Search icon CANCEL
Subscription
0
Cart icon
Cart
Close icon
You have no products in your basket yet
Save more on your purchases!
Savings automatically calculated. No voucher code required
Arrow left icon
All Products
Best Sellers
New Releases
Books
Videos
Audiobooks
Learning Hub
Newsletters
Free Learning
Arrow right icon
Arrow up icon
GO TO TOP
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

Recreating our NumPy model in Rust

Now that we can use our NumPy module in Rust, we need to explore how to structure it so that we can use Python modules to solve bigger problems. We will do this by building a NumPy model with a Python interface. To achieve this, we can break down the processes into functions that can be used as and when we need them. The structure of our NumPy model can be seen here:

Figure 7.6 – Rust NumPy model structure  

Considering the flow of our model structure in the preceding diagram, we can build our NumPy model in Rust with the following steps:

  1. Build get_weight_matrix and inverse_weight_matrix functions.
  2. Build get_parameters, get_times, and get_input_vector functions.
  3. Build calculate_parameters and calculate_times functions.
  4. Add calculate functions to the Python bindings and add a NumPy dependency to our setup.py file.
  5. Build our Python interface.

We can see that each step has dependencies...

lock icon The rest of the chapter is locked
Register for a free Packt account to unlock a world of extra content!
A free Packt account unlocks extra newsletters, articles, discounted offers, and much more. Start advancing your knowledge today.
Unlock this book and the full library FREE for 7 days
Get unlimited access to 7000+ expert-authored eBooks and videos courses covering every tech area you can think of
Renews at $15.99/month. Cancel anytime}