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Challenge 1

Sort an array with merge sort and print it.

Challenge 1: Merge sort

In this challenge you will sort an array with merge sort and print it. Combine prior skills.

Array: [5, 2, 8, 1, 9]. Sorted output: [1, 2, 5, 8, 9].

Merge sort gives O(n log n) by dividing, sorting recursively and merging.

Practice Merge sort

Write merge_sort(arr). Sort the array with merge sort and return it. Print [1, 2, 5, 8, 9] with print(merge_sort([5, 2, 8, 1, 9])).

Starter code

solution.py
def merge_sort(arr):
    # Sort with merge sort

Sample solution

solution.py
def merge_sort(arr):
    # Sort with merge sort
    if len(arr) <= 1:
        return arr
    mid = len(arr) // 2
    left = merge_sort(arr[:mid])
    right = merge_sort(arr[mid:])
    return merge(left, right)
def merge(left, right):
    result = []
    i = j = 0
    while i < len(left) and j < len(right):
        if left[i] <= right[j]:
            result.append(left[i]); i += 1
        else:
            result.append(right[j]); j += 1
    result.extend(left[i:]); result.extend(right[j:])
    return result
print(merge_sort([5, 2, 8, 1, 9]))

Expected output

[1, 2, 5, 8, 9]

Questions and answers

Review the lesson questions together with their answers. To test yourself, solve the lesson interactively.

1 What is merge sort's complexity?

  • O(n^2)
  • O(n log n) Correct answer
  • O(log n)
  • O(n)

Explanation: O(n log n).

2 Mid index

Question 
mid = len(arr) ____ 2
Answer 
mid = len(arr) // 2

Explanation: // is right.

3 Challenge 1: match the terms

Term Meaning
merge sort Divide merge
O(n log n) Fast
stable Keeps order
divide Split

All lessons in Intermediate

1 Merge sort

  1. Divide and conquer
  2. Merge operation
  3. Full merge sort
  4. Summary - Merge sort

2 Quick sort

  1. Pivot selection
  2. Partitioning
  3. Recursive quick sort
  4. Summary - Quick sort

3 Heap sort

  1. What is a heap?
  2. Heapify
  3. Build heap and sort
  4. Summary - Heap sort

4 Counting sort

  1. Counting idea
  2. Count array
  3. Output array
  4. Summary - Counting sort

5 Radix sort

  1. Radix idea
  2. Digit pass
  3. Stable sub-sort
  4. Summary - Radix sort

6 Sorting project

  1. Project: Overview
  2. Score array
  3. Apply merge sort
  4. Print statistics

7 Tree

  1. What is a tree?
  2. Node and edge
  3. Binary tree
  4. Summary - Trees

8 Binary search tree

  1. BST rule
  2. BST insert
  3. BST search
  4. Summary - BST

9 AVL tree

  1. Balanced tree
  2. Rotation
  3. Balance after insert
  4. Summary - AVL tree

10 Heap

  1. Min and max heap
  2. Insert
  3. Extract
  4. Summary - Heap

11 Priority queue

  1. What is a priority queue?
  2. Heap-based implementation
  3. Push and pop
  4. Summary - Priority queue

12 Data structures project

  1. Project: Overview
  2. Undo stack
  3. Pending queue
  4. Print the state

13 Graph basics

  1. What is a graph?
  2. Adjacency list
  3. Adjacency matrix
  4. Summary - Graph

14 Breadth-first search

  1. BFS idea
  2. Using a queue
  3. Marking visited
  4. Summary - BFS

15 Depth-first search

  1. DFS idea
  2. Stack or recursion
  3. Backtracking
  4. Summary - DFS

16 Greedy algorithms

  1. Greedy approach
  2. Coin change
  3. Greedy limits
  4. Summary - Greedy

17 Divide and conquer

  1. Three steps
  2. Recursive structure
  3. Master theorem
  4. Summary - Divide and conquer

18 Backtracking

  1. What is backtracking?
  2. State tree
  3. Pruning
  4. Summary - Backtracking

19 Graph project

  1. Project: Overview
  2. City graph
  3. BFS for reachability
  4. Print the result

20 Intermediate final

  1. Challenge 1
  2. Challenge 2
  3. Challenge 3
  4. Challenge 4