Rust vs Python: Choosing the Right Language for Your Project

Compare the two most commonly used programming languages- Python vs. Rust. Explore the detailed comparison- pros, cons, features, and use cases for making the right decision for your next project.

By : Aashiya Mittal

Python vs Rust– is the most common debate of the year. Python is an old robust language while Rust is a newbie but making its mark in the developers’ community. As per the StackOverflow developer’s survey, Python is preferred over Rust, but making Rust is somehow better in some scenarios. 

Python vs Rust-Stackoverflow stats

To know which programming language to choose for your next project, read our detailed comparison and understand their unique features and architecture.

What is Python?

Python is a versatile programming language known for its object-oriented and functional programming styles, with dynamic features. Created by Guido van Rossum and released in 1991, it’s ideal for fast application development due to its dynamic typing and binding. Python is used widely for tasks like data analysis, web development, automation, testing scripts, and creating prototypes. Its straightforward syntax makes it easy to learn, reducing the complexity of maintaining programs.

Python is user-friendly for both beginners and seasoned developers. Its extensive library and third-party packages enable efficient completion of tasks, from analyzing data to building machine-learning models. Like other languages, Python has a strong community offering support, resources, and detailed documentation for ongoing help.

Advantages of Python

Python is loved by 49% of developers, below are the reasons why.

  • Ease of Learning and Power: Python’s straightforward style makes learning easy without compromising on functionality. Its asynchronous coding supports handling complex tasks efficiently.
  • Rich Library and Framework Support: Python benefits from a vast array of libraries and frameworks, supported by its popularity and open-source community. This extensive ecosystem ensures tools are available for various needs.
  • Versatile Integration Capabilities: Python seamlessly integrates with diverse software systems, including enterprise applications and databases. It also supports integration with other languages like PHP and .NET, enhancing its adaptability.
  • Future-proof: As the core language for AI and ML, Python is highly adopted across industries. You can use it to build future-proof applications that will keep on meeting evolving market demands with ease of updation.

Disadvantages of Python

Despite Python being used across industries, and suitable for several use cases, it still shows some limitations.

  • Performance Limitations: Python can be slower compared to compiled languages like C++ or Java, particularly in CPU-intensive tasks due to its interpreted nature.
  • Threading Limitations: Python has a Global Interpreter Lock (GIL) so it cannot execute threads concurrently, impacting performance. So it is not suitable for multi-threaded applications.
  • Design Restrictions: Python’s dynamic typing can lead to errors that might only be caught at runtime, rather than compile-time, potentially affecting program stability.

Key Features of Python

Rust vs Python: Key Features of Python

  • Clear and Simple Syntax: Python has a simple syntax that makes it popular among beginners. You can write fewer lines of code, reducing the time to market.
  • Dynamically Typed: In Python, you don’t need to declare variable types explicitly because the interpreter determines them at runtime based on the assigned value. This saves time and allows developers to focus more on functionality rather than type definitions.
  • Large Community Support: Python benefits from a vast global community that actively supports its development. This community provides quick solutions to issues developers encounter and offers abundant resources such as documentation, guides, videos, and tutorials.
  • Cross-Platform Compatibility: Python applications can run seamlessly across platforms including Windows, Linux, and macOS using a single codebase for each platform, simplifying the deployment and maintenance of applications.

Also read- The Definitive Guide to Python App Development in 2024

Diverse Applications of Python

Rust vs Python: Diverse Applications of Python

What is Rust?

Graydon Hoare at Mozilla Research introduced Rust a versatile programming language. It is known for its safety, stability, and performance, to build memory-efficient architecture that follows C/C++ standards.

what is Rust- popularity

Despite being newer than Python, Rust has rapidly become a favorite among developers. Rust finds applications in various domains, including system development, web applications, embedded systems, blockchain, and game engines. Over 84% of Developers using Rust, love it and want to keep working with it!

Advantages of Rust

Rust is known for its high performance. Below are other benefits of using Rust.

  • Performance-Oriented Design: Rust prioritizes performance, offering faster execution and efficient memory usage compared to other languages. It avoids runtime overhead and eliminates the need for garbage collection.
  • Strict Memory Safety: Rust ensures strict and safe memory management, enforcing secure coding practices that enhance stability and security in software development.
  • Control Over Low-Level Resources: Developers using Rust gain direct and safe control over low-level resources, akin to the capabilities found in languages like C/C++.

