today, a fresh wave of coding languages has emerged, presenting inventive solutions and pushing the limits of what can be accomplished in the realm of software engineering.
This article by a seasoned software engineer and tech enthusiast Alex Babin (shared here with his permission).
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Coding languages play a vital role in shaping the manner we create software.
Throughout the years, we have observed the prevalence of established languages such as Python, Java, and C++.
Nevertheless, today, a fresh wave of coding languages has emerged, presenting inventive solutions and pushing the limits of what can be accomplished in the realm of software engineering.
In this article, I will explore some of these newly emerged programming languages you might have not heard of yet, uncovering their potential and unique characteristics. I’ll touch upon their scope and the problems they excel at solving and also include some code samples. Let’s start!\
Pony is a contemporary, statically classified, object-oriented coding language that highlights straightforwardness, efficiency, and actor-based parallelism. It provides developers with a safe and efficient environment for building highly concurrent and scalable applications.
With Pony, developers can write code without the common pitfalls of deadlocks and data races, as its type system ensures memory safety and eliminates the need for manual locking. Pony also introduces "reference capabilities," which label data based on how it can be shared.
However, Pony’s novelty means fewer resources and a smaller community for support. The unique syntax and semantics can be difficult for newcomers, and its standard library is not as comprehensive as those in more established languages, demanding more development from scratch.
Scope:
The Pony programming language is tailored to create high-performance, concurrent, and secure applications. It is especially fitting for crafting scalable and resilient systems, such as distributed and real-time applications, where concurrency and data integrity are of utmost importance.
Primary niche: concurrent programming
Especially good for developing:
Safety-critical systems, such as medical devices, aviation software, and autonomous vehicles
High-speed networking applications, including servers, routers, and real-time communication systems
Interactive entertainment and multimedia applications that demand rapid response times and optimal utilization of system resources
Pros and Cons:
Pros
Cons
Exceptional concurrency support
Limited adoption and community
Focus on safety
Small standard library
Impressive performance capabilities
Steep learning curve
Code sample:
Crystal is a compiled language that embraces static typing, fusing the inherent expressiveness reminiscent of Ruby with the inherent performance capabilities akin to languages such as C and C++. Crystal offers a familiar and readable programming style, making it a great choice for developers coming from a Ruby background.
Crystal's static type checking ensures type safety and improves performance, resulting in faster execution. It also provides powerful metaprogramming capabilities that allow developers to define custom macros and enhance code expressiveness.
When it comes to downsides, Crystal isn't yet as feature-rich as more established languages. Further, the compilation time can be quite long, which might deter some developers.
Scope:
Crystal's emphasis on web development renders it an optimal selection for designing high-velocity web applications, web services, and APIs.
Primary niche: web development
Especially good for developing:\
Scalable and high-performance web applications
Automation scripts, command-line tools, and DevOps-related tasks
Networking applications like TCP/UDP servers, proxies, and network protocols
Pros and Cons:
Pros
Cons
Ruby-like syntax
Limited library support and tooling
High performance
Less mature ecosystem
Easy to read and write code
Longer compilation time
Code sample:
Zig is a versatile, statically typed coding language that prioritizes efficiency, safeguarding, and comprehensibility. It strives to offer fine-grained authority while upholding user-friendliness and reliability. Zig's structure, influenced by the C programming language, renders it accessible to programmers well-versed in C or C++.
One of Zig's key strengths lies in its predictable memory management, which includes features like automatic memory deallocation and compile-time memory tracking. Its blend of low-level control and modern language features makes Zig a compelling option for developers seeking performance and reliability in their projects.
However, Zig is still in the early stages of development which means potential instability. Its community is small and the tooling is still under development. Also, the language does not yet offer a comprehensive standard library, which can necessitate extra work for programmers.
Scope:
Zig's interoperability with C codebases enables easy integration with existing projects, making it a powerful choice for systems programming, embedded systems, game development, and scripting.
Primary niche: systems programming
Especially good for developing:\
Low-level code, device drivers, operating systems, and embedded systems
High-performance game engines, rendering pipelines, and game logic
Efficient code for IoT and resource-constrained devices, such as sensors, microcontrollers, and wearable devices
Pros and Cons:
Pros
Cons
Excellent low-level control over code
Relatively new and evolving
Emphasis on safety and reliability
Limited library support
Good interoperability with other languages
Steep learning curve
Code sample:
Reason is an innovative statically-typed programming language that seamlessly melds the functional programming paradigm with the widely recognized syntax of JavaScript. Born out of Facebook's creative endeavors, Reason seeks to present a steadfast and dependable substitute to JavaScript for crafting web and mobile applications.
