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  1. Stackups
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  5. Haskell vs Julia

Haskell vs Julia

OverviewDecisionsComparisonAlternatives

Overview

Haskell
Haskell
Stacks1.4K
Followers1.2K
Votes527
Julia
Julia
Stacks666
Followers677
Votes171
GitHub Stars47.9K
Forks5.7K

Haskell vs Julia: What are the differences?

Introduction

This article compares the key differences between Haskell and Julia programming languages. Both Haskell and Julia are popular and powerful programming languages that are widely used in various domains. Understanding the differences between these two languages can help programmers choose the most appropriate language for their specific needs.

  1. Type System: One of the major differences between Haskell and Julia lies in their approach to typing. Haskell is a statically typed language, which means that variable types must be declared and are checked at compile time. On the other hand, Julia is a dynamically typed language, allowing variables to change their type during runtime.

  2. Syntax and Style: Haskell follows a pure functional programming paradigm and has a distinctive syntax that emphasizes immutability and pure functions. It uses indentation for expressing code structure and avoids the use of traditional looping constructs like 'for' and 'while' loops. On the contrary, Julia combines functional programming with imperative programming paradigms. It has a more traditional syntax similar to other imperative languages and allows the use of loops for iterative operations.

  3. Performance: Performance is another significant difference between Haskell and Julia. Haskell is known for its strong optimization capabilities and can produce highly optimized code. It achieves this through techniques like memoization, lazy evaluation, and strict typing. Julia, on the other hand, focuses on just-in-time (JIT) compilation to achieve high performance. It uses a type inference system to compile code on the fly and optimize it for specific hardware.

  4. Concurrent Programming: Haskell provides strong support for concurrent programming through its pure functional nature and constructs like lazy evaluation and immutable data structures. It has advanced mechanisms like Software Transactional Memory (STM) and lightweight threads for efficient parallelism. In contrast, Julia simplifies concurrent programming by providing built-in support for multi-threading, coroutine-based concurrent programming, and distributed computing.

  5. Community and Ecosystem: Haskell has a mature and active community with a rich ecosystem of libraries and frameworks, making it suitable for a wide range of applications. It has a strong emphasis on type-driven development, formal verification, and academic research. Julia, on the other hand, has a growing community with a focus on scientific computing, numerical analysis, and high-performance computing. It offers a wide variety of specialized packages for data analysis, visualization, and machine learning.

  6. Learning Curve and Adoption: Haskell is considered to have a steeper learning curve due to its unique approach to functional programming and type system. It requires understanding of concepts like monads, typeclasses, and lazy evaluation. Julia, on the other hand, has a relatively gentle learning curve and offers an easier transition for programmers familiar with other dynamic languages like Python or MATLAB. Haskell has been adopted by industries such as finance and academia, while Julia has found popularity in scientific research and computation-intensive domains.

In summary, Haskell and Julia differ in their type systems, syntax and style, performance optimization strategies, concurrent programming support, community and ecosystem, as well as the learning curve and adoption in different domains. These differences make them suitable for different types of applications and programming paradigms.

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Advice on Haskell, Julia

Timm
Timm

VP Of Engineering at Flexperto GmbH

Nov 10, 2020

Decided

We have a lot of experience in JavaScript, writing our services in NodeJS allows developers to transition to the back end without any friction, without having to learn a new language. There is also the option to write services in TypeScript, which adds an expressive type layer. The semi-shared ecosystem between front and back end is nice as well, though specifically NodeJS libraries sometimes suffer in quality, compared to other major languages.

As for why we didn't pick the other languages, most of it comes down to "personal preference" and historically grown code bases, but let's do some post-hoc deduction:

Go is a practical choice, reasonably easy to learn, but until we find performance issues with our NodeJS stack, there is simply no reason to switch. The benefits of using NodeJS so far outweigh those of picking Go. This might change in the future.

PHP is a language we're still using in big parts of our system, and are still sometimes writing new code in. Modern PHP has fixed some of its issues, and probably has the fastest development cycle time, but it suffers around modelling complex asynchronous tasks, and (on a personal note) lack of support for writing in a functional style.

