#Get priority queue python how to#
#Get priority queue python code#

However, the list also does not reflect the order in which the assignments have been added to the queue. When you look at the output produced by the print statement in the last line, you may be disappointed because it doesn’t look like the list is really ordered based on the priority numbers of the assignments. Heapq.heappush(pQueue, 'Assignment ' + str(priority))

#Get priority queue python code#

The code starts with an empty list in variable pQueue and then simulates the arrival of 100 assignments with random priority using heappush (…) to add a new assignment to the queue. The reason we defined the highest priority to be given by the number 1 and the lowest priority by the number 9 is that heapq implements a min heap in which heappop (…) always returns the lowest value element according to the < relation in contrast to a max heap in which heappop (…) would always return the highest value element. “Assignment 1” < “Assignment 2” < … < “Assignment 9”. In the following code, we again use strings for representing our assignments and encode the priority in the strings themselves so that their lexicographical order corresponds to their priority, i.e. The heapq module among other things provides a set of functions for adding elements to a list (function heappush (…)) and for removing the first item with highest priority (function heappop (…)). That means we need to make sure we keep the assignments in the queue ordered based on their priority so that taking the first assignment from the queue will be that with the highest priority. Let’s say that instead of performing the assignments in the order in which they arrive (first-in-first-out), the assignments have a priority value between 1 and 9 with 1 meaning highest and 9 meaning lowest priority. The order of processing is based on the business criticallity irrespective of what order they have been added.The idea of a priority queue is that items in the collection are always kept ordered based on their < relation so that when we take the first item from the queue it will always be the one with lowest (or highest) value.įor instance, let’s get back to the example we started this section with of managing a queue of assignments or tasks that need to be performed. This example has multiple threads consuming the jobs, which are processed based on the priority of items in the queue at the time get() was called. *** Now, Processing the job - Developer-Print jobĦ.

*** Now, Processing the job - Business-Report job New job: Business-Critical Job Output *** Now, Processing the job - Business-Critical Job Threading.Thread(target=process_job, args=(q,)), ] Threading.Thread(target=process_job, args=(q,)), Print(f' *** Now, Processing the job - ') # create a priority queue and define the priority # Class to get the priority and description and validate the priorityĭef _init_(self, priority, description): PriorityQueue uses the sort order of the contents of the queue to decide which item to retrieve. For instance, a business critical job running in producton requires highest CPU and precedence over a print something job that a developer wants to print. Sometimes the processing order of the items in a queue needs to be based on priority of those items, rather than just the order they are created or added to the queue.

#Get priority queue python how to#

Finally, we will see how to implement priority queue. The above example shows, that the most recently put into the queue is removed by get.ĥ. The above example uses a single thread to show how the elements are removed from the queue in the same order in which they are inserted.ģ. # if not empty get the numbers from queueĢ. If you do not, you may want to read some of the references before continuing.ġ. Note : This discussion assumes you already understand the general nature of a queue. Locking is generally handled for the caller. between creator and consumer threads safely. Queues can be used to pass data or any wide range of information e.g. The queue module provides a first-in, first-out (FIFO), Last-in, First out (LIFO) data structure suitable for multi-threaded programming.