In this Python tutorial, we will discuss the **priority queue in python**. Also, We will see these below topics as:

- What is the priority queue in python?
- Python priority queue implementation
- Max priority queue in python
- Priority queue using a python library
- Priority queue implementation using heapq in python
- Python heapq example
- Python Priority Queue vs heapq

**Table of Contents**show

## What is the priority queue in python?

What is the priority queue in python? **A priority queue in python is an advanced type of queue data structure. Instead of dequeuing the oldest element, a priority queue sorts and dequeues elements based on their priorities. A priority queue is commonly used for dealing with scheduling problems. It gives precedence to tasks with higher urgency.**

## Python Priority queue implementation

To **implement a priority queue in Python**, we have to declare an empty Python list into which elements are inserted using the** append() **method of list class. The list is then sorted in ascending order. The While loop is used to retrieve the elements using the **pop()** method.

**Example:**

```
student = []
student.append((5, 'Nick'))
student.append((1, 'Rohan'))
student.append((3, 'Jack'))
student.sort(reverse=True)
while student:
t = student.pop()
print(t)
```

After writing the above code (python priority queue implementation), Ones you will print **” t “** then the output will appear as **“ (1, ‘Rohan’) (3, ‘Jack’) (5, ‘Nick) ”**. Here, the element sorts and dequeue elements based on their priority queue.

You can refer to the below screenshot for **python priority queue** implementation.

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## Max priority queue in Python

Now, let us understand **max priority queue in Python**.

In the **Python max priority queue**, the list will be arranged in descending order of their priority. The While loop is used to retrieve the elements using the **pop(0)** method.

**Example:**

```
student = []
student.append((5, 'Nick'))
student.append((1, 'Rohan'))
student.append((3, 'Jack'))
student.sort(reverse=True)
while student:
t = student.pop(0)
print(t)
```

After writing the above code (max priority queue in python), Ones you will print **“t”** then the output will appear as **“ (5, ‘Nick) (3, ‘Jack’) (1, ‘Rohan’) ”**. Here, the list is sorted in descending order and dequeue elements based on their priority queue.

You can refer to the below screenshot for **max priority queue in python**.

## Priority queue using a Python library

Let us see how we can implement **Priority queue using a Python library**.

Python provides a **built-in** implementation of a priority queue. The queue module is imported and the elements are inserted using the **put() method**. The while loop is used to dequeue the elements using the** get() **method. The time complexity of the **queue.PriorityQueue** class is O(log n).

**Example:**

```
from queue import priorityQueue
q = PriorityQueue()
q.put((10,'Red balls'))
q.put((8,'Pink balls'))
q.put((5,'White balls'))
q.put((4,'Green balls'))
while not q.empty():
item = q.get()
print(item)
```

After writing the above code (priority queue using a python library), Ones you will print **” item “** then the output will appear as **“ (4, ‘Green balls’) (5, ‘White balls’) (8, ‘Pink balls’) (10, ‘Red balls’) ”**. Here, the list is sorted in ascending order and dequeue elements based on their priority queue.

You can refer to the below screenshot for **priority queue using a python library**.

## Priority queue implementation using heapq in python

We can also use **heapq module in python** to implement a **priority queue**. We will **import heapq **from the library and then created an empty list. But heapq only provides the min-heap implementation.

**Example:**

```
import heapq
s_roll = []
heapq.heappush(s_roll,(4, "Tom"))
heapq.heappush(s_roll,(1, "Aruhi"))
heapq.heappush(s_roll,(3, "Dyson"))
heapq.heappush(s_roll,(2, "Bob"))
While s_roll:
deque_r = heapq.heappop(s_roll)
print(deque_r)
```

After writing the above code (priority queue implementation using heapq in python), Ones you will print **” deque_r “** then the output will appear as **“ (1, ‘Aruhi’) (2, ‘Bob’) (3, ‘Dyson’) (4, ‘Tom’) ”**. Here, by using

**heappush()**method of the heapq module, we inserted the elements into the list. While loop is then used to pop elements out.

You can refer to the below screenshot **priority queue implementation using heapq in python**.

## Python heapq example

We will use **heapq class **to implement **heaps in python**. In heapq by default, **min-heap** is implemented by this class.

**Example:**

```
from heapq import heapify, heappush, heappop
heap = []
heapify(heap)
heappush(heap, 5)
heappush(heap, 40)
heappush(heap, 30)
heappush(heap, 50)
print("Minimum value of heap is : "+str(heap[0]))
print("The heap element : ")
for i in heap:
print(i, end = ' ')
print("\n")
element = heappop(heap)
print("The heap element : ")
for i in heap:
print(i, end= ' ')
```

After writing the above code (python heapq example), Ones you will print then the output will appear as **“ Minimum value of heap is : 5 ”**. Here, by using **heappush() **method of the heapq module, we inserted the elements into the heap and it will print the value of the minimum element.

You can refer to the below screenshot **python heapq example**

## Python Priority Queue vs heapq

Priority Queue | heapq |

Queue.PriorityQueue is a thread-safe class | heapq module makes no thread-safety |

In queue.PriorityQueue, you can use the usual queue method put() to add items. | In heapq, you can use the method heappush() to add new items. |

In queue.PriorityQueue, you can use the usual queue method get() to remove. | In heapq, you can use the method heappop() to remove. |

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In this Python tutorial, we have learned about the ** priority queue in python**. Also, We covered these below topics:

- What is the priority queue in python?
- Python priority queue implementation
- Max priority queue in python
- Priority queue using a python library
- Priority queue implementation using heapq in python
- Python heapq example
- Python Priority Queue vs heapq

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