Rust vs Python

Rust vs Python: What Are The Actual Differences?

Nowadays, comparing programming languages has become highly popular. When there are so many languages to pick from, it can be tough to know which one will best fit the project. People in business and enterprises must choose the best technology from a variety of options. 

So, in this article, we’ll go over Rust vs Python programming in detail. Python and Rust have a lot in common when it comes to how APIs should work, but that’s where the likenesses end. 

One is an interpreted language, whereas the other is compiled. On both sides, you’ll find some unmatched features that insist that one is superior to the other. Let’s start with a brief overview of both languages before diving into the details of Rust vs Python.

What Is Rust Programming?

Rust is a programming language that is high-level, general-purpose, and multi-paradigm. It is designed for safety and performance, mainly for safe concurrency. Graydon Hoare created Rust along with Dave Herman, Brendan Eich, and others at Mozilla Research. 

Rust is a low-level programming language that has direct hardware and memory access, making it ideal for embedded and bare-metal development. Rust can be used to create control systems and microcontroller programs. 

While working on the Servo experimental browser engine and the Rust compiler, the designers fine-tuned this language. Rust has been the most liked programming language’ according to the Stack Overflow Developer Survey, since 2016. The reasons behind the popularity of Rust are as follows-

  • High performance with memory safety.
  • The number of Rust packages is expanding at the crates.io repository.
  • Concurrent programming is supported.
  • Stability and backward compatibility are guaranteed.
  • A growing community is evolving this language.
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Rust Program To Check If A Number Is Positive, Negative, Or Zero

Program

fn main() {    
let n = -3;

    if n < 0 {
        print!(“{} is a negative number”, n);
    } else if n > 0 {
        print!(“{} is a positive number”, n);
    } else {
        print!(“{} is zero”, n);
    }

}

Output

-3 is a negative number

What Is Python Programming?

Python is an object-oriented, high-level, and interpreted programming language. It has dynamic semantics. Python has a very simple and understandable syntax that is easier to read and write than other languages like C, C++, and Java. It is used in software development, web development (server-side), system scripting, data science, and so on. 

Python, like Rust, is a multi-paradigm and extendable language. If performance is critical, you can use lower-level API calls like CPython. Guido van Rossum is the creator of the Python language, first released in 1991. 

Python is the second most popular programming language in the world, according to the TIOBE Index for August 2021. The main reasons behind the popularity of Python are as follows-

  • Python is Free and open-source, which means anyone can use and distribute this language freely.
  • Python is very easy to learn, understand, and code. Therefore, it is beginner-friendly.
  • Python is known for portability. So, we can move and run Python programs from one platform to another.
  • Python has a wide range of uses, such as web development, rapid application development, data science, etc.
  • Python allows the development of programs with fewer lines of code than most other languages.
  • Python is now one of the most widely used programming languages.

Python Program To Check If A Number Is Positive, Negative, Or Zero

Program

def NumberCheck(a):

           if a > 0:
            print(“Integer”,a,”given by you is Positive”)

           elif a < 0:
            print(“Integer”,a,”given by you is Negative”)

           else:
            print(“Integer”,a,”given by you is zero”) 
 
# Taking number from user
num = int(input(“Enter an integer: “))
# Printing result
NumberCheck(num)  

Output

Enter an integer: -99

Integer -99 given by you is Negative

Rust vs Python: All Essential Differences

Here is the list of essential differences between Rust and Python

Rust vs Python Performance

Rust provides better performance than Python. Rust offers developers a solid balance of high performance and security, as well as faster processing. Rust is about twelve times faster, and its performance is comparable to C and C++, but Python is slower. Yes, Python is known for being “slow” in some situations, but this doesn’t matter in most cases. This is a minor element that will not affect the majority of projects. 

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Rust vs Python Security

Managing computer memory safely and efficiently is one of the most difficult tasks for any programming language. Security is one of the best aspects of Rust. Python has a garbage collector that looks for and cleans up unused memory as the program runs. 

Rust is extremely safe. There is a higher emphasis on fixing memory leaks and other security issues. Memory leaks are addressed in many of its key principles. 

