Python And Rust Can Be Friends: Combine Python’s Comfort with Rust’s Speed

Working with multiple programming languages teaches a software developer that you don’t have to trade off speed for convenience (or vice versa).

Python provides programmers with an agile and convenient programming environment. However, this language lacks fast speed. Reasonably, you might want to speed up your Python code. The great news is that we can leverage Rust and its powerful features for speeding up Python code. On the other hand, Rust can benefit from Python’s ease of use since Python is ahead of the Rust language in terms of simplicity.

In this article, we compare these two languages and explain how developers can get the most out of both.

Rust vs Python: how these programming languages differ

Recently, the popularity of Python has grown and it’s been one of the top trending languages. Statista states that Python is one of the five most utilized programming languages around the globe. Rust, on the other hand, is a relatively new language from Mozilla that combines speed and safety. Rust turned out to be the most loved technology according to the StackOverflow Developer survey 2022.

Here’s a quick overview of the most important differences between Rust and Python:

Ease of code. The primary difference between Rust and Python is that Rust is a compiled language whereas Python is interpreted (although there are efforts underway to compile Python). This means that when you write code in Rust and run it, it will take some time to compile into machine code before being able to run; whereas with Python this happens automatically as part of running your code.

Performance. Rust is faster than Python because it uses static analysis to determine at compile time what memory needs to be allocated. This means that errors related to incorrect memory usage are caught immediately when you compile your code instead of at runtime when your program runs (as happens with Python). This means that Rust programs run faster than equivalent Python programs because they don’t spend time running checks for memory use that don’t need to be made.

Concurrency. Rust uses multiple threads by default, whereas Python does not unless explicitly specified in the program code (through the use of threading). This means that programs written in Rust can take advantage of multiple cores or processors much more easily than those written in Python.

Documentation. Python has much better documentation than Rust. It is easier to grasp, better organized, and more comprehensive. In fact, Python has a larger community that constantly updates the docs, so it’s always fresh and relevant.

Learning Curve. Python is better than Rust for beginners because Python is much more simple and intuitive. On the other hand, Rust takes some time to get used to, especially if you’re not familiar with functional programming.

Python implementations cover a wide range of domains including web development, data analysis, scientific computing, and machine learning. It’s also one of the main languages at Google. Read this post if you want to get the answer to the question: What is Rust used for?

In general, both languages are great. And depending on which, Rust or Python, is your primary language, you should choose between the two – calling Rust from Python or calling Python from Rust.

Rust for Python programmers: call Rust from Python

The Python community has been working on a project called PyO3 to enable Python code to call Rust functions and vice versa. This is especially useful for writing performance-critical parts of your application in Rust. The PyO3 project provides bindings for about 80% of the standard library, so it’s still possible to write a lot of your code in Python. It also provides support for interfacing with C extensions (such as NumPy) from Rust.

PyO3 offers another project, called Maturin. It’s an open-source Python library that provides a bridge between Python and Rust. It allows you to easily create Rust crates with Python-friendly APIs, and use them in your Python programs.

PyO3 also provides mappings between Rust types and Python types. The PyO3 user guide explains how the mapping between the Python types and the Rust types is performed. PyO3 does this automatically enabling you to easily use function arguments of various types.

For more details, an article by Red Hat Developer explains how to speed up Python utilizing Rust by providing Python and Rust code examples.

But what if your primary language is Rust?

Call Python from Rust

One of the cool things about Rust is that it has a lot of libraries for working with other languages. If you’re a Rust developer willing to utilize Python inside a Rust app, the cpython crate is the best way to perform this task. Cpython is a crate that provides bindings for the CPython runtime. The cpython crate also contains some extra functionality that makes it easier to work with Python objects in Rust.

This crate provides a Python interpreter that can be used to run Python code from your Rust program. It also allows you to import Python modules and call functions and classes defined in them.

Conclusion

Given Rust and Python’s strengths, it would be worthwhile to consider the potential of these two languages combined. Such a pairing will likely lead to more efficient applications, for their combined benefits would provide an ideal situation for both general-purpose and high-performance development.

As you can see, there are undisputable benefits to using the Python and Rust languages together, whether you’re a developer or an architect. By learning how to code with both of these languages, you’ll have a greater understanding of their individual strengths, as well as an in-demand skill that others find valuable. Plus, every project is unique and there’s no better way to learn your craft than by taking on real-world problems—and that’s what we encourage you to do!