The core ambition of Reason lies in fostering predictability and circumventing typical errors by leveraging static typing and strong type inference. Reason's functional programming roots provide a rich set of features for building scalable and maintainable applications. It endorses immutable data structures, pattern matching, algebraic data types, and higher-order functions, enabling more expressive and fluid code.
Reason is relatively new, resulting in a small user base and fewer resources for learning and problem-solving. Its interoperability with JavaScript is a key feature, but there can be complexities and inefficiencies in this interoperation which could be a source of confusion or performance issues.
Scope:
Reason finds applications in various domains, including web development, mobile app development, and backend development. It is particularly well-suited for complex applications that require strong typing, concurrency, and reliability.
Primary niche: front-end development
Especially good for developing:
Cross-platform mobile applications
Compilers, static analyzers, and other development tools
Scalable and maintainable web applications in finance and healthcare\
Pros and Cons:
Pros
Cons
Strong type inference
Smaller community compared to other languages
Interoperability with JavaScript
Limited industry adoption
Functional programming features
Limited tooling integration
Code sample:
V emerges as a contemporary programming language that was designed with a focus on developer productivity and aims to eliminate common pitfalls found in other programming languages. One of the key features of V is its simplicity. The syntax is designed to be straightforward and easy to understand, reducing the cognitive load on developers. It takes inspiration from C and Go, resulting in a familiar and intuitive programming model.
V emphasizes strong type checking and automatic memory management, reducing the occurrence of bugs and memory-related issues. The language encourages explicit error handling and offers built-in support for concurrency and parallelism, making it suitable for building concurrent and high-performance applications.
The language also focuses on minimizing resource usage.
Vlang's simplicity and performance are promising, but its novelty results in a lack of comprehensive libraries and the small community. The language is also under constant changes which may cause instability and compatibility issues.
Scope:
V supports both server-side and client-side development, making it suitable for building web applications, APIs, and command-line tools. Additionally, its interoperability with existing C code allows seamless integration with libraries and frameworks.
Primary niche: systems programming
Especially good for developing:
Operating systems, device drivers, embedded systems, and other software that interacts closely with hardware
Web applications, APIs, and backend services
Applications that have compatibility across various operating systems, including but not limited to Windows, macOS, Linux, etc.
Pros and Cons:
Pros
Cons
Simplicity
Limited library support
Safety
Smaller community
Fast compilation speed
Immaturity of the language
Code sample:
Julia stands as a high-level programming language crafted explicitly for numerical and scientific computation endeavors, in the realms like data analysis, machine learning, simulation, and visualization. It combines the user-friendly nature and syntax of Python with the efficiency inherent to low-level languages such as C and Fortran.
A noteworthy facet within Julia's arsenal rests in its just-in-time (JIT) compilation, affording the capacity to dynamically compile code for streamlined execution. Additionally, Julia supports concurrent and distributed computing, empowering users to make use of multiple cores or even clusters of machines for speedier execution.
While Julia performs well in scientific computing and data analysis, it is less versatile in other areas. Its syntax can be unfamiliar to those accustomed to languages in the C family, and although it has a growing community, it's still not as large as those of Python or R.
Scope:
Julia strives to strike a balance between productivity and performance, positioning it as a compelling option for data scientists, researchers, and engineers engaged in computationally demanding undertakings.
Primary niche: data science
Especially good for:
Data analysis tasks, including data cleaning, processing, and statistical analysis
Training and deploying complex machine learning algorithms
Developing data-intensive applications and computationally intensive tasks that can benefit from parallelization
\ Pros and Cons**:
Pros
Cons
Extensive libraries and tools specifically designed for data science
Steep learning curve for beginners
High-performance
Limited application scope
Ease of use
Inefficient memory management
Code sample:
Final thoughts
These are merely a handful of examples illustrating the manifold programming languages that have surfaced in recent years. Trying out some of them can be a rewarding experience, allowing us to think differently, challenge traditional approaches, and enhance our programming skills. I personally find it immensely practical to monitor the programming languages landscape and am happy to share my findings with you.