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 concept of a thread

In the field of computer science, a thread of execution is the smallest unit of programming commands (code) that a scheduler (usually as part of an operating system) can process and manage. Depending on the operating system, the implementation of threads and processes (which we will cover in future chapters) varies, but a thread is typically an element (a component) of a process.

Threads versus processes

More than one thread can be implemented within the same process, most often executing concurrently and accessing/sharing the same resources, such as memory; separate processes do not do this. Threads in the same process share the latter's instructions (its code) and context (the values that its variables reference at any given moment).

The key difference between the two concepts is that a thread is typically a component of a process. Therefore, one process can include multiple threads, which can be executing simultaneously. Threads also usually allow for shared resources...