In this guide, we will compare the Rust and Python programming languages. We’ll discuss the applicable use cases in each case, review the pros and cons of using Rust versus Python, and explain why Rust might replace Python.

I will introduce the following:

  • What is Rust?
  • What is Python?
  • When to use Rust
  • When to use Python
  • Why can Rust replace Python

What is Rust?

Rust is a multi-paradigm language that enables developers to build reliable and efficient software. Rust focuses on security and performance, similar to C and C++, with speed, memory efficiency and no garbage collection. It can be integrated with other languages and run on embedded systems.

Rust has excellent documentation, a friendly compiler, and useful error messages, as well as advanced tools, including integrated package manager, build tools, intelligent multi-editor support, auto-completion and type checking, automatic formatting, and more.

Rust was launched in 2010 by Graydon Hoare of Mozilla Research. Although Rust is a young language compared to Python, its community is growing steadily. In fact, 86% of respondents to Stack Overflow’s 2020 Developer Survey named Rust their favorite programming language for 2020.

At first glance, Rust being static and strongly typed may seem extreme. As you can see, this helps prevent unexpected code behavior in the long run.

What is Python?

Python is a programming language designed to help developers work more efficiently and integrate systems more effectively. Like Rust, Python is multiparadigm and is designed to be extensible. If speed is of the essence, you can use low-level API calls like CPython.

Python, which dates back to The introduction of Python by Guido van Rossum in 1991, is known for its readability and elimination of semicolons and braces.

In addition to its extensibility, Python is an interpreted language, which makes it slower than most compiled languages. As you might expect, Python is highly mature, with a large library ecosystem and a large professional community.

When to use Rust

Rust is used in system development, operating systems, enterprise systems, microcontroller applications, embedded systems, file systems, browser components, virtual reality simulation engines, and more.

Rust is a common language when performance is important because it handles large amounts of data well. It can handle CPU-intensive operations such as executing algorithms, which is why Rust is better suited for system development than Python.

Rust ensures memory security and allows you to control thread behavior and how resources are allocated between threads. This enables you to build complex systems, which gives Rust an advantage over Python.

In summary, you should use Rust when:

  • Your project needs high performance
  • You’re building complex systems
  • You value memory security over simplicity

When to use Python

Python can be used in many applications, from Web development, to data science and analytics, to AI and machine learning, to software development.

Python is widely used in machine learning, data science, and AI because it is:

  • Easy to write
  • flexible
  • Contains a number of data-oriented software packages and libraries
  • Supported by an excellent tool and library ecosystem

You should use Python when:

  • You need a flexible language to support Web development, data science and analytics, as well as machine learning and AI
  • You value readability and simplicity
  • You need a beginner friendly language
  • You prefer simple syntax and speed of development to performance

Why can Rust replace Python

Given Rust’s rapid popularity and wide use cases, it seems almost inevitable that it will surpass Python in the near future, and here are a few reasons why.

performance

One of the main reasons Rust outperforms Python is performance. Because Rust compiles directly to machine code, there is no virtual machine or interpreter between your code and your computer.

Another key advantage over Python is Rust’s threading and memory management. While Rust does not have garbage collection capabilities like Python, the compiler in Rust forces checks for invalid memory reference leaks and other dangerous or irregular behavior.

Compiled languages are usually faster than interpreted languages. But what puts Rust on a different level is that it is almost as fast as C and C ++, but has no overhead.

Let’s look at an example of an O (log n) program written in Python and using an iterative method to calculate the time required to complete the task:

import random
import datetime
def binary_searcher(search_key, arr) :
  low = 0
  high = len(arr)-1
  while low <= high:
    mid = int(low + (high-low)//2)
    if search_key == arr[mid]:
      return True
    if search_key < arr[mid]:
      high = mid-1
      elif search_key > arr[mid]:
        low = mid+1
return False
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Output:

> python -m binny.py
It took 8.6Mu s to searchCopy the code

Now, let’s look at a timed O (log n) program written with Rust using an iterative approach:

>use rand::thread_rng;
use std::time::Instant;
use floating_duration::TimeFormat;

fn binary_searcher(search_key: i32, vec: &mut Vec<i32- > >)bool {
  let mut low: usize = 0;
  let mut high: usize = vec.len()-1;
  let mut _mid: usize = 0;
  while low <= high {
    _mid = low + (high-low)/2;
    if search_key == vec[_mid] {
      return true;
    }
    if search_key < vec[_mid] {
      high = _mid - 1;
    } else if search_key > vec[_mid] {
      low = _mid + 1; }}return false;
}

fn main() {
  let mut _rng = thread_rng();
  let mut int_vec = Vec::new();
  let max_num = 1000000;

  for num in 1..max_num {
    int_vec.push(num as i32);
  }
  let start = Instant::now();
  let _result = binary_searcher(384723, &mut int_vec);
  println!("It took: {} to search", TimeFormat(start.elapsed()));
}
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The output

