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  4. Rust vs Python: Differences and Ideal Use Cases

Rust vs Python: Differences and Ideal Use Cases

Python vs. Rust is one of the most debated topics among devs, as both are widely used programming languages. Make the right choice for your next project.

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Maxwell Fary
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Feb. 24, 25 · Analysis
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Rust and Python are widely used programming languages in software development and data science. Rust’s adoption has grown significantly in recent years, leaving many wondering if it will eventually replace Python as a top programming language.

Compared to Python, Rust is a newbie but is making its mark among developers. According to the StackOverflow Developer Survey, Python is preferred over Rust, but in some cases, Rust is better. To better understand which one to choose, this article walks you through both languages' features, what makes them different, and how they fit into specific projects.

What Is Python?

Python is a popular scripting language. Python is used in many fields, including machine learning, data science, data visualization, data analysis, DevOps, automation, and testing.

Python is also ideal for novice developers worldwide due to its simple syntax. According to the Stack Overflow Developer Survey 2023, it is the third most popular language among professionals and beginners. Although Python is primarily used for object-oriented programming, you can also use it for functional programming.

There are many reasons why Python is so popular, including its ease of use, simplicity, and versatility. It provides a simple programming experience with a simple syntax in place of the staples of other programming languages, like semicolons and curly brackets.

Advantages of Python

The following are some significant reasons why developers use Python:

As one of the most popular programming languages, it is also among the easiest to learn because of its simple syntax. This makes it a better choice for amateur developers than complex languages such as Rust or PHP. 

  • With Python's extensive standard library, you can perform everything from simple numerical calculations to complex data analytics.
  • Declaring variable types is easier with dynamic typing.
  • Many tools support Python development, including Python-specific IDEs and code review tools. Python also has a tool called GitPython that interacts with Git repositories. 
  • This language provides cross-platform support for software development.
  • Due to Python's interpreted nature, debugging is easier.
  • Python has a large community that can help you resolve problems faster and provide quick support.

Compared to Rust, Python is easy to integrate with other components, such as databases, which can be used with .NET and PHP programs.

Disadvantages of Python

Despite its many advantages, the language has some limitations regarding performance and security. Let's discuss them below. 

  • Due to its interpreted nature, Python has slower performance than lower-level languages like Rust.
  • When multi-threaded applications are running, Global Interpreter Lock (GIL) can cause concurrency problems.
  • The dynamic nature of the code can lead to runtime errors and less predictable behavior.
  • Due to its line-by-line execution and dynamic typing, the language is less suitable for performance-critical applications and systems programming than Rust. 
  • A number of Python's features, including flexible data types, consume a large amount of memory. Hence, it is not suitable for memory-intensive applications.
  • The slow speed and high memory usage make it unsuitable for mobile applications.
  • It can be difficult to access databases using Python because it is not as developed as many other languages.

Who Uses Python?

  1. Facebook 
  2. Google
  3. Netflix
  4. Spotify
  5. Instagram 

What is Rust? 

Rust was developed by Graydon Hoare of Mozilla Research as a general-purpose multi-paradigm programming language. 

It is a relatively new programming language that has quickly gained popularity due to its ability to create fast, memory-efficient, and reliable applications. It has a similar syntax to C++ and is statically typed. In the StackOverflow Developer Survey 2023, 13.05% of developers used Rust, up from 9.32% in 2022. 

It does not have garbage collection or a run time. Therefore, Rust provides solutions to many C++ issues, including multitasking and memory management.

Advantages of Rust 

Rust is known for its high performance. Here are all the main advantages of Rust.

  • Rust is an ideal choice if you are developing performance-critical applications because it is memory-efficient without garbage collection or runtime.
  • Rust's type system and ownership model makes it thread- and memory-safe.
  • Since Rust is a statically and strongly typed language, incorrectly declared variables cannot cause code errors.
  • The low overhead of Rust makes it ideal for developing embedded applications.
  • In the Rust community, you can discuss issues and ideas with others, organize events and conferences, and learn more.
  • Along with its rich documentation, it also provides several tools to enhance productivity. For example, it features an integrated package manager, a build tool, and an editor with useful features.
  • You can develop software using Rust with cross-platform support.

Disadvantages of Rust 

The Rust programming language is known for its safety, concurrency, and performance. However, like any language, Rust has a few drawbacks that need to be understood before using it. 

