Book Image

High-Performance Computing with Python 3.x [Video]

By : Mohammed Kashif
Book Image

High-Performance Computing with Python 3.x [Video]

By: Mohammed Kashif

Overview of this book

Python is a versatile programming language. Many industries are now using Python for high-performance computing projects. This course will teach you how to use Python on parallel architectures. You'll learn to use the power of NumPy, SciPy, and Cython to speed up computation. Then you will get to grips with optimizing critical parts of the kernel using various tools. You will also learn how to optimize your programmer using Numba. You'll learn how to perform large-scale computations using Dask and implement distributed applications in Python; finally, you'll construct robust and responsive apps using Reactive programming. By the end, you will have gained a solid knowledge of the most common tools to get you started on HPC with Python. All code files are located on GitHub at this link https://github.com/PacktPublishing/High-Performance-Computing-with-Python-3.x
Table of Contents (8 chapters)
Chapter 1
Getting Started with Faster and Efficient Python Code
Content Locked
Section 3
Using Lambda Expressions
Lambda expressions allow us to create function on the go, making our code more efficient. In this section, we will explore how we can use lambda expressions in Python. - Understand what are lambda expressions - Implement anonymous functions using lambda expressions - Combine lambda expressions with other functions for improved functionality