This article gives you a complete picture of the Rust vs. Python landscape. By the end of the article, you’ll have a clear idea of what Rust and Python offer. In addition, you know to pick the right programming language for your project.

Let’s get started.

What is Rust?

Rust is a multi-purpose, high-performance programming language. It is statically typed with a similar syntax to C++. With Rust, developers can create memory-efficient and performance-optimized applications.

Rust’s core idea is to compile everything before the program runs. Therefore, it doesn’t house a runtime solution, making it ideal for writing critical applications. Moreover, it offers excellent concurrency and memory management rules powered by its ownership model.

The best way to describe Rust is to have low-level access similar to C++ while having the safety of a high-level programming language such as Python.

Who uses Rust?

Rust is popular among startups and big companies. Rust is a multi-purpose programming language that uses servers, tooling, web applications, game development, data science, etc.

Some prominent industry names using Rust include Coursera, Dropbox, Figma, Microsoft, Facebook, and Discord.

Each company uses Rust differently depending on requirements. For example, Figma, a collaborative web design tool, uses Rust to boost its platform’s front-end performance. They have entirely written Figma’s multiplayer syncing engine from TypeScript to Rust.

Coursera, a popular online learning platform, uses Rust to power web-based assignment solutions for students. In addition, Dropbox uses Rust for its file synchronization engine due to better testing and debugging, making it easy to manage complex databases and concurrent code.

Rust key features

Rust excels as a multi-paradigm programming language. However, its key features separate it from Python. It offers a good combination of low-level access with high-level usability, matching C++ performance. Its key features include:

• Memory Safety: Rust is a memory-safe programming language. Thanks to its ownership model, it achieves memory safety without relying on a garbage collector. It also has a robust type system that ensures no runtime errors can occur as Rust’s compiler analyze memory during compile time. 
• Zero-cost abstraction: Rust doesn’t punish developers for deploying abstractions. This means you get no performance penalty when you use abstraction, and the code runs without overhead. The zero-cost conception helps do code maintenance or add new features.
• Thread safety: Rust’s ownership model approach to concurrency includes a thread-safe approach. It protects the program from running into race conditions at run time. Programmers using Rust can use Rust’s mutable option to give access to a variable and then purge it once not needed, leading to a thread-safe environment.

Apart from these, Rust also offers easy-to-understand error messages, type interface, pattern matching, and move semantics.

What is Python?

Python is a high-level programming language. It is known for its scripting capabilities and ease of use. Moreover, it is also an excellent pick for visualization, automation, testing, and much more.

Python is interpreted and supports object-oriented paradigm. It also supports dynamic typing and binding, which is crucial for Rapid Application Development(RAD).

Who uses Python?

Python is a popular programming language. It is used widely in different sectors, including Finance, Government, Education, and IT. Python’s use cases include web development, data analysis & machine learning, scripting, automation, software prototyping, and more.

Google is at the forefront of using Python for its projects. Their founders are vocal about how Python can help them achieve better results, as Python offers better prototyping and ease of maintenance. 

Next, we have Facebook. They released a post in 2016 showcasing how Python is used to write and maintain multiple infrastructure management services. These include Dapper, FBOSS, and TORconfig; each offers unique functionality to Facebook’s core infrastructure.

Spotify also uses Python to power its back-end services, including data analysis. According to Spotify, they like Python’s ability to fit in a fast development pipeline.

Python key features

Python is a popular programming language. The key features that make it so popular among developers and learners include the following:

• English-like syntax: Python syntax is similar to English in many ways. It is identical to writing pseudo code, which appeals to most learners and engineers. Apart from learning advantages, Python’s English-like syntax makes development faster. 
• Interpreted: Python is an interpreted language. It enables developers to have flexibility compared to a compiled language. Moreover, interpreted languages are genuinely platform-independent. Python, an interpreted language, also brings other benefits, including faster prototyping and easy error identification.
• Dynamically typed: Python is dynamically typed, which makes it easier to understand. The interpreter takes care of determining variable data types at runtime.
• High-level language: Python is a high-level language that makes it easy to work with.
• Object-oriented programming language: Python supports an object-oriented model that lets programmers implement concepts such as Inheritance, Polymorphism, and Encapsulation. It helps developers to map things similar to how the real world works, enabling them to write code faster and more efficiently.

Apart from these features, other Python’s key features include a large community, an extensive standard library, open source, platform-independent, GUI support, etc.

Rust Pros and Cons

This section takes a look at Rust’s pros and cons.

Pros of Rust

• Rust has low memory usage. This is possible because of Rust’s ability to offer excellent memory control without using Garbage Collector.
• Rust is an excellent performance out of the box. It manages to match C++ performance. That’s because it is designed to perform. Moreover, it also offers LLVM optimizations. The other Rust features that improve the system’s performance include slices, HashMap API, and more.
• Rust also offers easy-to-understand error messages. That’s a boon compared to other programming languages that fail to do so. The compiler provides a detailed error so you can work with them with as much information as possible. 
• Rust offers a solid toolchain for better development workflow. Here, you get a Cargo package manager capable of providing package management, documentation generation, and test runner.
• Rust is statically typed, ensuring that type errors don’t creep in during runtime.
• Rust supports cross-platform development.

