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Summary - Greedy

Print the greedy coin change solution in a mini task.

Summary - Greedy

Greedy is a simple approach that picks the local best each step and never backtracks. It is optimal on standard coin systems.

In this mini task you will print the greedy coin change solution; combine all steps.

Greedy is often preferred in practice because it is fast and simple; but it is not always optimal.

Practice Print greedy

Write greedy_print(coins, amount). Print the greedy coin count with print(). Output: 6.

Starter code

solution.py
def greedy_print(coins, amount):
    # Print greedy coin count

Sample solution

solution.py
def greedy_print(coins, amount):
    # Print greedy coin count
    coins.sort(reverse=True)
    count = 0
    for coin in coins:
        count += amount // coin
        amount = amount % coin
    print(count)
greedy_print([25, 10, 5, 1], 63)

Expected output

6

Questions and answers

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

1 Summary - Greedy: match the terms

Term Meaning
greedy Local best
coin Coin
amount Amount
optimum Best

2 Counter increment

Question 
count ____ amount // coin
Answer 
count += amount // coin

Explanation: += is right.

3 What is greedy's biggest risk?

  • Being too slow
  • Missing the global optimum Correct answer
  • Memory usage
  • Infinite loop

Explanation: Missing the global optimum.

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