  • Rust's syntax can be quite complex, especially with features such as lifetimes and trait bounds. Beginners may find this complexity intimidating.
  • Compared to languages such as C++ or Go, Rust's emphasis on safety and zero-cost abstractions results in longer compile times. This can slow down development if you are working on large projects.
  • The integration of Rust with other languages and existing code bases can be complicated and time-consuming.
  • In terms of libraries and frameworks, Rust lags behind Python and JavaScript in the debate between Rust and Python. Finding pre-built solutions for some problems can be challenging.
  • A newcomer to systems programming may find Rust difficult to learn. You may have trouble understanding its strict compiler and ownership model.
  • It can be hard to find resources, tutorials, and community support on Rust, even though the community is passionate and growing.

Who Uses Rust?

  1. Amazon
  2. Dropbox
  3. Google
  4. Microsoft
  5. Coursera 

Python vs. Rust: A Side-by-Side Comparison

FACTORS RUST PYTHON

Purpose 

Systems programming, performance-critical applications

General-purpose programming, suitable for web development, data science, and machine learning

Performance 

High performance, comparable to C, C++

Slower, interpreted language but user-friendly 

Ease of Use 

Complex, especially for beginners 

Very easy to use and understand 

Tooling 

Good, but still maturing 

Excellent, mature, and widely supported by many IDEs

Garbage Collection 

No garbage collector; it uses an ownership system

Automatic garbage collection, less control 


Memory Management 

Manual, fine-grained control 

Automatic, abstracted from the developer

Concurrency

Strong concurrency model with threads and async/await

GIL limits true multi-threading but supports async/await

Security

Strong memory safety and security guarantees

Relies on best practices and libraries

Documentation

Detailed, comprehensive, user-friendly

Extensive, mature, and widely available

Community

Smaller, but active and welcoming

Large, diverse, and highly active

Learning Curve

Complex to learn, difficult concepts like ownership and borrowing

Simple, easy to learn and use

Development Speed

Slower due to strict compile-time checks

Faster due to simple syntax and dynamic typing

Integration

Good with C/C++, harder with other languages

Excellent with many other languages and tools

Error Handling

Explicit, through Result and Option types

Flexible, through exceptions

Popularity

Growing, especially in systems programming

Extremely popular, widely used in various fields


A More Detailed Comparison 

Python and Rust have been a long-debated topic. Let's discuss the major differences between Rust and Python one by one.

1. Ease of Use

Python's syntax is simple and easy to read, making it suitable for both experienced developers and beginners. However, Rust can be quite challenging if you're unfamiliar with system programming concepts like borrowing and ownership.

2. Performance

Like C and C++, Rust is very fast when it comes to performance. You can control system resources and memory management with Rust, which prevents unnecessary slowdowns. Rust's static typing and compiling processes also ensure that the code runs efficiently.

On the other hand, Python is a programming language that tends to be slower to interpret. Python focuses more on ease of use and readability than speed. Python can be an excellent choice if your project does not prioritize speed. Python is faster when you use tools like PyPy, but it still can't match Rust's performance, especially when it comes to tasks that require a lot of processing power.

3. Garbage Collection 

There is a significant difference between Rust and Python in terms of garbage collection. Instead of garbage collection, it uses a compile-time ownership system to manage memory. The system ensures memory safety and eliminates issues such as null pointer dereferencing. So, if you are a beginner, this approach can be complex, even though it provides predictable performance.

However, Python uses automatic garbage collection, simplifying developers' memory management. Since Python's garbage collector reclaims unneeded memory, it can introduce unpredictability in performance. Python uses reference counting and a cyclic garbage collector to handle circular references.

4. Security

Compared to Python, Rust's compile-time checks and ownership model significantly reduce the risk of common programming errors that can result in security vulnerabilities like buffer overflows and data races. So, if your project’s security is paramount, then Rust is an ideal choice.

Python abstracts many low-level details, lowering the chances of certain bugs. Python does not offer the same level of memory safety as Rust. Python security is often dependent on best practices and libraries designed to mitigate common vulnerabilities. 

5. Features

Considering the features of each language, Rust is more intuitive and unique than Python. As mentioned earlier, Rust is safer than Python when it comes to memory and threads. A Rust program is more efficient than a Python program without garbage collection and run time. With Rust, programmers can write complex applications with zero-cost abstractions. A number of useful tools are available in Rust to simplify the deployment process.

On the other hand, Python is less feature-rich than Rust. Among Python's prominent language features are its dynamic typing, simple syntax, and interpreted general-purpose nature. Both languages support cross-platform development. Therefore, Rust offers a greater variety of features than Python.

6. Preferred IDEs

There are several local IDEs that excel at Python app development, specifically for data scientists and engineers. PyCharm is a popular choice because it offers comprehensive code analysis, debugging tools, and integration with popular data science libraries. Other popular IDEs include Spyder and Visual Studio Code.

A number of IDEs are now offering data-related features for Rust development. Visual Studio Code stands out as an IDE with powerful Rust support through plugins like Rust Analyzer and Rust Language Server.

