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You're reading from  Advanced Python Programming - Second Edition

Product typeBook
Published inMar 2022
PublisherPackt
ISBN-139781801814010
Edition2nd Edition
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Author (1)
Quan Nguyen
Quan Nguyen
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Quan Nguyen

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.
Read more about Quan Nguyen

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Approaching the readers-writers problem

The readers-writers problem is one of the classic use cases in concurrent programming, illustrating problems that might occur in a concurrent program. Throughout the analysis of the different variations of the readers-writers problem, we will reveal more about starvation, as well as its common causes. We will also simulate the problem in Python so that a deeper understanding of the problem can be gained.

Problem statement

In a readers-writers problem, first and foremost, we have a shared resource, which, in most cases, is a text file. Different threads interact with that text file; each is either a reader or a writer. A reader is a thread that simply accesses the shared resource (the text file) and reads in the data included in that file, while a writer is a thread that accesses, and possibly mutates, the contents of the text file.

We know that writers and readers cannot access the shared resources simultaneously since if a thread is...

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Advanced Python Programming - Second Edition
Published in: Mar 2022Publisher: PacktISBN-13: 9781801814010

Author (1)

author image
Quan Nguyen

Quan Nguyen is a Python programmer and machine learning enthusiast. He is interested in solving decision-making problems under uncertainty. Quan has authored several books on Python programming and scientific computing. He is currently pursuing a Ph.D. degree in computer science at Washington University in St. Louis, researching Bayesian methods in machine learning.
Read more about Quan Nguyen