The purpose of this tutorial is to demonstrate how to create a Counter Queue to process large amounts of data. We will use Python to demonstrate the basic concepts of creating a queue. If you have an existing application where you need to process a large amount of data, a counter queue can be very useful in that situation.
In this tutorial, we will use a queue to demonstrate how to handle large amounts of data. You can use a queue to handle large amounts of data by placing a count of the number of items in the queue on the front of the queue. This method will allow the processor to access the first item in the queue and remove it, then the next, and so on. A counter queue is useful when you want to process a large amount of data, but only want to process one item at a time.
In another words, A counter queue is a data structure that is used to keep track of how many times a word or phrase occurs in a text file. This is typically done to avoid having to search through every single word in the text file to count how many times it appears.
A counter queue has the ability to store how many times each element has been added to the queue. This allows the user to search through the elements in the queue and get back a list of the elements that occur the most times in the text file.
There are various ways to implement a queue in Python. Queue in Python can be implemented in the following ways:
- list
- collections.deque
- queue.Queue
Here is the python program for Create a Counter Queue
import threading
import Queue
class ThreadedCount(threading.Thread):
def init (self, name, start, stop):
threading.Thread. init (self)
self.name = name
self.counter = start
self.limit = stop
def run(self):
while self.counter < self.limit:
self.counter += 1
print(self.name, self.counter)
print(self.name , "finished")
return
queue = Queue()
foo = ThreadedCount("Foo", 1, 10)
bar = ThreadedCount("Bar", 1, 10)
foo.start()
bar.start()
print("main - running")
foo.join()
bar.join()
print("main - thread is done")
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