Book Image

Advanced Python Programming

By : Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis
Book Image

Advanced Python Programming

By: Dr. Gabriele Lanaro, Quan Nguyen, Sakis Kasampalis

Overview of this book

This 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 Lanaro • Mastering Concurrency in Python by Quan Nguyen • Mastering Python Design Patterns by Sakis Kasampalis
Table of Contents (41 chapters)
Title Page
About Packt

The problem of timeout

In this section, we will explore a potential improvement to be made to our ping test application: timeout handling. Timeouts typically occur when the server takes an unusually long time to process a specific request, and the connection between the server and its client is terminated.

In the context of a ping test application, we will be implementing a customized threshold for the timeout. Recall that a ping test is used to determine whether specific servers are still responsive, so we can specify in our program that, if a request takes more than our timeout threshold for the server to response, we will categorize that specific server with a timeout.

Support from and simulation in Python

In addition to different options for status codes, the website additionally provides a way to simulate a delay in its response when we send in requests. Specifically, we can customize the delay time (in milliseconds) with a query argument in our GET request. For...