Cons of Rust

• Rust’s borrower checker introduces complexity. This requires Rust programmers to think as a borrow checker and resolve any issues with it.
• Rust doesn’t capture stack traces, which makes errors hard to debug. However, community-based tools already provide a workaround, such as using the error chain library.
• Rust is a new programming language and still growing. Its early phase means developers must deploy workarounds to overcome drawbacks, and libraries are still in progress.
• Rust’s documentation is still a work in progress. It can lead many developers to look for other resources or longer debug times. 
• Rust compile time is slower due to several checks to ensure error-free code development.

Python Pros and Cons

This section covers Python’s pros and cons.

Pros of Python

• Python is an easy-to-learn programming language thanks to its English-like syntax.
• Python offers an extensive library for easier and faster development across different spheres, including machine learning, web development, testing, automation, scraping, visualization, etc.
• Python is great for rapid application development. This is because of multiple factors, including dynamic typing, easy-to-learn, shorter program code, and extensive availability of libraries.
• Python is interpreted, which means benefits like faster error checking and the ability to execute independently of the platform.
• Python is truly portable and follows the write once, run anywhere philosophy. As Python is pre-compiled, its Python code can run anywhere using the platform-specific Python Virtual Machine(PVM)
• Python is dynamically typed, which doesn’t require programmers to type variable types. Its interpreter then determines the data type during runtime.

Cons of Python

• As Python is not a low-level language, it is not the fastest programming language. However, it doesn’t mean it is not ideal for real-world applications, but if you’re building a critical application, there are better choices than Python.
• Due to the dynamic type approach and use of an interpreter, Python suffers from runtime errors. This makes it harder to debug.
• Python memory consumption is higher due to the flexible data type, making it unideal for memory-sensitive apps.
• Python is not optimized for database access. So, if you’re working with a data-focused application that requires writing complex queries, there are better fits than Python.
• Python is not an ideal pick for developing mobile or desktop applications due to its high memory consumption and limited availability of Python mobile frameworks.

Rust vs. Python Comparison

In this section, we’ll look closely at Rust vs Python. Then, we’ll compare them via different criteria. If you’re in a hurry, check out the Rust vs Python table.

Popularity

When it comes to popularity, Python is the winner. This is because of multiple reasons, including its ease of use, usage in the ML/AI sphere, and the most obvious factor, age. 

Python is almost 3 decades old, from its inception in 1991 when Dutch programmer Guido van Rossum released its first version. In contrast, Rust was released in 2006. And, only recently, it has started gaining popularity.

Even though Python’s popularity is more than Rust, it doesn’t make Rust a loser. 

On the contrary, in the last 7 consecutive years, Rust has been the most loved programming language in the StackOverflow developer survey. However, it may not gain as much popularity as Python, considering Rust has a steep learning curve.

Learning Curve

Python is easy to learn and get started with. Its ease of learning begins with its English-like syntax and dynamic type approach. On top of that, there are excellent resources for learning Python, making it more accessible to the learning audience.

Rust, on the other hand, has a steep learning curve. Its core philosophy is to offer a tool to create memory-safe programs. To do so, it introduces many new concepts, such as the ownership model. If you’re a beginner, you may find it way more challenging. Experienced programmers must invest time and effort to become proficient at Rust.

Apart from that, Python also has a rich ecosystem where you get access to frameworks, libraries, and modules. Furthermore, it makes it easy to use Python, considering it offers good documentation. Lastly, you can write a program in fewer lines with Python than with Rust.

Performance

Performance-wise, Rust wins hands down. It can interact directly with the hardware as the code is compiled into machine code. Rust’s memory management approach also means better performance as it enforces memory checks during code compilation.

Python lacks speed because it is interpreted. This means that the Python Virtual Machine(PVM) must first interpret the code before it can interact with the hardware. However, Python’s goal is never to be fast but to offer more flexibility and ease to use.

Memory Management

Both Python and Rust aim to be memory-safe. However, Rust takes memory management too seriously and implements it through its unique ownership model, where variables need to be borrowed to use. Once the borrowing period ends, Rust’s borrow checker removes variable references automatically, ensuring proper memory management.

Additionally, the Rust ownership model forces programmers to use stack and heap to store values in the memory. Heap offers a less organized way to store values, whereas stack provides a faster, more organized way to store and access values. However, programmers can use the heap to store unorganized values and then use the stack to store the heap pointer for faster access.

On the other hand, Python is also memory safe but uses a garbage collector, which can lead to runtime race conditions.

