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  5. Common Lisp vs Julia

Common Lisp vs Julia

OverviewDecisionsComparisonAlternatives

Overview

Common Lisp
Common Lisp
Stacks269
Followers255
Votes145
Julia
Julia
Stacks666
Followers677
Votes171
GitHub Stars47.9K
Forks5.7K

Common Lisp vs Julia: What are the differences?

<Common Lisp and Julia are both powerful programming languages used for different purposes. Common Lisp is a multi-paradigm language known for its strong support for object-oriented, functional, and procedural programming, while Julia is a high-level, high-performance language designed specifically for scientific computing and data analysis.>

  1. Syntax: Common Lisp has a Lisp-like syntax with prefix notation, while Julia uses traditional infix notation similar to languages like Python and MATLAB.
  2. Typing: Common Lisp is dynamically typed, allowing variables to change types during runtime, whereas Julia is statically typed, requiring explicit type declarations for variables.
  3. Performance: Julia is often faster than Common Lisp due to its built-in just-in-time compiler, which optimizes code execution during runtime to achieve better performance.
  4. Package Ecosystem: Julia has a growing and extensive package ecosystem focused on scientific computing and data analysis, while Common Lisp has a smaller but dedicated community producing libraries mainly for general-purpose programming.
  5. Metaprogramming: Common Lisp has powerful metaprogramming capabilities, allowing developers to manipulate code as data, while Julia has metaprogramming features but with a different design philosophy aimed at enhancing performance.
  6. Community and Adoption: Julia has gained popularity in the scientific computing community for its performance and ease of use, while Common Lisp has a smaller but dedicated following within the Lisp community.

In Summary, Common Lisp and Julia differ in syntax, typing, performance, package ecosystem, metaprogramming capabilities, and community adoption.

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Advice on Common Lisp, Julia

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.

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Detailed Comparison

Common Lisp
Common Lisp
Julia
Julia

Lisp was originally created as a practical mathematical notation for computer programs, influenced by the notation of Alonzo Church's lambda calculus. It quickly became the favored programming language for artificial intelligence (AI) research. As one of the earliest programming languages, Lisp pioneered many ideas in computer science, including tree data structures, automatic storage management, dynamic typing, conditionals, higher-order functions, recursion, and the self-hosting compiler. [source: wikipedia]

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
-
GitHub Stars
47.9K
GitHub Forks
-
GitHub Forks
5.7K
Stacks
269
Stacks
666
Followers
255
Followers
677
Votes
145
Votes
171
Pros & Cons
Pros
  • 24
    Flexibility
  • 22
    High-performance
  • 17
    Comfortable: garbage collection, closures, macros, REPL
  • 13
    Stable
  • 12
    Lisp
Cons
  • 4
    Too many Parentheses
  • 3
    Standard did not evolve since 1994
  • 2
    No hygienic macros
  • 2
    Small library ecosystem
  • 1
    Ultra-conservative community
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
    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 Common Lisp, 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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