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Mastering Concurrency in Python | 19. Testing, Debugging, and Scheduling Concurrent Applications
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Mastering Concurrency in Python is available from:
This is the "Code in Action" video for chapter 19 of Mastering Concurrency in Python by Quan Nguyen, published by Packt. It includes the following topics:
00:12 Blocking scheduler
00:42 Background scheduler
01:07 Executor pool
02:12 Running on the cloud
05:25 Unit testing
05:37 Testing programs concurrently
Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming.
Connect with Packt:
Video created by Quan Nguyen.
This is the "Code in Action" video for chapter 19 of Mastering Concurrency in Python by Quan Nguyen, published by Packt. It includes the following topics:
00:12 Blocking scheduler
00:42 Background scheduler
01:07 Executor pool
02:12 Running on the cloud
05:25 Unit testing
05:37 Testing programs concurrently
Python is one of the most popular programming languages, with numerous libraries and frameworks that facilitate high-performance computing. Concurrency and parallelism in Python are essential when it comes to multiprocessing and multithreading; they behave differently but their common aim is to reduce the execution time. This book serves as a comprehensive introduction to various advanced concepts in concurrent engineering and programming.
Connect with Packt:
Video created by Quan Nguyen.
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