Security

Rust takes security very seriously, and that’s obvious from its ownership model. It also offers proper Secure Rust guidelines for developers who want to build bullet-proof applications. Also, as Rust is compiled before the program runs, most errors and security issues are highlighted beforehand. Lastly, the Rust team actively patches any security vulnerabilities, ensuring a safe Rust ecosystem.

So, when you start developing with Rust, you use their default, “safe-by-default” mode. It also offers another mode known as unsafe Rust, which gives developers more flexibility to work with their code and makes them responsible for the app’s security.

Python is also very secure. However, it does lack in both memory and thread safety. This means developers must do the grunt work(such as memory management) to secure their applications.

Error Handling

When it comes to error handling, Python uses exceptions to handle errors. So, a developer can explicitly mention exception which works in addition to already available built-in exceptions.

In Rust, error handling works differently. Rust offers two error categories, known as recoverable errors and unrecoverable errors. The developer must resolve the unrecoverable errors because Rust enters the panic macro once it happens. Here, you get every detail of how to resolve the issue. In case of a recoverable error, the user must enter the correct input or resolve from its side. However, Rust’s inability to provide stack traces can leave developers who need help to be knowledgeable. Plenty of chain tools provide the much-necessary stack information for debugging.

Overall, Rust offers a better error-handling model, which guarantees memory safety, improves user-friendliness, and offers reliability & consistency.

Employability

Most learners learn a programming language because of the prospect of making money. So, where do Rust and Python stand when making money? 

Here, Python seems to win by a large margin. This is because most industry players use Python more often in their processes. That’s why most IT companies are looking for skilled Python programmers. Additionally, Python’s broad use cases mean plenty of roles across the industry, including data analyst, machine learning expert, full-stack developer, and so on.

• Practice Python interview questions

Rust, on the other hand, has a limited market demand. However, even if it is relatively new, its demand grows as more companies embrace Rust in their product or service. This means there is good demand for Rust programmers, but lower than that of Python programmers.

• Practice Rust interview questions

Both Rust and Python programmers are paid adequately according to industry standards.

Garbage Collection

Python relies on garbage collection to free up memory. Rust, however, doesn’t use a garbage collector as it handles memory at compile-time rather than run time.

Scalability

Regarding core design, Rust offers a more scalable architecture thanks to proper memory management, error handling, and the ability to interact with the hardware directly. However, Python can also be used to build scalable solutions, primarily because of available vertical or horizontal scaling options.

Community and Documentation

Python has a rich ecosystem and a vast community. It also offers excellent documentation which covers almost every aspect of its programming language. So, if you’re developing in Python, you’ll find help instantly in official documentation, video, or community.

Rust does fairly in community and documentation. The fact that it is new means a small community with fewer resources to fiddle with. However, its documentation has grown strong each year and offers a comprehensive outlook on what Rust offers.

Which one should you learn?

Choosing between Python and Rust takes work. Both are excellent programming languages. However, you may find that each has its strengths and weaknesses. Rust’s primary goal is to provide developers with the tool to create bug-free, high-performance apps, and services. Its memory management is unmatched, but it can take longer for teams to ship prototypes and final products due to its strict development rules.

In short, you should learn Rust if:

• You want solutions that use concurrency at its core.
• You want to scale your applications to meet users’ demands.
• You want to do low-level programming with access to logical and functional syntax.
• You want your code to be easily maintainable, as Rust’s old codes are compatible with newer versions.
• You want to benefit from the Rust high demand in the market.

Python, on the other hand, excels at prototyping. As a result, learning is easy, and teams can start with Python faster than Rust or any other programming language. Moreover, Python’s modern features, such as functional programming, object-oriented support, and abstractions, are well known to aid development. On top of that, Python is easy to maintain.

You should learn Python if:

• You want to do a data science project and benefit from its extensible visualization options.
• You want to create web apps that are easy to develop and maintain.
• You want to become in demand as a Python developer.
• You want to do web scraping or data extraction.

If you’re entirely new to programming, it is better to start with Python and shift to Rust. For experienced programmers, Rust can feel more powerful. However, you should consider future goals before learning any of these programming language.

In short, always remember that Python and Rust are programming language tools.

They are a way for you to create your desired output. So, pick a tool that lets you reach your goals.

When to use it?

In the previous section, we discussed which one should learn. However, it doesn’t guide you as you still need to figure out when to use Rust or Python. So let’s resolve it in this section.

When to use Rust?

Rust’s low-level performance, zero-cost abstraction, and excellent memory management make it ideal for the following purposes:

• Programming an operating system or microcontroller applications as you can connect to the hardware with Rust’s ability to do low-level programming.
• Rust is also an excellent pick for projects where you need to rewrite replacement software parts’ programming. Rust offers an excellent foreign-function interface so that you can write better-performing code for these parts.
• If you’re working with Embedded systems, you can make the most out of Rust as it can directly access the underlying hardware, including CPU, memory, and storage.

These’re not all the use cases. To better understand Rust’s ability to solve problems, you can see how companies like Figma or Coursera solve their proprietary platform-specific issues.

When to use Python?

