Julia vs Objective-C

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Julia

621
666
+ 1
166
Objective-C

12.4K
6.4K
+ 1
490
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Julia vs Objective-C: What are the differences?

Julia: A high-level, high-performance dynamic programming language for technical computing. 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; Objective-C: The primary programming language you use when writing software for OS X and iOS. Objective-C is a superset of the C programming language and provides object-oriented capabilities and a dynamic runtime. Objective-C inherits the syntax, primitive types, and flow control statements of C and adds syntax for defining classes and methods. It also adds language-level support for object graph management and object literals while providing dynamic typing and binding, deferring many responsibilities until runtime.

Julia and Objective-C can be categorized as "Languages" tools.

"Lisp-like Macros" is the top reason why over 7 developers like Julia, while over 211 developers mention "Ios" as the leading cause for choosing Objective-C.

Julia is an open source tool with 22.7K GitHub stars and 3.43K GitHub forks. Here's a link to Julia's open source repository on GitHub.

Uber Technologies, Instagram, and Pinterest are some of the popular companies that use Objective-C, whereas Julia is used by inFeedo, Platform Project, and N26. Objective-C has a broader approval, being mentioned in 851 company stacks & 363 developers stacks; compared to Julia, which is listed in 5 company stacks and 5 developer stacks.

Decisions about Julia and Objective-C
Alexander Nozik
Senior researcher at MIPT · | 3 upvotes · 171.1K views
Migrated
from
JuliaJulia
to
KotlinKotlin

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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Noel Broda
Founder, CEO, CTO at NoFilter · | 5 upvotes · 232.4K views

1 code deploys for both: Android and iOS. There is a huge community behind React Native. And one of the best things is Expo. Expo uses React Native to make everything even more and more simple. Awesome technologies. Some other important thing is that while using React Native, you are reusing all JavaScript knowledge you have in your team. You can move easily a frontend dev to develop mobile applications.

A huge PRO of Expo, is that it includes a full building process. You run 1 line in the terminal, and 10 minutes after you have 2 builds done. Double check EAS Expo.

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Pros of Julia
Pros of Objective-C
  • 24
    Fast Performance and Easy Experimentation
  • 21
    Designed for parallelism and distributed computation
  • 18
    Free and Open Source
  • 17
    Dynamic Type System
  • 16
    Multiple Dispatch
  • 16
    Calling C functions directly
  • 16
    Lisp-like Macros
  • 10
    Powerful Shell-like Capabilities
  • 9
    Jupyter notebook integration
  • 8
    REPL
  • 4
    String handling
  • 4
    Emojis as variable names
  • 3
    Interoperability
  • 212
    Ios
  • 115
    Xcode
  • 62
    Backed by apple
  • 47
    Osx
  • 40
    Interface builder
  • 10
    Good old fashioned ooe with a modern twist
  • 2
    Goober, please
  • 1
    Object-oriented
  • 1
    Handles well null values (no NullPointerExceptions)

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Cons of Julia
Cons of Objective-C
  • 5
    Immature library management system
  • 4
    Slow program start
  • 3
    JIT compiler is very slow
  • 3
    Poor backwards compatibility
  • 2
    Bad tooling
  • 2
    No static compilation
  • 1
    UNREADABLE

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- No public GitHub repository available -

What is Julia?

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.

What is Objective-C?

Objective-C is a superset of the C programming language and provides object-oriented capabilities and a dynamic runtime. Objective-C inherits the syntax, primitive types, and flow control statements of C and adds syntax for defining classes and methods. It also adds language-level support for object graph management and object literals while providing dynamic typing and binding, deferring many responsibilities until runtime.

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What companies use Julia?
What companies use Objective-C?
See which teams inside your own company are using Julia or Objective-C.
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What tools integrate with Julia?
What tools integrate with Objective-C?

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What are some alternatives to Julia and Objective-C?
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.
R Language
R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, ...) and graphical techniques, and is highly extensible.
MATLAB
Using MATLAB, you can analyze data, develop algorithms, and create models and applications. The language, tools, and built-in math functions enable you to explore multiple approaches and reach a solution faster than with spreadsheets or traditional programming languages, such as C/C++ or Java.
Rust
Rust is a systems programming language that combines strong compile-time correctness guarantees with fast performance. It improves upon the ideas of other systems languages like C++ by providing guaranteed memory safety (no crashes, no data races) and complete control over the lifecycle of memory.
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.
See all alternatives