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Speed Up Your Python with Rust

Speed Up Your Python with Rust

By : Maxwell Flitton
4.9 (12)
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Speed Up Your Python with Rust

Speed Up Your Python with Rust

4.9 (12)
By: Maxwell Flitton

Overview of this book

Python has made software development easier, but it falls short in several areas including memory management that lead to poor performance and security. Rust, on the other hand, provides memory safety without using a garbage collector, which means that with its low memory footprint, you can build high-performant and secure apps relatively easily. However, rewriting everything in Rust can be expensive and risky as there might not be package support in Rust for the problem being solved. This is where Python bindings and pip come in. This book will help you, as a Python developer, to start using Rust in your Python projects without having to manage a separate Rust server or application. Seeing as you'll already understand concepts like functions and loops, this book covers the quirks of Rust such as memory management to code Rust in a productive and structured manner. You'll explore the PyO3 crate to fuse Rust code with Python, learn how to package your fused Rust code in a pip package, and then deploy a Python Flask application in Docker that uses a private Rust pip module. Finally, you'll get to grips with advanced Rust binding topics such as inspecting Python objects and modules in Rust. By the end of this Rust book, you'll be able to develop safe and high-performant applications with better concurrency support.
Table of Contents (16 chapters)
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1
Section 1: Getting to Understand Rust
5
Section 2: Fusing Rust with Python
11
Section 3: Infusing Rust into a Web Application

Answers

  1. This is because a String is essentially a pointer to Vec<u8> with some metadata. If we copy this, then we will have multiple unconstrained pointers to the same string literal, which will introduce errors with concurrency, mutability, and lifetimes.
  2. We can use an Enum, which means that the type being accepted into the container can be one of those types housed in the Enum. When reading the data, we can then use a match statement to manage all possible data types that could be read from the container. The second way is to create a trait that multiple different structs implement. However, the only interaction that we can have from the container read when this is the case is the functions that the trait implements.
  3. They both wrap around the code and alter the implementation or attributes of the code that they are wrapping without directly returning anything.
  4. The Python equivalent is if __name__ == "__main__":.
  5. A signed integer must accommodate positive and negative values, whereas an unsigned integer only accommodates positive values.
  6. This is because there is no garbage collection; as a result, variables get deleted when they shift out of the scope of where they were created. If we do not consider lifetimes, we could reference a variable that has been deleted.
  7. No, the ownership of the variable has essentially been moved and there are no references to the original variable anymore.
  8. We can still copy and borrow the original variable; however, we cannot perform a mutable borrow.
  9. We cannot use the original variable at all as the state of the variable might be altered.
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