feel below par.

I attempted to solve it as best as I could and ended up with a neat linear-time program.

from collections import Counterclass Solution:def singleNumber(self, nums):""":type nums: List[int]:rtype: int"""ints = Counter()maybes = set()for i in nums:maybes.add(i)ints[i] += 1if ints[i] == 3:maybes.remove(i)for i in maybes:return i

For every element in the array, there are a few more Dictionary operations than one might like but they are all constant time, and the code is clean and precise.

Runtime complexity: `O(n)`

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Spacetime complexity: `O(n)`

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- Fibonacci Number

Problem: Given `n`

find the `n`

th Fibonacci number.

It's a shame that this problem doesn't support memoization because that would make it a little more interesting.

As it is, the only mistep you can make is going for a heavy-handed recursive solution. Mine just iterates and adds.

class Solution:def fib(self, N):""":type N: int:rtype: int"""if N == 0:return 0last = 1curr = 1i = 2while i < N:temp = currcurr += lastlast = tempi += 1return curr

A fairly neat solution. Only beaten if you use math which brings a constant runtime. E.g., using a formula for the n^th Fibonacci sequence in terms of the golden ratio.

Runtime complexity: `O(n)`

.

Space complexity: `O(1)`

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- Ransom Note

Problem: Given a ransom note string and a magazine string work out whether the ransom note can be constructed from the magazine.

I first attempted to solve this with a pair of Dictionaries, then a single Dictionary, then I remembered that when dealing with single letters it's usual viable to use an array instead.

import stringclass Solution(object):def canConstruct(self, ransomNote, magazine):""":type ransomNote: str:type magazine: str:rtype: bool"""letters = [0] * 26for i in magazine:letters[string.lowercase.index(i)] += 1for i in ransomNote:letters[string.lowercase.index(i)] -= 1if letters[string.lowercase.index(i)] < 0:return Falsereturn True

Mostly pretty simple solutions today. I worked through some tree problems but ran into some edge cases. Presumably at some point I will post up a whole swathe of tree and graph problems!

Runtime complexity: `O(n)`

.

Spacetime complexity: `O(1)`

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