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Speed Up Your Python with Rust

You're reading from  Speed Up Your Python with Rust

Product type Book
Published in Jan 2022
Publisher Packt
ISBN-13 9781801811446
Pages 384 pages
Edition 1st Edition
Languages
Author (1):
Maxwell Flitton Maxwell Flitton
Profile icon Maxwell Flitton
Toc

Table of Contents (16) Chapters close

Preface 1. Section 1: Getting to Understand Rust
2. Chapter 1: An Introduction to Rust from a Python Perspective 3. Chapter 2: Structuring Code in Rust 4. Chapter 3: Understanding Concurrency 5. Section 2: Fusing Rust with Python
6. Chapter 4: Building pip Modules in Python 7. Chapter 5: Creating a Rust Interface for Our pip Module 8. Chapter 6: Working with Python Objects in Rust 9. Chapter 7: Using Python Modules with Rust 10. Chapter 8: Structuring an End-to-End Python Package in Rust 11. Section 3: Infusing Rust into a Web Application
12. Chapter 9: Structuring a Python Flask App for Rust 13. Chapter 10: Injecting Rust into a Python Flask App 14. Chapter 11: Best Practices for Integrating Rust 15. Other Books You May Enjoy

Building a model in NumPy

In this section, we are going to build a basic mathematical model to demonstrate the power that NumPy has apart from speed. We are going to use matrices to make a simple model. To achieve this, we will have to carry out the following steps:

  1. Define our model.
  2. Build a Python object that executes our model.

Let's look at these steps in detail in the following subsections.

Defining our model

A mathematical model is essentially a set of weights that calculate an outcome based on inputs. Before we go any further, we must remember the scope of this book. We are building a model to demonstrate how to utilize NumPy. If we covered the nuances of mathematical modeling, that would take up the whole book. We will be building a model based on the example discussed in the previous section, but this does not mean that the model defined is an accurate description of the complexity of mathematical modeling. Here are the steps we need to take...

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