Julia vs Python vs Ruby

Overview

Ruby

Stacks46.0K

Followers21.8K

Votes4.0K

GitHub Stars23.0K

Forks5.5K

Python

Stacks262.9K

Followers205.4K

Votes6.9K

GitHub Stars69.7K

Forks33.3K

Julia

Stacks666

Followers677

Votes171

GitHub Stars47.9K

Forks5.7K

Julia vs Python vs Ruby: What are the differences?

Ease of Learning: Julia is known for its simplicity and readability, making it beginner-friendly with concise syntax. Python, on the other hand, focuses on readability and simplicity, making it a popular choice for beginners. Ruby emphasizes the principle of least astonishment, aiming for code that is intuitive and easy to understand for newcomers.
Performance: Julia shines in terms of performance, with capabilities to match or even surpass C and Fortran in certain scenarios due to its just-in-time (JIT) compilation. Python, although versatile, tends to be slower in performance compared to Julia and is often associated with the Global Interpreter Lock (GIL) constraint. Ruby falls behind in terms of performance compared to both Julia and Python, making it less suitable for intensive computational tasks.
Community and Ecosystem: Python boasts a massive and active community with a plethora of libraries and frameworks for various applications, making it a go-to language for a wide range of projects. Julia, while growing, has a smaller community compared to Python but is rapidly expanding with a focus on scientific computing and data analysis. Ruby, with its robust community, is well-known for its web development frameworks like Ruby on Rails, catering to the web development domain.
Typing System: Julia has a type system that allows for parametric types, making it versatile for both dynamic and static typing paradigms. Python is dynamically typed, offering flexibility but potentially leading to runtime errors. Ruby, like Python, is dynamically typed, allowing for rapid development but may result in unexpected behavior due to its dynamic nature.
Concurrency and Parallelism: Julia provides built-in support for concurrent and parallel programming, making it easier to manage tasks simultaneously and efficiently utilize multiple cores. Python, with libraries like asyncio and multiprocessing, offers options for concurrent processing, but its GIL can limit true parallelism. Ruby lacks robust built-in support for concurrency and parallelism, often requiring additional libraries or tools to achieve similar functionality.
Syntax and Features: Julia features a mathematical syntax with high-level abstractions for numerical computing, catering to scientific and technical computing needs. Python prioritizes readability with a clean and structured syntax, suitable for a wide range of domains. Ruby emphasizes simplicity and elegance with a focus on human-centered design, making it easy to write and understand code efficiently.

In Summary, Julia excels in performance and mathematical computing, Python offers a vast ecosystem and simplicity, while Ruby prioritizes elegance and web development.

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Advice on Ruby, Python, Julia

Octavian

Software Engineer

May 26, 2020

Decided

Both PHP and Python are free but when it comes to web development PHP wins for sure. There is no doubt that Python is a powerful language but it is not optimal for web. PHP has issues... of course; but so does any other language.

Another reason I chose PHP is for community - it has one of the most resourceful communities from the internet and for a good reason: it evolved with the language itself.

The fact that OOP evolved so much in PHP makes me keep it for good :)

377k views377k

Comments

Avy

Apr 8, 2020

Needs adviceon

React Native

Python

Flutter

I've been juggling with an app idea and am clueless about how to build it.

A little about the app:

Social network type app ,
Users can create different directories, in those directories post images and/or text that'll be shared on a public dashboard .

Directory creation is the main point of this app. Besides there'll be rooms(groups),chatting system, search operations similar to instagram,push notifications

I have two options:

@{React Native}|tool:2699|, @{Python}|tool:993|, AWS stack or
@{Flutter}|tool:7180|, @{Go}|tool:1005| ( I don't know what stack or tools to use)

722k views722k

Comments

Davit

Apr 11, 2020

Needs advice

Hi everyone, I have just started to study web development, so I'm very new in this field. I would like to ask you which tools are most updated and good to use for getting a job in medium-big company. Front-end is basically not changing by time so much (as I understood by researching some info), so my question is about back-end tools. Which backend tools are most updated and requested by medium-big companies (I am searching for immediate job possibly)?

