# Links

Go to my solution

Go to the question on LeetCode

# My Thoughts

**What Went Well**

I recently learned about the “key = “ sorting feature and applied it to this problem to solve the question almost instantly.

# Solution Statistics

**Time Spent Coding**

1 minute

**Time Complexity**

O(n log n) - The built-in sort method takes O(n log n) time, resulting in the O(n log n) space complexity.

O(n log n) is the fastest possible runtime for sorting algorithms.

**Space Complexity**

O(1) - The built-in sort method sorts the list in place, resulting in the O(1) space complexity.

**Runtime Beats**

99.99% of other submissions

**Memory Beats**

99.99% of other sumbissions

# Solution

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class Solution:
def kClosest(self, points: List[List[int]], k: int) -> List[List[int]]:
# The sort function sorts each element of the list based off their
# squared sums (x^2 + y^2)
points.sort(key = lambda x: x[0]**2 + x[1]**2)
# We then return from 0 to k elements of the sorted list
return points[:k]