7. Documentation

When discussing Python and Rust, both programming languages have strong documentation but different emphases. Rust's documentation is well known for its thoroughness, including the official Rust book, a comprehensive guide highly praised by the community. Rust's standard library documentation includes many examples, and the learning ecosystem is robust, with a variety of books, courses, and community contributions.

Python's extensive and mature documentation reflects its long history and widespread use. Also, it offers various tutorials, guides, and examples to suit all levels of experience. Numerous third-party tutorials, books, and courses further enhance the Python learning resources.

8. Community Support 

The community side of Rust and Python also highlights important differences. Because the two programming languages are open source, fellow developers participate actively in their development and improvement processes. The Rust community, though not as big as Python’s, is growing and caring, too. For instance, Rust developers can find help or share knowledge through many forums, chat rooms, or even at various community events.

Python has one of the largest and most active programming communities. It contains many third-party libraries and testing frameworks, as well as a good number of forums and user groups.

9. Popularity 

When comparing the popularity of the two languages — Rust and Python — it is undeniably established that Python has been embraced more than any other language. Its vast library and framework ecosystem make it popular for web development, data science, machine learning, automation, etc.

But what has made Python so popular is its flexibility and friendly user interface. While Rust is becoming more popular for high-performance applications, such as system programming, it is still less common than Python. Rust has indeed gained a loyal following among safety-conscious programmers who are satisfied with its commitment to safety; therefore, these rankings have risen gradually.  Rust also lacks the extensive and diverse community that Python has. So, python is the clear winner in terms of popularity.

10. Learning Curve

Last but not least, Rust is known for its steeper learning curve than Python, mostly because of its strict compilers and complex concepts. It might be hard for beginners to learn Rust's low-level programming concepts. 

Python is one of the most popular programming languages chosen by beginners because of its simplicity and readability. Python is considered easy to learn due to its clear syntax and high-level abstractions.

Python Use Cases: When Should You Use It? 

Python is ideal for rapid web development, data science, and automation due to its versatility and speed. Its simple and readable syntax makes prototyping and development fast, which is perfect for startups.

Python excels in data analysis and machine learning with powerful libraries like Pandas and TensorFlow. Its extensive library support simplifies automation and scripting tasks.

Python is the better choice in the following scenarios when comparing Python and Rust:

  • If your project requires a language that supports web development, data science, machine learning, and artificial intelligence, then Python is a good choice.
  • You prefer beginner-friendly languages.
  • Simplicity and readability are important to you.
  • Performance is less important to you than syntax simplicity and development speed.
  • Python is a great tool for prototyping and developing applications quickly.
  • It’s a good choice when you need extensive third-party libraries and frameworks.
  • The wide adoption, large community support, and versatility of Python across various industries make it a compelling choice.

Rust Use Cases: When Should You Use It?

Rust is ideal for processing large amounts of data because it works well when performance is important. As a result, Rust is better suited for systems development than Python because it can handle CPU-intensive operations like executing algorithms.

Rust guarantees memory safety, and you control resource allocation. It offers an edge over Python because you can build complex systems this way.

Rust is a better choice in the following scenarios when comparing Rust and Python:

  • When you need an application to perform fast and efficiently, choose Rust.
  • For projects that require memory safety and bug prevention at compile time, Rust is the best choice. 
  • Rust is an excellent language for system-level programming, especially when dealing with low-level hardware or operating systems.
  • It is suitable for applications requiring efficient handling of concurrency and parallelism.

Rust or Python: Which Is Better?

Many programmers highly prefer Python due to its versatility. Despite being a newer language than Python, Rust has been gaining popularity, especially in terms of safety and performance advantages.

The top tech companies use both languages. In terms of Rust and Python, deciding which is best for you depends on your goals. Rust is good for systems programming as well as performance-critical applications because of its high performance, fine-grained control over memory, and strong focus on safety and concurrency. However, the language can be difficult for beginners to understand since it involves concepts such as ownership and borrowing, which make it more challenging, but these characteristics also make it robust and secure.

Python excels at web development, data science, and automation, which require rapid development and ease of use. Due to its simple and readable syntax and extensive libraries, it is suitable for both novices and experienced developers. Python is better suited to projects prioritizing speed and ease of use, while Rust is better suited to projects demanding maximum performance and safety.

Python (language) Rust (programming language) Performance programming langauge

Opinions expressed by DZone contributors are their own.

Related

  • Segmentation Violation and How Rust Helps Overcome It
  • Rust and WebAssembly: Unlocking High-Performance Web Apps
  • Mastering Ownership and Borrowing in Rust
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