Thank you in advance Davit

390k views390k

Comments

Detailed Comparison

Ruby	Python	Julia
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.	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.	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.
Statistics
GitHub Stars 23.0K	GitHub Stars 69.7K	GitHub Stars 47.9K
GitHub Forks 5.5K	GitHub Forks 33.3K	GitHub Forks 5.7K
Stacks 46.0K	Stacks 262.9K	Stacks 666
Followers 21.8K	Followers 205.4K	Followers 677
Votes 4.0K	Votes 6.9K	Votes 171
Pros & Cons
Pros 608 Programme friendly 538 Quick to develop 492 Great community 469 Productivity 432 Simplicity Cons 7 Memory hog 7 Really slow if you're not really careful 3 Nested Blocks can make code unreadable 2 Encouraging imperative programming 1 No type safety, so it requires copious testing	Pros 1188 Great libraries 967 Readable code 849 Beautiful code 790 Rapid development 692 Large community Cons 53 Still divided between python 2 and python 3 28 Performance impact 26 Poor syntax for anonymous functions 22 GIL 21 Package management is a mess	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 No static compilation
Integrations
Rails	Django	GitHub Azure Web App for Containers GitLab Slack C++ Rust C lang Stack Overflow vscode.dev Jupyter

What are some alternatives to Ruby, Python, Julia?

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.

PHP

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

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

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 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# (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

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 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.

Elixir

Elixir leverages the Erlang VM, known for running low-latency, distributed and fault-tolerant systems, while also being successfully used in web development and the embedded software domain.

Swift

Writing code is interactive and fun, the syntax is concise yet expressive, and apps run lightning-fast. Swift is ready for your next iOS and OS X project — or for addition into your current app — because Swift code works side-by-side with Objective-C.

Related Comparisons

Julia vs Python vs Ruby: What are the differences?

Ease of Learning: Julia is known for its simplicity and readability, making it beginner-friendly with concise syntax. Python, on the other hand, focuses on readability and simplicity, making it a popular choice for beginners. Ruby emphasizes the principle of least astonishment, aiming for code that is intuitive and easy to understand for newcomers.
Performance: Julia shines in terms of performance, with capabilities to match or even surpass C and Fortran in certain scenarios due to its just-in-time (JIT) compilation. Python, although versatile, tends to be slower in performance compared to Julia and is often associated with the Global Interpreter Lock (GIL) constraint. Ruby falls behind in terms of performance compared to both Julia and Python, making it less suitable for intensive computational tasks.
Community and Ecosystem: Python boasts a massive and active community with a plethora of libraries and frameworks for various applications, making it a go-to language for a wide range of projects. Julia, while growing, has a smaller community compared to Python but is rapidly expanding with a focus on scientific computing and data analysis. Ruby, with its robust community, is well-known for its web development frameworks like Ruby on Rails, catering to the web development domain.
Typing System: Julia has a type system that allows for parametric types, making it versatile for both dynamic and static typing paradigms. Python is dynamically typed, offering flexibility but potentially leading to runtime errors. Ruby, like Python, is dynamically typed, allowing for rapid development but may result in unexpected behavior due to its dynamic nature.
Concurrency and Parallelism: Julia provides built-in support for concurrent and parallel programming, making it easier to manage tasks simultaneously and efficiently utilize multiple cores. Python, with libraries like asyncio and multiprocessing, offers options for concurrent processing, but its GIL can limit true parallelism. Ruby lacks robust built-in support for concurrency and parallelism, often requiring additional libraries or tools to achieve similar functionality.
Syntax and Features: Julia features a mathematical syntax with high-level abstractions for numerical computing, catering to scientific and technical computing needs. Python prioritizes readability with a clean and structured syntax, suitable for a wide range of domains. Ruby emphasizes simplicity and elegance with a focus on human-centered design, making it easy to write and understand code efficiently.

In Summary, Julia excels in performance and mathematical computing, Python offers a vast ecosystem and simplicity, while Ruby prioritizes elegance and web development.

Julia vs Python vs Ruby

Overview