Julia vs Racket

Overview

Julia

Stacks666

Followers677

Votes171

GitHub Stars47.9K

Forks5.7K

Racket

Stacks92

Followers83

Votes54

Julia vs Racket: What are the differences?

<Write Introduction here>

Syntax: The most distinct difference between Julia and Racket lies in their syntax. Julia follows a more traditional programming language syntax similar to Python and MATLAB, making it easier for users already familiar with these languages to transition to Julia. On the other hand, Racket has a unique syntax that is based on s-expressions, which might be unfamiliar to those used to C-style languages.
Performance: Julia is renowned for its high performance, often rivaling languages like C and Fortran. This is attributed to its Just-In-Time (JIT) compilation process, allowing for efficient code execution. In contrast, Racket's performance is not as optimized as Julia, as it is primarily designed for educational and rapid development purposes rather than high-performance computing tasks.
Type System: Another prominent difference is their type systems. Julia is dynamically typed, enabling flexibility and ease of use, while also providing the option for type annotations for performance optimization. Racket, on the other hand, features static typing by default, requiring explicit type declarations which can aid in catching errors early in the development process.
Community and Ecosystem: Julia has a rapidly growing community and an expanding ecosystem of packages and libraries directed towards scientific computing, machine learning, and data analysis. In comparison, Racket focuses more on its integrated development environment (IDE) and tools for teaching and research, leading to a smaller but dedicated community and ecosystem.
Parallelism and Concurrency: Julia has robust support for parallelism and concurrent programming, making it a suitable choice for tasks that can benefit from utilizing multiple cores or distributed computing. Racket, on the other hand, has less emphasis on parallelism and concurrency features, focusing more on language extensibility and domain-specific languages.
Learning Curve: Julia is designed to be intuitive and user-friendly, with a low learning curve for those familiar with mathematical languages. In contrast, Racket's unique syntax and emphasis on functional programming concepts may pose a steeper learning curve for beginners, requiring time to grasp the fundamentals and conventions of the language.

In Summary, Julia excels in performance, syntax familiarity, and parallelism support, while Racket shines in its educational tooling, static typing, and community focus.

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CLI (Node.js)

Manual

Detailed Comparison

Julia	Racket
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.	It is a general-purpose, multi-paradigm programming language based on the Scheme dialect of Lisp. It is designed to be a platform for programming language design and implementation. It is also used for scripting, computer science education, and research.
-	Multi-paradigm; Object-oriented;Cross-platform;Powerful macros & languages;DrRacket IDE & tons of documentation
Statistics
GitHub Stars 47.9K	GitHub Stars -
GitHub Forks 5.7K	GitHub Forks -
Stacks 666	Stacks 92
Followers 677	Followers 83
Votes 171	Votes 54
Pros & Cons
Pros 25 Fast Performance and Easy Experimentation 22 Designed for parallelism and distributed computation 19 Free and Open Source 17 Calling C functions directly 17 Dynamic Type System Cons 5 Immature library management system 4 Slow program start 3 JIT compiler is very slow 3 Poor backwards compatibility 2 No static compilation	Pros 4 Meta-programming 3 Hygienic macros 2 Language-oriented programming 2 Great libraries 2 Open source Cons 2 LISP BASED 2 No GitHub
Integrations
GitHub Azure Web App for Containers GitLab Slack C++ Rust C lang Stack Overflow vscode.dev Python	Windows Oracle MySQL Cassandra PostgreSQL Linux IBM DB2 SQLite macOS Microsoft SQL Server

What are some alternatives to Julia, Racket?

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.

Bower

Bower is a package manager for the web. It offers a generic, unopinionated solution to the problem of front-end package management, while exposing the package dependency model via an API that can be consumed by a more opinionated build stack. There are no system wide dependencies, no dependencies are shared between different apps, and the dependency tree is flat.

Elm

Writing HTML apps is super easy with elm-lang/html. Not only does it render extremely fast, it also quietly guides you towards well-architected code.

PureScript

A small strongly typed programming language with expressive types that compiles to JavaScript, written in and inspired by Haskell.

Composer

It is a tool for dependency management in PHP. It allows you to declare the libraries your project depends on and it will manage (install/update) them for you.

pnpm

It uses hard links and symlinks to save one version of a module only ever once on a disk. When using npm or Yarn for example, if you have 100 projects using the same version of lodash, you will have 100 copies of lodash on disk. With pnpm, lodash will be saved in a single place on the disk and a hard link will put it into the node_modules where it should be installed.

Bun

Develop, test, run, and bundle JavaScript & TypeScript projects—all with Bun. Bun is an all-in-one JavaScript runtime & toolkit designed for speed, complete with a bundler, test runner, and Node.js-compatible package manager.

Homebrew

Homebrew installs the stuff you need that Apple didn’t. Homebrew installs packages to their own directory and then symlinks their files into /usr/local.

fpm

It helps you build packages quickly and easily (Packages like RPM and DEB formats).

SDKMAN

It provides a convenient way to install, switch, list and remove candidates. Using it, you can now manage parallel versions of multiple SDKs easily on any Unix-like operating system.

Related Comparisons

Julia vs Racket: What are the differences?

<Write Introduction here>

Syntax: The most distinct difference between Julia and Racket lies in their syntax. Julia follows a more traditional programming language syntax similar to Python and MATLAB, making it easier for users already familiar with these languages to transition to Julia. On the other hand, Racket has a unique syntax that is based on s-expressions, which might be unfamiliar to those used to C-style languages.
Performance: Julia is renowned for its high performance, often rivaling languages like C and Fortran. This is attributed to its Just-In-Time (JIT) compilation process, allowing for efficient code execution. In contrast, Racket's performance is not as optimized as Julia, as it is primarily designed for educational and rapid development purposes rather than high-performance computing tasks.
Type System: Another prominent difference is their type systems. Julia is dynamically typed, enabling flexibility and ease of use, while also providing the option for type annotations for performance optimization. Racket, on the other hand, features static typing by default, requiring explicit type declarations which can aid in catching errors early in the development process.
Community and Ecosystem: Julia has a rapidly growing community and an expanding ecosystem of packages and libraries directed towards scientific computing, machine learning, and data analysis. In comparison, Racket focuses more on its integrated development environment (IDE) and tools for teaching and research, leading to a smaller but dedicated community and ecosystem.
Parallelism and Concurrency: Julia has robust support for parallelism and concurrent programming, making it a suitable choice for tasks that can benefit from utilizing multiple cores or distributed computing. Racket, on the other hand, has less emphasis on parallelism and concurrency features, focusing more on language extensibility and domain-specific languages.
Learning Curve: Julia is designed to be intuitive and user-friendly, with a low learning curve for those familiar with mathematical languages. In contrast, Racket's unique syntax and emphasis on functional programming concepts may pose a steeper learning curve for beginners, requiring time to grasp the fundamentals and conventions of the language.

In Summary, Julia excels in performance, syntax familiarity, and parallelism support, while Racket shines in its educational tooling, static typing, and community focus.

Julia vs Racket

Overview