Python is a general-purpose programming language that fits various use cases. These include:

• Python is an excellent pick for web development. It has a vibrant web ecosystem where you can use Python frameworks such as Django and Flask to create your web app.
• Python is very effective in data analysis and visualization. It has a rich visualization library and frameworks.
• Python is also a popular machine learning and artificial intelligence choice. It offers dedicated tools and libraries to do ML and AI projects.

Conclusion: Which One is Better?

There is no real winner when it comes to programming language. At the core of each programming language, a philosophy guides it. Python and Rust’s core philosophies are different.

Python’s philosophy is ease-of-use, prototype-friendly, and maintenance-friendly. On the other hand, Rust primarily focuses on giving programmers the tool to develop bug-free, high-performance solutions. This makes Rust hard to learn and use. It also means developers spend more time perfecting the solution before releasing it. However, an almost perfect Rust app means less technical debt and maintenance.

You can choose Python for scientific research, data science, and web development. However, if you’re doing neural network development, WebAssembly development, or blockchain development, Rust seems to be a better choice.

The post Rust vs Python – Is THIS the Language of the FUTURE? appeared first on Simple Programmer.

The suggested timeline for this is 4-8 months, but depending on your existing knowledge, motivation, and amount of time for study, you could finish the self-paced course more quickly – or even spread out your learning over a whole year.

The training is part of Codecademy’s Pro subscription – meaning it takes some monetary investment to go through it.

I’ll do my best to show you what this course is all about, reviewing the different modules and Codecademy’s teaching methodology, so you can make an informed decision whether the Full Stack Career Path is right for you.

About me and this review

In my decade plus as a Software Developer, I’ve learned multiple programming languages to where I could teach them to others. At one point I created over 50 coding courses for a popular learning platform.

This taught me about how information should be relayed so that the students learn most efficiently. And I’ll be holding Codecademy to that same standard in this review.

Why consider taking Codecademy’s Full Stack Engineer Career Path?

There’s many ways (free and paid) to learn Front-End and Back-End development online. The draw of Codecademy’s Career Paths is the streamlined curriculum taking you from start to finish in just a few months, without having to do a bunch of manual research and keep jumping back and forth between different resources.

The attractive user interface has been created to make learning more immersive and fun. There’s also a community within the platform to help you out whenever you’re stuck.

All in all, their offer does seem to give some compelling reasons for choosing Codecademy over other ways of becoming a Full-Stack Engineer.

The timeline

The whole career path has 50 units with 168 total lessons. There’s several intermediate-level projects to apply your new skills, as well as multiple code challenges inside each unit. 

Let’s not kid ourselves – to become a Full-Stack Engineer from scratch, you’ll need to put in a serious amount of work.

For each lesson, you should be getting your hands dirty implementing the code yourself. And coding out those complete projects will take a bunch of effort and time as well. 

6 months is a reasonable timeline to go through the course in this focused manner. If you’re highly motivated, smart, and with a lot of free time on your hands, you might be able to do it in three months, or even two.

The exact timeline depends on you and your circumstances.

How it works

The curriculum consists of a number of modules, each teaching you one major aspect of Full Stack development. 

The text-based lessons inside each module introduce you to one concept at a time, which you’re then asked to implement via Codecademy’s signature built-in coding environment.

At the end of a module, you need to pass a two-part exam to further prove your learnings and receive your Codecademy Certificate at the end.

Features of Codecademy’s Full Stack Engineer Career Path

Let’s now have a look at what exactly is inside the program:

Modules

There are 6 modules in total, aimed at progressing you from the basics to job-ready.

Module 1: Web Development Fundamentals

Here you’ll be learning how to use HTML & CSS to create the scripts for websites. This includes local development, deployment, and styling your websites using CSS.

Module 2: Interactive Web Development with JavaScript

JavaScript is used to make websites interactive – and that’s what Codecademy will teach you in this module. By the end, you’ll be asked to create your very own portfolio website.

Module 3: Front-End Development

The Front-End development module will go deeper into JavaScript development and testing, as well as introduce the React framework, and give further instruction on how to use Git and GitHub.

The portfolio project for this module will be to build your own Reddit-inspired message board app. 

Module 4: Back-End Development

For the Back-End part of the career path, you’ll dive into using the Express.js framework in the back end, as well as databases with PostgreSQL and REST APIs. You’ll then build your own e-commerce app with REST API.

Module 5: Full-Stack Development

In the fifth module you’ll first learn about Front-End to Back-End connection and deploying web apps.

Then you’ll get a deeper education in security and DevOps.

You’ll finish by fleshing out the client side of your e-com app and merging it with the back-end you’ve already built.

Module 6: Interview Preparation

The interview prep module is interesting for those who actually want to get a job as a Full-Stack developer.

It teaches you everything from data structures & algorithms to the soft skills you need to win at both the technical and behavioral part of Software Engineering interviews.

Projects

Lesson Projects

These are smaller projects you find inside almost all lessons. They come with many hints, holding your hand until you’ve coded the solution.