Rust vs Python Low-level language 

It is one of the primary differences in Rust is a low-level programming language. It is a great option for embedded and bare-metal development due to its direct access to hardware and memory. 

Rust is best for developers who have limited resources and need to ensure that their software does not fail. Whereas the high-level language Python is better suited to fast prototypes.

Rust vs Python Dynamic And Static Typing

Python is a dynamic type system, which makes creating software easier for programmers. Whereas Rust is a static type system requiring programmers to declare parameters, i.e., constants and function arguments, it supports Python-like dynamic typing within the function body. “None” is a valuable feature in Rust that allows programmers to deal with exceptions at build time, ensuring that the program executes smoothly for the user.

Rust vs Python Easiness to Code & Learn

The most significant, but also the most subjective, part of this comparison is learning and coding experience. Everyone wants their first programming language to be simple to learn but versatile to pursue various programming careers. 

Beginners generally take one to two weeks to start building projects, whereas it only takes a few days for them to start building projects in other competitive languages. 

In comparison to Rust, Python is much easier to learn. Python is a great language for beginners because of its extremely short learning curve. The syntax of Python is extremely simple to read, understand, and code, even for beginners.

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Rust vs Python Documentation

Both languages come with comprehensive documentation. In the documentation of Python, there are numerous examples to help you comprehend it. The Python community has done an excellent job with documentation, with the majority of functions being described in plain English. 

When it comes to an introduction and functions, Rust’s documentation is well-organized and contains a lot of information. However, Rust’s documentation is more complex than Python’s when these two are compared.

A+ grade

Rust vs Python Applications

Rust is mostly utilized in operating systems, gaming engines, file systems, browser components, and virtual reality (VR) engines. Python is used for numerous applications such as web application development, web scraping, enterprise applications, data analytics, data visualization, machine learning, etc.

Rust vs Python Community

The larger the community is, the easier it is to get support. Python has a huge community. It is larger than Rust’s community. Therefore, the solution to most of the problems you encounter while coding is already present on the Internet.

Rust vs Python Search Trends

The below graph shows the last 5 years’ search trends of Rust and Python languages on google. Rust language is not even closer to the popularity of Python on the google search. 

Rust vs Python Search Trends

Rust vs Python: Head To Head Comparison

ParametersRustPython
CreatorGraydon HoareGuido van Rossum
SpeedFaster than PythonSlower than Rust
Ease of coding, learning, and UnderstandingDifficultEasier
Error ProcessingPassed back errors in the return valueThrow errors as exceptions
SecurityMost fundamental concepts focus on the fixation of security issues and memory leaksGarbage collector cleans up unused memory
Development CostHighAverage
CommunitySmallLarge
Documentationwell-organized and contains a lot of information, but complex than Python’s documentationNumerous examples to help learners to understand it. The Python community has done an excellent job with documentation
TypingStatic TypingDynamic Typing
ApplicationsMostly used in operating systems, gaming engines, file systems, browser components, virtual reality (VR) engines, etcMostly used in web application development, web scraping, enterprise applications, data analytics, data visualization, machine learning, etc

Summary

In this blog, we have gone through Rust vs Python in detail. Rust is faster than Python, but Python is better at the ease of coding. Rust is secure than Python, but the development cost is high. In comparison, Python is less secure but comes with lower development costs than Rust. Rust has static typing, whereas Python has dynamic typing. 

Therefore, which language is better than the other entirely depends on the project requirements. Hopefully, now everything about Rust vs Python is cleared in your mind, and you can decide to choose one of these two languages. 

Moreover, if you need Rust Assignment Help or Help with Python Homework, you can discuss your requirements with our experts anytime.

Frequently Asked Questions

Is learning Rust hard?

Yes, Rust is considered a difficult language to learn. For someone who doesn’t know any other programming language, Rust is very hard. But, if someone knows any other programming language, he may learn it with ease.

Is Python still relevant 2021?

Python is one of the most popular languages. It is used for a variety of different applications such as web development, game development, scientific and numeric applications, Artificial Intelligence, software development, etc. Python’s prominent ML libraries, such as Pandas and Scikit-learn, make it the favored language for machine learning and data science.

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