Book Image

Advanced Python Programming - Second Edition

By : Quan Nguyen
Book Image

Advanced Python Programming - Second Edition

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)
1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

Questions

  1. Identify the best/most appropriate from the data structures covered in this chapter concerning the following use cases:
    1. Mapping items to another set of items (set being used in the most general sense)
    2. Accessing, modifying, and appending elements
    3. Maintaining a collection of unique elements
    4. Keeping track of the minimum/maximum of a set (in the most general sense)
    5. Appending and removing elements at the endpoints of a sequence (in the most general sense).
    6. Fast searching according to some similarity criterion (for example, being used by autocompletion engines).
  2. What is the difference between caching and memoization?
  3. Why are comprehensions and generators (in most situations) more preferred than explicit for loops?
  4. Consider the problem of representing a pairwise association between a set of letters and a set of numbers (for example, a  2, b  1, c  3, and so on), where we need to look at what number a given letter is associated with in our application...