Disadvantages of Rust

Rust has the following limitations.

  • Slower Compilation Time: Rust’s compilation process can be slower compared to other languages because it compiles entire packages or crates at once, leading to longer wait times.
  • Steep Learning Curve: Learning Rust may take more time compared to languages like Python. Familiarity with at least one programming language is recommended to effectively use Rust, making it less beginner-friendly.
  • Limited Support for Monkey Patching: Rust does not offer extensive support for monkey patching, a technique for modifying or extending code at runtime, which can limit flexibility in certain programming paradigms.
  • Larger Binary Files: Rust’s focus on performance and safety can result in larger binary files compared to languages that prioritize smaller executable sizes.

Key Features of Rust

Key Features of Rust

Rust combines the strengths of C++ with additional features. Its main advantages are memory safety, thread safety, cross-platform support, and zero-cost abstractions.

  • Memory Safety: Unlike C++, Rust avoids common memory issues through its ownership model and type system. This allows programs to detect and prevent bugs at compile time without needing a garbage collector.
  • Thread Safety: Rust ensures thread safety by managing data ownership. Only one thread can write to a variable at a time, preventing race conditions where multiple threads access the same memory simultaneously.
  • Zero-Cost Abstractions: Rust supports abstractions that don’t impact performance at runtime. This means using abstractions doesn’t add overhead, ensuring efficient code execution even with complex features.
  • Cross-Platform Support: Rust enables development across different platforms like Windows, Linux, and macOS. Its cargo build tool simplifies deploying code to multiple platforms with minimal configuration.

Rust vs Python: Head-to-Head Comparison

1. Ease of Use/Learning

Python’s simplicity and extensive libraries make it globally popular and easy to learn. It’s recommended for beginners over Rust due to its straightforward syntax.

Python’s user-friendly development and broad application in diverse industries highlight its accessibility. Researchers find Python straightforward, requiring fewer lines of code than Rust for similar tasks, making it the preferred choice for ease of learning and usability.

2. Performance

Rust excels in performance compared to Python. It’s built for high-performance applications, known for its speed and efficient memory management without an interpreter.

In contrast, Python’s performance is hindered by its interpreter and inefficient memory management with runtime garbage collection. This makes Python less suitable for performance-intensive applications.

3. Garbage collection

Rust does not use runtime garbage collection, unlike Python. This means Rust does not spend time checking for unused memory during program execution, which can slow down performance.

In contrast, Python’s runtime garbage collection can contribute to slower program execution compared to Rust.

4. Memory Management

Python uses a garbage collector that continuously scans for unused variables in code and frees up memory accordingly.

In contrast, Rust utilizes an ownership model to manage memory, which checks for ownership rule violations during compilation.

Rust distinguishes between stacks (for scalar values) and heaps (for non-scalar values) to store data. This approach allows Rust to manage memory more efficiently than Python’s runtime garbage collector.

5. Error handling

Python handles errors by throwing exceptions at runtime without offering suggestions for fixes during compilation. This method lacks opportunities for improvement before runtime.

On the other hand, Rust identifies errors during compilation and suggests possible solutions without halting the program.

This approach makes error handling in Rust more straightforward and facilitates the creation of high-quality programs by catching issues early in the development process.

6. Security

Rust emphasizes security by focusing on memory safety through its Secure Rust Guidelines. It detects all memory issues during compilation, preventing unauthorized access to variables.

Additionally, the Rust team actively addresses security vulnerabilities in the Rust ecosystem, regularly issuing patches that developers can track through the Rust security announcements mailing list.

In contrast, Python does not offer the same level of memory and thread safety as Rust. Developers using Python must manually manage memory and address potential memory leaks themselves.

7. Community

Both Python and Rust are open-source languages, allowing developers to contribute directly to their development and enhancement.

Python, being more mature and extensively used, boasts a significantly larger and more accessible community compared to Rust at present. It offers abundant resources catering to various development needs.

Rust’s community, although smaller, is supportive, active, and growing. However, Python holds an advantage due to its larger community, which means resources are more readily available and easier to find compared to Rust.