We don't use Python, Elixir or Ruby, mostly because of personal preference and for historic reasons.

Rust, though I personally love and use it in my projects, would require us to specifically hire for that, as the learning curve is quite steep. Its web ecosystem is OK by now (see https://www.arewewebyet.org/), but in my opinion, it is still no where near that of the other web languages. In other words, we are not willing to pay the price for playing this innovation card.

Haskell, as with Rust, I personally adore, but is simply too esoteric for us. There are problem domains where it shines, ours is not one of them.

682k views682k
Comments
Alexander
Alexander

Senior researcher at MIPT

Oct 27, 2020

Decided

After writing a project in Julia we decided to stick with Kotlin. Julia is a nice language and has superb REPL support, but poor tooling and the lack of reproducibility of the program runs makes it too expensive to work with. Kotlin on the other hand now has nice Jupyter support, which mostly covers REPL requirements.

188k views188k
Comments

Detailed Comparison

Haskell
Haskell
Julia
Julia

It is a general purpose language that can be used in any domain and use case, it is ideally suited for proprietary business logic and data analysis, fast prototyping and enhancing existing software environments with correct code, performance and scalability.

Julia is a high-level, high-performance dynamic programming language for technical computing, with syntax that is familiar to users of other technical computing environments. It provides a sophisticated compiler, distributed parallel execution, numerical accuracy, and an extensive mathematical function library.

Statically typed; Purely functional; Type inference; Concurrent
-
Statistics
GitHub Stars
-
GitHub Stars
47.9K
GitHub Forks
-
GitHub Forks
5.7K
Stacks
1.4K
Stacks
666
Followers
1.2K
Followers
677
Votes
527
Votes
171
Pros & Cons
Pros
  • 90
    Purely-functional programming
  • 66
    Statically typed
  • 59
    Type-safe
  • 39
    Open source
  • 38
    Great community
Cons
  • 9
    Too much distraction in language extensions
  • 8
    Error messages can be very confusing
  • 5
    Libraries have poor documentation
  • 3
    No best practices
  • 3
    No good ABI
Pros
  • 25
    Fast Performance and Easy Experimentation
  • 22
    Designed for parallelism and distributed computation
  • 19
    Free and Open Source
  • 17
    Dynamic Type System
  • 17
    Calling C functions directly
Cons
  • 5
    Immature library management system
  • 4
    Slow program start
  • 3
    JIT compiler is very slow
  • 3
    Poor backwards compatibility
  • 2
    Bad tooling
Integrations
No integrations available
GitHub
GitHub
Azure Web App for Containers
Azure Web App for Containers
GitLab
GitLab
Slack
Slack
C++
C++
Rust
Rust
C lang
C lang
Stack Overflow
Stack Overflow
vscode.dev
vscode.dev
Python
Python

What are some alternatives to Haskell, Julia?

JavaScript

JavaScript

JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.

Python

Python

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

PHP

PHP

Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.

Ruby

Ruby

Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.

Java

Java

Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!

Golang

Golang

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

HTML5

HTML5

HTML5 is a core technology markup language of the Internet used for structuring and presenting content for the World Wide Web. As of October 2014 this is the final and complete fifth revision of the HTML standard of the World Wide Web Consortium (W3C). The previous version, HTML 4, was standardised in 1997.

C#

C#

C# (pronounced "See Sharp") is a simple, modern, object-oriented, and type-safe programming language. C# has its roots in the C family of languages and will be immediately familiar to C, C++, Java, and JavaScript programmers.

Meteor

Meteor

A Meteor application is a mix of JavaScript that runs inside a client web browser, JavaScript that runs on the Meteor server inside a Node.js container, and all the supporting HTML fragments, CSS rules, and static assets.

Scala

Scala

Scala is an acronym for “Scalable Language”. This means that Scala grows with you. You can play with it by typing one-line expressions and observing the results. But you can also rely on it for large mission critical systems, as many companies, including Twitter, LinkedIn, or Intel do. To some, Scala feels like a scripting language. Its syntax is concise and low ceremony; its types get out of the way because the compiler can infer them.

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