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Advanced Python Programming

Advanced Python Programming - Second Edition

By : Quan Nguyen
4.6 (14)
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Advanced Python Programming

Advanced Python Programming

4.6 (14)
By: Quan Nguyen

Overview of this book

Python's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages. In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level. This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models. The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming. You'll also understand the common problems that cause undesirable behavior in concurrent programs. Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable. By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.
Table of Contents (32 chapters)
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1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

Reactive programming

Reactive programming is a paradigm that aims at building better concurrent systems. Reactive applications are designed to comply with the following requirements exemplified by the reactive manifesto:

  • Responsive: The system responds immediately to the user.
  • Elastic: The system is capable of handling different levels of load and can adapt to accommodate increasing demands.
  • Resilient: The system deals with failure gracefully. This is achieved by modularity and avoiding having a single point of failure (SPOF).
  • Message-driven: The system should not block and take advantage of events and messages. A message-driven application helps achieve all the previous requirements.

The requirements for reactive systems are quite reasonable but abstract, which leads us to a natural question: how exactly does reactive programming work? In this section, we will learn about the principles of reactive programming using the Reactive Extensions for Python (RxPY...

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Advanced Python Programming
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