> cargo run
Finished dev [unoptimized + debuginfo] target(s) in 0.04s
Running target\debug\algo_rusty.exe
It took: 4.6Mu s to searchCopy the code

Without any optimization techniques, it takes 4.6 and 8.6 microseconds, respectively, for Rust and Python to perform similar operations on the same machine. This means Python takes almost twice as long as Rust.

Memory management

Python, like most modern programming languages, is designed to be memory safe. Rust, however, leaves Python in the dust when it comes to memory security, even without garbage collection.

Rust takes a unique approach to memory security that involves an ownership system and a Borrow checker. Rust’s borrowing checker ensures that references and Pointers do not exceed the data to which they point.

Error checking and diagnosis

Python, like other languages, provides error checking and logging mechanisms. But there are some contrasts between Rust and Python when it comes to letting developers know what’s wrong.

Here’s a classic example of a Python variable error:

apple = 15
print('The available apples are:', apple)
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Python output

Traceback (most recent call last):
    File "binny.py", line 2, in <module>
      print('The available apples are:', aple)
    NameError: name 'aple' is not defined
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A similar example in Rust:

fn main() {
  let apple = 15;
  println!("The available apples are:", apple);
}
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Rust output

println! ("The available apples are:", aple); ^^^^ help: a local variable with a similar name exists: `apple`Copy the code

Here Rust recommends possible variables that you might want to enter. Python simply throws errors, not suggestions on how to fix them.

Here’s an example:

fn main() {
  let grass = 13;

  grass += 1;
}
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This code raises an error because variables in Rust are immutable by default. It cannot be changed unless it has the keyword ou’t.

Error:

let grass = 13;
      |         -----
      |         |
      |         first assignment to `grass`
      |         help: make this binding mutable: `mut grass`
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Fix errors:

fn main() {
  let mut _grass: i32 = 13;

  _grass += 1;
}
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As you can see, it now raises no errors. In addition, Rust does not allow different data types to interoperate with each other unless they are converted to the same type.

As a result, maintaining Rust code bases is usually easy. Rust does not allow changes unless specified. Python does allow changes of this nature.

Compared to most compiled languages, Rust is favored for its speed, memory security, superior reliability, consistency, and user-friendliness. In programming, we’ve reached the point where speed starts to be effortless.

As technology evolves, it gets faster and faster, trying to do more things in less time without so many trade-offs. Rust helps achieve this without hindering the developer’s work. When technology tries to push the boundaries of what can be done, it also considers the security and reliability of the system, which is the main idea behind Rust.

Parallel computing

In addition to speed, Python has limitations when it comes to parallel computing.

Python uses a global interpreter lock (GIL), which encourages only one thread to execute simultaneously to improve single-threaded performance. This process is a hindrance because it means you can’t do intensive computing with multiple CPU cores.

community

As mentioned earlier, 86% of respondents to Stack Overflow’s 2020 Developer survey named Rust their favorite programming language of 2020.

Similarly, respondents to the 2020 HackerRank Developer Skills Report listed Rust as the top 10 programming languages they plan to learn next:

By contrast, the 2019 survey placed Rust at the bottom of the list, indicating that the Rust developer community is growing rapidly.

As these numbers show, Rust is becoming part of the mainstream developer community. Many large companies use Rust, and some developers even use it to build libraries used by other programming languages. Well-known Rust users include Mozilla, Dropbox, Atlassian, NPM and Cloudflare, to name a few.

Amazon Web Service has also adopted Rust for performance-sensitive components in Lambda, EC2, and S3. In 2019, AWS announced its sponsorship of the Rust Project and has since provided THE AWS development kit for Rust.

Companies are increasingly replacing slower programming languages with more efficient ones, such as Rust. No other language balances simplicity and speed like Rust.

conclusion

Rust has evolved into a common programming language, and adoption has increased as a result. While Python has a solid foothold in the machine learning/data science community, Rust is likely to be used as a more efficient backend for Python libraries in the future.

Rust has great potential to replace Python. As the programming language of choice for applications, performance, and speed, Rust is more than just a programming language; it’s a way of thinking.

reading

  • Rust Tutorial: An introduction to Rust for JavaScript developers
  • Python and JavaScript — what are the main differences between these two popular programming languages?