Challenge Projects

You can either complete the projects inside the built-in environment (and share it by creating a Gist), or off-platform (and share it on GitHub) as well. 

Afterwards, you can download Codecademy’s solution code and compare it to yours.

They do have some starter code to get you running, but you’ll be doing most of the work yourself.

Portfolio Projects

Portfolio projects are meant to get you to become autonomous as a developer – able to create your own applications from scratch, from architecture, to coding, to deployment.

As opposed to Codecademy’s other more hand-held projects, you’re asked to gather your own resources, and write an individual app using your own code.

The result is something you can confidently show off to potential employers, in contrast to the guided projects which thousands of others have built in the same way.

Hence the name portfolio projects!

Quizzes

Codecademy have created a number of quizzes for you to test your retention of important Full-Stack concepts – while keeping your learning journey as fun and interesting as possible.

Community

The community feature you get with Codecademy is invaluable. No matter how thorough the educational material, it’s inevitable you’ll get stuck at some point.

That’s where the member forums come to the rescue. For any obstacle you run into, there will be someone who’s been there before and can share their insights with you.

On top of that, you can can create your own journal-type thread to document your progress with the Full-Stack curriculum.

The accountability and feedback you get from this community of peers can be most motivating and helpful.

Pros & Cons

Pros:

• The interactive UI is one of Codecademy’s strongest points
• The abundance of code challenges, quizzes and projects means your learning will never be passive, but always very hands-on
• The training is laid out very well, with lessons building on one another
• They’ve done a great job at combining guided learning with getting you to be more and more self-sufficient the further along you are in your journey to Full-Stack

Cons:

• Codecademy is mostly text- and code-based with few instructional videos. If you’re a very visual learner, it might not be best for you – check alternatives to Codecademy.
• The monthly Pro subscription is not necessarily cheap. If saving money is your prime concern, you might want to consider learning from free resources and tutorials instead.
• It doesn’t include one-to-one or group coaching calls or mock interviews, like a higher-priced online bootcamp would
• Codecademy’s certificate of completion is not equal to a cert from a higher education institution

Pricing

The Pro subscription required to access the Full-Stack Career Path will run you $29.99 monthly, or 20% less with yearly billing (23.99/month).

This is reasonable if you’re serious about putting in the work and getting to Full-Stack with a few months of focused study.

But it might be too much if you’re just looking to dabble in the topic, and you’re not going to spend that much time with the materials.

Compared to other platforms like Udemy, Codecademy is more expensive – but you also get a focused, multi-month curriculum. Considering there’s a whole module dedicated to interview prep, you could see the course as affordable.

Most stand-alone coding interview prep courses cost a similar amount, and they don’t teach you coding.

So whether the price is expensive or not depends on your goals and likely level of commitment.

7-day trial

Even if you’re not sure you want to stick with the Full-Stack Engineer Career Path for the long haul, you get the option to test-drive it for a week, entirely free.

That’s enough time to scan through the material – even complete the first few lessons – and see if it suits you and you can see yourself working with the training for the next few months.

Will it get you a job?

This course will not guarantee you a job as a Full-Stack Engineer.

What it will do is put you into a great position.

If you diligently completed the program, and created some unique portfolio projects all by yourself – that’s a good selling point to potential employers.

Of course, even after the training, you should keep sharpening and expanding your skills, and creating more and more real-world projects, preferably by joining forces with others as well.

The skills you’ve learned at Codecademy might be enough to land you a job – or it might take you more months of leveling up and getting your name out there.

Either way, you’re on a forward path of continuous improvement, and before long you’ll be able to break into professional development.

Final verdict – Do I recommend the Full Stack path?

In my opinion Codecademy is a great all-around option for learning Full-Stack development.

• They’ve nailed the step-by-step and interactive aspect, always motivating you to keep learning.
• The structure and the abundance of both guided and autonomous projects are excellent.
• The monthly price is fine if you’re actually using the platform a lot.

And while the certificate is not the same as a degree or bootcamp cert, it’s still valuable, especially if you’ve no work experience to show for.

Overall, I would recommend the Codecademy Career Path to anyone looking to seriously dive into Full-Stack development.

If you at any point feel it’s not challenging you enough, you can always add on other books and resources.

With any course, that’s a good idea anyway.

The post Codecademy Full Stack Engineer Career Path Review (2023) appeared first on Simple Programmer.

And if you’re not sure which one fits your project – check out this comparison article, in which we’ll look deeper into Rust vs. Go.

By the end of the comparison, you’ll have a clear picture of what Rust and Go offer. We’ll cover their key features, pros & cons, similarities, and differences and discuss the right pick based on your requirements. 

On top of all these, we’ll also argue that most teams might be able use both to power their applications, and reap benefits over sticking to just one programming language.

So, why the wait? Let’s begin.

What is Rust?

