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Parallel Programming with Python
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Understanding the different approaches to task execution is extremely important to model and conceive a scalable solution. Knowing when to use asynchronous, blocking, and nonblocking operations can make an enormous difference in the response time of a system.
In the case of a blocking operation, we can use the example of attending a customer at a bank counter. When the customer's number is called for attendance, all the attention of the cashier is focused on this specific customer. Until the necessity of the current customer is achieved, the cashier can't attend another customer simultaneously. Now, with this in mind, imagine a bank agency with only two cashiers and an influx of 100 customers per hour; we have then a flow problem. This case illustrates the blocking of processing, when a task needs to wait for another to end, blocking the access to resources.
In the blocking of processing...
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