All of the ones I have attempted/completed

• isSumEqual.py
• backspaceCompare.py
• intersection_II.py
• isPalindrome.py
• increasingBST.py
• PalindromeLinkedList.py
• maxDepth.py
• countNegatives.py
• isBalanced.py
• checkSortRotate.py
• lengthLastWord.py
• arrayPairSum.py
• runningSum.py
• removeDuplicates.py
• intersection.py
• vowelReverse.py
• diStringMatch.py

• findOrder.py
• minOperations.py
• nonDecreasingArray.py
• maxAncestorDiff.py
• checkInclusion.py
• uglyNumber.py
• matrixScore.py
• courseSchedule.py
• numRescueBoats.py
• alphabetBoardPath.py
• mergeIntervals.py
• leastUniqueInts.py
• maxProfitAssigned.py
• isValid.py
• maximumUniqueSubarray.py
• biggestMountain.py
• minSetSize.py
• checkPow3.py
• spiralMatrix.py
• maxDistance.py
• maxAverageSum.py
• pushDominoes.py
• countBattleships.py
• displayTable.py
• findCenter.py
• LinkedListBinaryTree.py
• canReach.py
• maxProfit.py
• minimumLength.py
• hasAllCodes.py
• kthGrammar.py
• numsSameConsecDiff.py
• maxEvents.py
• 01Matrix.py
• CoinChange.py
• findLongestWord.py
• isValidBST.py
• addTwoNumbers.py
• Notes.md
• maxProductTree.py
• rotateBox.py
• newInterval.py
• kFreqElements.py
• LongestBeautifulSubString.py
• numOfSubarrays.py
• minFallingPathSum.py
• characterReplacement.py
• removeNthNodeFromEnd.py
• DiceTargetSum.py
• countVowelString.py

• uniquePathsIII.py
• minDistance.py
• RussianDolls.py
• mergeKlists.py
• MaxRequests.py
• orderlyQueue.py
• RangeModule.py
• getCoprimes.py
• maxPathSum.py
• isPossible.py

2/6/21 2-Medium/minSetSize.py

One of the weirdest things I've noticed has been dot references outperforming non-dot references. This also includes var = var2 = val notation; typically it has been though that these should yield better performance. This has led me to the conclusion that while non-dots outperform dot references - in a localised system using multiple imports - it makes it easier to recognise which one your are referencing to.

This was highlighted after using minSetSize and noticed the ~200ms difference between dot and non-dot references in favour of dot references.

counter = collections.Counter > counter=Counter

A second note I noticed from the exercise,

list.sort() outperforms list=sorted(list)

9/6/21 3-Hard/mergeKLists.py

I would have liked to implemented a merge sort, as I feel that is what was desired by the question and it feels the most optimal, although it can taken into dispute that it is not better than the current O(n) solution I have implemented as it performs 3 O(n) operations

./update_README.py

Needs a redo