Rust is a high-level, multi-paradigm, memory-safe programming language to solve some of the problems encountered with C++. As it’s inspired by C++, it’s also statically typed and has a similar syntax to C++.

Unlike other modern programming languages, Rust focuses heavily on high-performance and secure applications. So, if you want to create a safe, yet fast app, choosing Rust is the right move.

Rust’s core design philosophy encapsulates many new ideas. These include its ownership and borrowing model, forcing developers to write bug-free code. So, you can write bug-free code as the compiler tells the programmer to fix all the issues beforehand.

Who uses Rust?

Even though Rust is a new programming language (first developed in 2006 by Graydon Horare), it has seen much success.

The first big founding block of Rust is its Rust Foundation. Many big companies, including Google, Microsoft, Amazon, and Dropbox, are part of the foundation. All of these companies are using Rust in their production systems.

Rust is also popular among developers, ranking as the number-one loved language for 7 consecutive years. A few of the exciting use cases for Rust are:

• Figma’s use of Rust to improve front-end experience, and 
• Coursera’s use of Rust to power web-based assignment solutions. 
• Dropbox also uses Rust to improve its file synchronization engine. 
• And one last example worth noting is npm, a JavaScript package manager, which uses Rust for its main service. They chose to go with the language because to avoid bottlenecks in their service.

Rust key features

Rust excels as a fast-performance and memory-safe programming language. It does it with the help of multiple features, including zero-cost abstraction, memory, and thread safety.

It comes with an excellent compiler that offers insights into error messages. You also get pattern matching, move semantics, and type interface.

Two key features are zero-cost abstraction and memory safety.

• Zero-cost abstraction means that Rust can offer low-level memory access while using high-level programming concepts. 
• With no overhead, Rustaceans can create complex applications without worrying about performance penalties.

But, the most fascinating Rust feature is its ownership model that drives memory safe development environment. It enforces a strict rule on how memory can be allocated and accessed through borrowing models, which results in memory-safe programs.

It also offers thread safety, ensuring concurrency programs don’t run into race conditions.

What is Go?

Go (Golang or Go language) is an open-source statically typed programming language that models itself on C. In 2007, Google sought answers to improve productivity, especially around networked machines, large codebases, and multi-core.

Google kept it under its control at first, but open-sourced it after two years, in 2009. Two of the best minds, including Ken Thompson, Robert Gresemer, and Rob Pike, created the Go language. 

Golang’s robust standard library makes it easy to learn and build upon. It offers simplicity like Python and also something called goroutines which make it an excellent programming language for building concurrency-powered apps and services.

Golang is also a great choice for building web apps. Apart from that, it is also great for large projects and multi-core processors. 

In short, Go solves multiple problems, including slow build time, uncontrolled dependencies, difficulty writing automatic tools, and cross-language development.

Who uses Go?

Many companies use Go. These include Google, Netflix, Riot Games, Uber, Twitter, Salesforce, and Paypal. 

For instance, Uber uses Golang for their geofencing service. This service handles the user’s location and Uber’s service availability. Their team quickly shifted to Go as it is easy to learn and gives their geofence service a new life with 99.99% uptime and reliability.

Dropbox, a leading cloud storage company, utilizes Go to scale its systems in the most efficient way. They also shifted to Go from Python for more critical backends, improving concurrency.

Lastly, we have Riot Games — a leading video game developer company that uses Go in most of their products, including their entire backend microservice architecture.

Go key features

Golang excels as a programming language due to its unique take on many programming concepts. Some of its key features include:

Concurrency model: Go excels in concurrency. It offers a concurrency model that lets developers create concurrent operations to operate flawlessly.

The parallelism is achieved by goroutine, an independent Golang function that provides lightweight threads to concurrency.

In addition, Go also offers channels that offer bidirectional communication between goroutines. These channels can include unbuffered and buffered channels, which require present and future values for successful operations.

Lastly, it also uses WaitGroups to make the program wait to finish thread execution.

Standard library: Go has an excellent standard library with access to plenty of pre-written code for easy access and use. This allows developers to implement different features and build apps faster and more efficiently.

However, how is this different from standard libraries of other programming languages, such as Rust or Python? In this case, you can expect libraries that generally need third-party solutions.

Simple to use: Go is simple to use. It offers a simplistic language specification, enabling the team to use Go with less of a learning curve.

For example, simple rules such as making the function name UPPERCASE works wonders to improve readability while keeping everyone using the same formats for better readability.

Static typing: Go is a statically typed programming language. It means you need to tell the compiler the variable type before it starts compilation. This helps with catching errors and ensures better code readability. 

Code package management: Golang offers Go Modules, a built-in package management system. As you grow, you may also add external packages. The Go package manager deals with package dependency by managing installation, updates, and removal.

Rust Pros and Cons

Just like any other programming language, Rust has its pros and cons. Let’s list them below.

Rust Pros

Rust offers excellent performance out of the box while matching C++ performance, thanks to zero-cost abstraction. With it, developers can directly access hardware while having access to high-level paradigms.

