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Mastering Concurrency in Python: Create faster programs using concurrency, asynchronous, multithreading, and parallel programming
Immerse yourself in the world of Python concurrency and tackle the most complex concurrent programming problems
Key FeaturesExplore the core syntaxes, language features and modern patterns of concurrency in PythonUnderstand how to use concurrency to keep data consistent and applications responsiveUtilize application scaffolding to design highly-scalable programs Book DescriptionPython 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.
Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples.
By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language
What you will learnExplore the concepts of concurrency in programmingExplore the core syntax and features that enable concurrency in PythonUnderstand the correct way to implement concurrencyAbstract methods to keep the data consistent in your programAnalyze problems commonly faced in concurrent programmingUse application scaffolding to design highly-scalable programsWho this book is forThis book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.
Table of ContentsConcurrent and Parallel Programming - An Advanced IntroductionAmdahl’s LawWorking with Threads in PythonUsing the ‘with’ Statement in ThreadsConcurrent Web ScrapingWorking with Processes in PythonThe Reduction Operation in ProcessesConcurrent Image ProcessingIntroduction to Asynchronous I/ Pros and ConsTCP with AsyncioDeadlockStarvationRace ConditionsThe Global Interpreter LockDesigning Lock-Free and Lock-Based Concurrent Data StructuresMemory Models and Operations on Atomic TypesBuilding a Server from ScratchTesting, Debugging, and Scheduling Concurrent Applications
Key FeaturesExplore the core syntaxes, language features and modern patterns of concurrency in PythonUnderstand how to use concurrency to keep data consistent and applications responsiveUtilize application scaffolding to design highly-scalable programs Book DescriptionPython 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.
Mastering Concurrency in Python starts by introducing the concepts and principles in concurrency, right from Amdahl's Law to multithreading programming, followed by elucidating multiprocessing programming, web scraping, and asynchronous I/O, together with common problems that engineers and programmers face in concurrent programming. Next, the book covers a number of advanced concepts in Python concurrency and how they interact with the Python ecosystem, including the Global Interpreter Lock (GIL). Finally, you'll learn how to solve real-world concurrency problems through examples.
By the end of the book, you will have gained extensive theoretical knowledge of concurrency and the ways in which concurrency is supported by the Python language
What you will learnExplore the concepts of concurrency in programmingExplore the core syntax and features that enable concurrency in PythonUnderstand the correct way to implement concurrencyAbstract methods to keep the data consistent in your programAnalyze problems commonly faced in concurrent programmingUse application scaffolding to design highly-scalable programsWho this book is forThis book is for developers who wish to build high-performance applications and learn about signle-core, multicore programming or distributed concurrency. Some experience with Python programming language is assumed.
Table of ContentsConcurrent and Parallel Programming - An Advanced IntroductionAmdahl’s LawWorking with Threads in PythonUsing the ‘with’ Statement in ThreadsConcurrent Web ScrapingWorking with Processes in PythonThe Reduction Operation in ProcessesConcurrent Image ProcessingIntroduction to Asynchronous I/ Pros and ConsTCP with AsyncioDeadlockStarvationRace ConditionsThe Global Interpreter LockDesigning Lock-Free and Lock-Based Concurrent Data StructuresMemory Models and Operations on Atomic TypesBuilding a Server from ScratchTesting, Debugging, and Scheduling Concurrent Applications
448 pages, Kindle Edition
Published November 27, 2018
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March 1, 2019
As the author of the book, I felt obligated to rate this 5 stars (though there are aspects of it that I now see could have been better). Feel free to leave any questions you might have in the comment section!
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