Create distributed applications with clever design patterns to solve complex problemsKey FeaturesSet up and run distributed algorithms on a cluster using Dask and PySpark Master skills to accurately implement concurrency in your code Gain practical experience of Python design patterns with real-world examplesBook DescriptionThis Learning Path shows you how to leverage the power of both native and third-party Python libraries for building robust and responsive applications. You will learn about profilers and reactive programming, concurrency and parallelism, as well as tools for making your apps quick and efficient. You will discover how to write code for parallel architectures using TensorFlow and Theano, and use a cluster of computers for large-scale computations using technologies such as Dask and PySpark. With the knowledge of how Python design patterns work, you will be able to clone objects, secure interfaces, dynamically choose algorithms, and accomplish much more in high performance computing. By the end of this Learning Path, you will have the skills and confidence to build engaging models that quickly offer efficient solutions to your problems. This Learning Path includes content from the following Packt products: Python High Performance - Second Edition by Gabriele LanaroMastering Concurrency in Python by Quan NguyenMastering Python Design Patterns by Sakis KasampalisWhat you will learnUse NumPy and pandas to import and manipulate datasets Achieve native performance with Cython and Numba Write asynchronous code using asyncio and RxPy Design highly scalable programs with application scaffolding Explore abstract methods to maintain data consistency Clone objects using the prototype pattern Use the adapter pattern to make incompatible interfaces compatible Employ the strategy pattern to dynamically choose an algorithmWho this book is forThis Learning Path is specially designed for Python developers who want to build high-performance applications and learn about single core and multi-core programming, distributed concurrency, and Python design patterns. Some experience with Python programming language will help you get the most out of this Learning Path.Table of ContentsBenchmarking and ProfilingPure Python OptimizationsFast Array Operations with NumPy and Pandas C Performance with CythonExploring CompilersImplementing Concurrency Parallel ProcessingAdvanced Introduction to Concurrent and Parallel ProgrammingAmdahl's LawWorking with Threads in PythonUsing the with Statement in ThreadsConcurrent Web RequestsWorking with Processes in PythonReduction Operators in ProcessesConcurrent Image ProcessingIntroduction to Asynchronous ProgrammingImplementing Asynchronous Programming in PythonBuilding Communication Channels with asyncioDeadlocksStarvationRace ConditionsThe Global Interpreter Lock The Factory PatternThe Builder PatternOther Creational PatternsThe Adapter PatternThe Decorator PatternThe Bridge PatternThe Facade PatternOther Structural PatternsThe Chain of Responsibility PatternThe Command PatternThe Observer Pattern
✔ Author(s): Dr. Gabriele Lanaro,Quan Nguyen,Sakis Kasampalis
✔ Title: Advanced Python Programming: Build high performance, concurrent, and multi-threaded apps with Python using proven design patterns
✔ Rating : 4.1 out of 5 base on (40 reviews)
✔ ISBN-10: 1838551212
✔ Language: English
✔ Format ebook: PDF, EPUB, Kindle, Audio, HTML and MOBI
✔ Device compatibles: Android, iOS, PC and Amazon Kindle
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