Additionally, Rust offers LLVM optimization, HashMap APIs, and much more.

Rust requires low memory to function as it offers excellent memory control. It also doesn’t require Garbage Collector.

Rust’s compiler spits out easy-to-understand error messages.

A solid toolchain eases development workflow, powered by Cargo package manager and others.

The language supports cross-platform development.

Rust Cons

• Rust is relatively new, which means its documentation and libraries haven’t matured yet. This can lead to developers having to adjust their Rust application to new features frequently.
• Rust’s unique approach to ensuring memory safety is not easy to implement. If you’re new to Rust, you must learn and practice how it works. This makes coding Rust apps time-consuming and unsuitable for rapid application development (RAD).
• Rust’s compiler does provide a detailed error message with explanations. But, it fails to create a stack trace which is required for effective debugging. To bypass the cons, developers can use tools such as error-chain.
• Rust’s approach of weeding out every single error means slow compile time.

Go Pros and Cons

Lets look into Golang’s pros and cons:

Pros of Go

• Golang is simple to understand and use. Its simplistic approach makes it great for teams and big projects.
• Offers rich standard libraries with functionalities and features that developers would usually need third-party libraries for.
• A garbage collector for easy memory management.
• Go programming language has Google’s name attached to it
• Go comes with smart documentation 

Cons of Go

• Due to its “easy-to-use” philosophy, Go can facilitate sloppy coding practices – which might end up causing performance issues down the line
• The automated garbage collector can lead to memory safety issues.
• Go is a relatively new language which means it is yet to mature in terms of tooling and some other features.
• No GUI library.

Rust vs Go Comparision

Rust and Go are relatively new programming languages that solve problems with old programming languages such as C and C++. Both are open-source and offers developers the tools to meet modern development requirement.

Below, we’ll go through their similarities and then differences. Let’s get started.

Rust vs Go Similarities

In some regards, Rust and Go are quite similar. Here’s what they have in common:

Open-source

Both Rust and Go are open source. If we look at history, Rust was launched with an open-source tag. It welcomes new developers and contributors to build the community. 

However, the same is not true for Go.

When Go was first created in 2007, it was not open source. Google waited 2 years before making it open source in 2009.

Their open-source nature means better development experience. This way, developers can include their packages in the project and let Rust and Go’s package management handle them by automatically fetching and building the packages.

Performance

Performance-wise, Rust and Go are high-performing programming languages. They enable you to write efficient code using hardware resources directly. 

Concurrency

Concurrency lets developers run tasks in parallel for more efficiency and scalability. Rust and Go offer concurrency models that let developers effectively build apps and solutions utilizing multi-core processors.

Team friendly

Teams need to look into tools that help them collaborate for a long time. In this case, both Rust and Go excel.

For example, both handle code formatting with proper tooling — Gofmt for Golang and rustfmt for Rust. Both automatically format the source code so that team members are always on the same page.

Lastly, we have code readability. Go sports excellent readability similar to Python, and Rust is just slightly behind. This improves code review time – and developers can add new features without spending too much time understanding the code.

Safety

Both Rust and Go programming languages have excellent security out of the box. For instance, any application you create using Rust or Go is completely secure from attacks such as buffer overflows, malware and brute force attacks.

This way, developers don’t have to worry about common security issues and can focus on making their applications more robust and feature-rich.

Additionally, their team works hard to address any core programming language loopholes. Finally, they offer a proper submission methodology, where their team of experts patches the security loophole as soon as possible. 

However, Go and Rust each have unique ways of managing security. We’ll cover this more in detail in the “Security” section under Rust vs. Go differences.

Portability

Developers can create portable applications using Rust or Go. Both follow the “write once, compile anywhere” philosophy. Rust, for example, can work across different operating systems using LLVM compiler infrastructure.

In addition, the infrastructure is capable of running across different hardware architectures. Furthermore, Rust’s standard library offers cross-platform abstractions, making it truly portable.

Go’s portability is enhanced by self-contained runtime, not having to rely on third-party/external libraries to run the program. Just like Rust, Go offers cross-platform abstractions.

Rust vs Go Differences

In this section, we’ll look closely at Rust vs. Go differences. If you’re in a hurry, check out the Rust vs Go comparison table.

Popularity

Undoubtedly, Go is more popular than Rust because Golang was released earlier. This means Go had more time to build a community, related frameworks, libraries, and documentation. It’s backed by the power of Google’s name and its open source status.

If we look at numbers, Go beats Rust by just around 1.8% (11.15% vs. 9.32% in favor of Go) in the most popular technologies. However, Rust has stayed at the top of the most loved programming language for the past 7 years.

According to the TIOBE Index for April 2023, Go is in the 10th position, whereas Rust is in the 19th. The index is a pointer for getting an idea of what’s happening in the world of programming languages from the usage perspective, and they can use it to make strategic decisions.

