36. Priority queues and heaps - Part A - Data Structures and Algorithms in Python
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36. Priority queues and heaps - Part A

36. Priority queues and heaps - Part A

The chapter discusses the implementation of priority queues and heaps, essential data structures for managing jobs with varying priorities within a scheduling system. It introduces the concept of a priority queue, explains the operations involved, and highlights the advantages of implementing heaps for more efficient processing times. Through the exploration of heaps as binary trees, the chapter details their structural and functional properties that allow for efficient insertion and maximum deletion operations.

17 sections

Sections

Navigate through the learning materials and practice exercises.

  1. 36.1
    Priority Queues And Heaps

    This section explores priority queues and heaps, essential data structures...

  2. 36.2
    Job Scheduler

    The job scheduler manages a list of jobs with varying priorities, selecting...

  3. 36.2.1
    Operations On Priority Queue

    This section discusses how priority queues operate, focusing on their data...

  4. 36.2.2
    Unsorted Vs Sorted

    This section discusses the differences between unsorted and sorted data...

  5. 36.3
    Two Dimensional Structures

    This section discusses priority queues and heaps, emphasizing how they...

  6. 36.3.1

    This section introduces binary trees as fundamental data structures and...

  7. 36.3.2
    Heap As A Binary Tree

    A heap is a balanced binary tree used for implementing priority queues,...

  8. 36.4
    Heap Properties

    This section discusses heap properties, focusing on the importance of heaps...

  9. 36.4.1
    Structural Property

    This section discusses priority queues, heaps, and the structural properties...

  10. 36.4.2
    Value Property

    This section introduces priority queues and heaps, detailing their structure...

  11. 36.5
    Examples Of Heaps

    This section explains the concept of heaps as a special kind of priority...

  12. 36.5.1
    Correct Examples

    This section discusses priority queues and heaps, detailing their properties...

  13. 36.5.2
    Incorrect Examples

    This section introduces incorrect heap structures, emphasizing the...

  14. 36.6
    Inserting Values Into A Heap

    This section covers the concept of inserting values into a heap while...

  15. 36.6.1
    Restoring Heap Property

    This section discusses the concept of a heap as a specific binary tree...

  16. 36.7
    Adding To A Heap

    This section introduces the concept of heaps, a specific type of binary tree...

  17. 36.7.1
    Balancing After Addition

    This section discusses priority queues and heaps in the context of job...

What we have learnt

  • A priority queue selects jobs based on priority rather than arrival time.
  • Heaps are a special kind of binary tree that maintains a balanced structure for efficient operations.
  • The two main operations in priority queues are insertion and deletion of maximum elements, both of which can be optimized using heaps.

Key Concepts

-- Priority Queue
A data structure that selects the next job to execute based on priority rather than the order of arrival.
-- Heap
A type of binary tree used to implement priority queues that maintains a specific structural and value-based property.
-- Max Heap Property
A property of a heap where each parent node has a value greater than or equal to its child nodes.
-- Binary Tree
A data structure consisting of nodes, where each node has up to two children, often used to model hierarchical relationships.

Additional Learning Materials

Supplementary resources to enhance your learning experience.