Could Rust Replace Python for High-Performance Computing?
Python is currently the hottest programming language. Developers and programmers love how easy it is to learn and fast to develop applications with. As a result, the language has penetrated almost all use cases, from web apps to scientific analysis.
There’s one area, however, where Python generally lags – high-performance computing. And this is where a relative newcomer, Rust, is slowly taking the helm.
In this post, we’ll compare these two languages side-by-side. We’ll see why, and how, Rust can overtake Python in high-performance applications.
Python is an object-oriented, interpreted programming language created by Guido van Rossum in 1991. It’s arguably one of the most popular languages right now, ranking third on a popularity index by TIOBE in January 2021, behind only Java and C.
Python spent the last 30 years maturing into a capable and flexible high-level scripting language. It’s used in everything from web applications to embedded systems and even scientific applications. Python counts several high-profile companies among its users, notably Google, Netflix, and NASA.
Pros of Python
Python is an old programming language, and that is where its biggest strength lies. Throughout its 30-year existence, it has evolved into a robust and stable platform with significant bugs and inefficiencies already fixed.
The large Python community also means help is readily available when needed. If a developer encounters any issues, the chances are big that someone else has already solved the same problem.
Easy to learn and use
Compared to languages like C and C++, Python is easier to read and understand. As a result, beginners tend to learn the language much faster.
But it’s more than just the syntax that makes Python a great first language to learn. Data types, a learning curve for most novice programmers, are automatically handled by the Python interpreter. This makes debugging programs simple and more straightforward.
It’s Highly Flexible
A consequence of Python’s long life is that it has amassed a vast library of functions for every use case imaginable (over 287,000 as of 2020). This makes the language well-suited to any application without having to code routines from scratch. Whichever the project, there’s bound to be a library that can help.
Fast Development Time
The main benefit of being easy to use and having robust libraries is that Python is a fantastic prototyping tool. Developers can code much faster and with fewer lines of code. From a business standpoint, it means saving on development costs while bringing projects to market much faster.
Cons of Python
It can be slow
Python’s biggest drawback is its speed, and that’s because it’s an interpreted language. Instead of compiling the code, the Python interpreter reads each line of code and executes it immediately. While that methodology has its perks, the additional layer of execution means Python programs run very slow.
On average, executing Python tasks takes significantly longer – as much 2 – 10 times compared to compiled languages.
Python is also much more memory intensive due to its dynamically-typed nature. Since a programmer doesn’t need to specify data types, the interpreter needs to keep all variables in memory, and that eats up space.
It can only execute one task at a time
Python has a GIL (Global Interpreter Lock) in place, which means it cannot run more than one task at a time. This is due to its use of flexible datatypes, which can go awry with parallel processes. Thus, multi-threaded applications generally run slower on Python.
It’s not optimized for mobile app development
With the rise of mobile, developing apps for these platforms is increasingly necessary. Unfortunately for Python, it’s pretty far behind in this regard. Both iOS and Android don’t support Python for their native apps.
That’s not to say that Python can’t be used for creating mobile apps, because it can. There are libraries and frameworks that make use of Python for mobile development. However, it’s not as robust and well-supported compared to mobile-ready languages like React Native and Cordova.
Rust is a multi-paradigm programming language that emphasizes safety and performance. It’s similar in terms of syntax and mechanisms to low-level compiler languages like C and C++, but with the memory management and ease of development features of interpreter languages like Java and Python.
The programming language is relatively new, with a life of a little over ten years. Despite this, Rust has picked up quite a pace and has been voted a favorite among Stack Overflow developers in a 2016 survey.
Pros of Rust
Safety and Reliability
Rust is built with safety in mind. The compiler goes out of its way to ensure that it handles critical errors before compiling the program. With Rust, if the program compiles, one can be sure that it will work.
What’s more, the way Rust handles memory eliminates a lot of the bugs that would compromise the safety of an application. This is one area where Rust offers a dramatic advantage over C++.
While Rust ensures that memory is handled safely, it gives broader control compared to runtime languages. Developers, for example, manage threads and their resources much more freely. In a way, Rust offers a better balance between memory safety and simplicity, although it leans more on the former.
With its powerful safety-focused compiler and error handling tools, Rust also helps save time testing software.
Speed – It’s FAST!
As a low-level system language, Rust excels at fast performance.
Rust doesn’t utilize any runtime environment or garbage collection, making the language incredibly fast and memory-efficient. It can also handle CPU-intensive processes and algorithms much more elegantly.
All of this makes Rust the language of choice for real-time, high-performance applications such as embedded software, data analysis, and other complex systems.
Because Rust forces developers to program reliable applications, it’s the best choice for building applications where security is paramount. Examples include stock trading software and operating systems.
Rust also has a more robust error checking facility. Aside from letting the programmer know of compile errors, it also gives helpful suggestions on fixing them.
Cons of Rust
Steep Learning Curve
Compared to most languages like Java and Python, Rust is notoriously hard to learn. It’s by far its biggest drawback. To put things in perspective, Rust’s difficulty is at par or close to that of C++, long considered to be the most challenging language to master.
And it’s not that the syntax is complicated. It’s because of the freedom Rust gives programmers in terms of memory and hardware. Developers need to understand some concepts a bit deeper to fully realize the language’s potential, even for coding simple tasks.
Rust is a fast language, but compiling it is another matter. Because of its robust error checking, compiling is drastically slower than C or C++, up to a minute or two longer when a thousand lines of code are involved.
As a consequence of being a low-level language, coding in Rust can be complex. On average, it takes a lot more code to execute a given task on Rust than Python. The lack of robust, open-source libraries doesn’t help, either.
Rust vs. Python – When to Use One Over the Other
Python is the language of choice for coding applications that don’t need real-time, high performance. Examples include web development, data analysis, and artificial intelligence.
Because Python is simple to use, developers can focus more on the applications’ logic and algorithm instead of worrying about how to code it properly. They can also rely on a repository of libraries, tutorials, and articles to further speed up development.
On the other hand, Rust is suitable for critical applications that must not break down or become compromised. It gives much better control over every aspect of software development, from the underlying hardware to how it handles memory.
Therefore, Rust excels in real-time performance and security. It’s why it’s used to create operating system routines, embedded systems, virtual reality (VR), and game engines.
Of course, the learning curve and development time with Rust are both steep, so developers must be prepared to make that trade-off when using the language.
Will Rust Replace Python in High-Performance Computing?
Comparing the two, it’s clear that one isn’t necessarily better than the other. It all depends on the developer’s context and goals.
When it comes to high-performance computing, however, it’s an entirely different matter. By now, it should be clear that Rust wins over Python, hands down.
Rust is much more efficient performance-wise in every way than Python. It’s compiled into a machine code, so it’s faster. There are no mechanisms like memory management or garbage collection to bog it down. At the same time, Rust gives developers the freedom to control low-level functions, a requirement when coding complex, system-level apps.
Do you have an upcoming high-performance project? Picking between Rust and Python may be just the first step. Contact us today and let our expert team help you find the best way to move forward.