Learning Curve

As Go values simplicity and a conventional approach, there’s an easy learning curve with the language. This makes it great for teams to pick up Golang quickly and start working on large codebases without feeling bogged down.

Its standard library enriches the Go ecosystem. You can pick the libraries you need and jump into your project.

Rust, on the other hand, has a steep learning curve. It’s because it follows a different philosophy than Go. 

Rust aims to give programmers the tools to create secure and bug-free code. To achieve this, Rust introduces many new concepts and models, including the ownership and borrowing model that requires programmers to think about stack and heap. 

All of these need a lot of time to learn and perfect before programmers become confident to use Rust at the production level. However, once known, Rust can become easier to implement, resulting in a high-performance, secure, and bug-free application.

Performance

Performance is one of the most significant talking points between Rust and Go difference. Considering that both Rust and Golang offer high performance, it is essential to know which one is faster and by how much.

If you check the publicly available Rust versus Go benchmark, you’ll notice that Rust is faster than Go in most scenarios.

On top of that, Rust offers a robust model for developers who want to create fast applications that are also predictable. It gives developers complete control of hardware and reaches maximum performance with reliability.

Go also offers high performance but is created for faster development time, which ends up producing a speed deficit compared to Rust programming language. 

Concurrency

Both Rust and Golang support concurrency. Go has complete concurrency support, whereas Rust’s concurrency is still under active development.

Go implements concurrency with its goroutines. Therefore, it is an excellent alternative to operating system threads as these goroutines threads. These threads can execute Go functions separately and map them to the OS threads. In addition, these threads can safely share data through Go channels.

This approach of complete control over lines gives Go developers full control over its execution and behavior.

So, if you’re building a scalable app that utilizes hardware’s multi-core capacity, then Go is a perfect choice. Golang also fits into high-scale applications. For example, you can use it to build and manage microservices.

Rust’s concurrency model is different as it takes advantage of its ownership and type systems. As the Rust compiler looks for memory issues, most concurrency problems are solved at compile-time. Rust names its approach fearless concurrency, where your code is free from subtle bugs and easy to refactor. 

Rust uses message-passing concurrency, creating channels between threads to send and receive messages. It also has Shared-state concurrency, Sync, and Send traits for easy concurrency management.

Overall, you can implement concurrency in both Rust and Go. However, if you want 

a straightforward approach with excellent concurrency support, Golang comes out ahead.

Memory Management and Safety

Golang uses a garbage collector to manage memory. This means it takes time for the data to get released. It is optimized but does come with some overhead. However, Go’s garbage collector runs periodically.

Rust, on the other hand, doesn’t use any garbage collector. Its approach is rigorous, and it requires the developer to take control of memory management. It would help if you did proper compiler checks to avoid data race conditions, making it very challenging, at least initially.

Updates

Rust is a new programming language that gets a lot of updates. These can be security or feature updates. Rust’s release cycle is set to 6 weeks, but that doesn’t guarantee new features, as some features can take years to develop before being released. 

On average, you can expect anywhere between 10-15 updates per year. This is great for the future of Rust language but can become a headache for developers trying to keep up. It means constantly looking to adjust their application code and the need to learn new things. 

Go, on the other hand, aims to offer a stable experience. It is now almost 15 years old and requires less frequent updates. Go receives two updates on average every year, which is way fewer compared to Rust.

Which one should you learn?

You should choose Rust if:

• you want to create a high-performance application that don’t run into race conditions
• you’re writing an operating system or hardware-level code
• you’re working on memory-safe feature
• you want to create a codebase that is easily maintainable
• you want to have complete control over concurrency threads
• you’re looking to build zero-cost abstraction solutions

You should choose Go if:

• your team wants to pick up a programming language that is easy to learn and work with, individually or as a team.
• you want to take advantage of multi-core modern processors
• you’re building scalable solutions
• you’re building a solution for simplicity and readability
• you want easy syntax
• you want a flexible web development programming language

When to use?

These are the use cases or scenarios for Rust or Go:

Rust

• Programming microcontrollers
• Systems programming

Go

• Building server-side applications, microservices, or network programming
• Creating Web APIs
• Web development
• Databases development

Final Words

Rust vs. Go — a fight of modern programming languages where you’re the only winner. As a programmer, team, manager, or developer, your job is to pick a programming language that fits your requirements. That’s why it doesn’t matter if Rust is better than Go or Go is better than Rust.

If you’ve been following along, you’ll have noticed that Rust and Golang have common grounds, be it performance, memory safety, concurrency, and their open source nature. However, there are differences in how each programming language achieves its goals.

Undoubtedly, picking Rust can be a challenging decision. But nothing can beat Rust if you’re creating a high-performance app where memory safety is crucial, with complete control over threads and hardware interaction.

Similarly, Go lends itself for use in big teams – with similar features to Rust, while offering simplicity, ease of learning, and an excellent standard library.

So, which one are you picking for your project? Comment below and let us know.

The post Rust vs Go – Comparison and How Each Fits Your Needs appeared first on Simple Programmer.