8. Scalability

Python’s slower performance and inefficient memory management can limit its ability to scale applications for larger user bases.

However, techniques like horizontal and vertical scaling of infrastructure can overcome these limitations. Despite these challenges, tech companies use Python extensively, scaling applications effectively through proper infrastructure management.

In contrast, Rust’s high-performance design enables scalable web services to be built with reduced reliance on extensive infrastructure scaling and associated costs.

9. Extensibility

Python leads Rust in extensibility due to its vast array of libraries, modules, frameworks, and tools. This allows Python to handle tasks from simple scripts for daily automation to complex web applications with minimal coding. Its high extensibility makes Python versatile across numerous industries.

In contrast, Rust’s ecosystem is expanding rapidly, with continuous growth in the Rust community crates registry. However, the current number of crates available in Rust does not match the extensibility seen in Python.

Rust vs Python: Which One Should You Choose?

When to Choose Rust-

  • High-Performance Needs: Opt for Rust when you need to build applications that require fast and efficient performance.
  • Memory Safety Priority: Choose Rust for projects where memory safety and preventing bugs at compile-time are critical.
  • Systems Programming: Use Rust for system-level programming, especially when working with low-level hardware or writing operating systems.
  • Concurrency and Parallelism: Rust is suitable for applications that require effective handling of concurrent operations and safe parallel execution.

When to Choose Python-

  • Choose Python for quick prototyping and developing applications rapidly.
  • Opt for Python when extensive third-party libraries and frameworks are necessary.
  • Use Python for data analysis, machine learning, and scripting tasks.
  • Consider Python for its widespread adoption, large community support, and versatility across various industries.


Python is widely used and very popular for various purposes. Rust, though newer, is gaining popularity because of its advantages over Python, especially in safety features and efficient performance.

Both languages are extensively used by top tech companies. Rust is known for its thread and memory safety, and it offers zero-cost abstractions.

On the other hand, Python is valued for its easy-to-understand syntax, flexible typing, large community, and many libraries.

Rust, however, has slower compile times and lacks support for certain programming techniques. Python is slower and doesn’t have strong support for databases and mobile development.

Python stands out for its user-friendliness, job opportunities, developer salaries, extensibility, popularity, and community support.

Despite being newer, Rust surpasses Python in error handling, memory management, performance, scalability, security, and speed.

In conclusion, Rust is seen as a superior language with competitive advantages over Python, positioning itself to potentially become one of the dominant programming languages globally.

It’s highly recommended to consider learning Rust for future projects.

Why Choose OnGraph for Your Next Project?

As we explore the ever-changing world of app development, Rust vs Python significantly impact app development in 2024.

OnGraph, a leader in innovation, providing developers with powerful tools to build dynamic and efficient applications for different niches.

Connect with OnGraph to build customized Rust and Python solutions for your business needs, leveraging innovative technologies and best practices. 

  • Scalable Solutions
  • Expert Developers
  • 24×7 support
  • Innovative Technologies
  • Robust Applications
  • Digital Transformation
  • Tailored Solutions


Q. What is Python used for? 

Python is used for a wide range of applications including web development, data analysis, artificial intelligence, automation, scientific computing, and more. Its versatility and ease of use make it popular among developers.

Q. Why choose Rust over other programming languages? 

Rust is chosen for its focus on safety, performance, and concurrency. It prevents common programming errors at compile-time, making applications more secure and efficient, especially in systems programming and performance-critical applications.

Q. Is Python easy to learn for beginners? 

Yes, Python is often recommended for beginners due to its simple and readable syntax. It allows new programmers to focus on learning programming concepts rather than dealing with complex syntax and rules.

Q. What are the advantages of learning a programming language with a large community?

Learning a programming language with a large community, such as Python, provides access to extensive resources, tutorials, libraries, and support forums. This community support can help developers solve problems faster and stay updated with industry trends.

Q. How important is performance in choosing a programming language? 

Performance is crucial depending on the nature of the application. High-performance applications like games, real-time systems, or large-scale data processing benefit from languages like Rust, while Python’s flexibility and ease of development may be preferred for less performance-critical tasks.


Aashiya Mittal

A computer science engineer with great ability and understanding of programming languages. Have been in the writing world for more than 4 years and creating valuable content for all tech stacks.

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