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

Concurrent web requests

In the context of concurrent programming, we can see that the process of making a request to a web server and obtaining the returned response is independent of the same procedure for a different web server. This is to say that we could apply concurrency and parallelism to our ping test application to speed up our execution.

In the concurrent ping test applications that we are designing, multiple HTTP requests will be made to the server simultaneously and the corresponding responses will be sent back to our program, as shown in the following diagram:

Figure 9.4 – Parallel HTTP requests

As we mentioned previously, concurrency and parallelism have significant applications in web development, and most servers nowadays can handle a large number of requests at the same time.

Now, let's see how we can make multiple web requests at the same time, with the help of threading.

Spawning multiple threads

To apply concurrency...