Julia Programming Language - Introduction

Installing Julia Programming Language

You can follow the steps to install Julia Programming Language in your system.

1. Go to julialang.org/downloads. Select the version you want to download according to your operating system.

1. For windows, select the “.exe” file.
2. For mac, select the “.dmg” file.
3. For Ubuntu/ Linux, select the “.tar.g.z” file.

2. Download the installer and start installing according to your operating system.

3. Let me guide you through the mac installer.

4. As soon as the installer is downloaded, double-click on the installer.

5. Drag the Julia icon to your applications

6. Now Open Julia's Application. It will open in the terminal as follows:

7. Congratulations! Julia is successfully installed in your system.

8. Now you can run any Julia program in the shell.

julia> a=5
5

julia> b=6
6

julia> a+b
11

julia> println("helloworld")
helloworld

Basics of Julia Programming Language

Now that you have successfully installed Julia programming language in your system let's learn some basics of Julia Programming Language.

The most basic program for any programming language is the “Hello World” Program.

Hello World Program in Julia Programming Language

julia> println("Hello World")
Hello World

Variable and Types in Julia Programming Language

Variables in Julia are dynamically typed. Thus you can declare the type when you create it. 

Now let's create a variable and assign an integer to it.

julia> a=5 # Creating a variable and assigning it a number
5

julia> a+7 # Basic math operation
12

Similarly, we can create string and float variables.

julia> name="Coding Ninjas" # String Variable
"Coding Ninjas"

julia> num= 234.56 # Float Variable
234.56

We can use the type of() function to know the data types of a variable.

julia> println(typeof(a))
Int64
 
julia> println(typeof(name))
String

julia> println(typeof(num))
Float64

Some special symbols called Unicode Characters in Julia are also very useful in mathematical equations. We can access these Unicode variables by doing a backslash “ \ ” and then typing the name, followed by pressing the tab button.

julia> π = 3.1415
3.1415

julia> σ=43
43

Here we inserted Pi and Sigma.

The following data types are supported in Julia: 

• Int64
• Float64
• Char
• String
• Bool

Comments in Julia Programming Language

Like Python, Julia Programming Language supports single-line comments using the # symbol. Multi-line comments are supported using the #= …  =# syntax.

1. Single Line Comments

julia> # Hello Everyone, This is a Single Line Comment.

2. Multi-Line Comments

julia> #=
      Hello Everyone, This is a multiline comment.
      We can use multiple comments this way.
      Hope you find this helpful.
      =#

Data Structures in Julia Programming Language

Julia Programming Language supports Array, Tuples, and Dictionaries. Functionally they are similar to python but with different syntax.

Array

Arrays in Julia are ordered collections that can store mixed types of data. It is mutable, and it can be indexed and sliced. Elements can be added and removed using the pop! ( ) and push! ( ) operations.

julia> fruits=["Apple", "Orange", "Banana", "Grapes"]
4-element Vector{String}:
"Apple"
"Orange"
"Banana"
"Grapes"

julia> fruits[1]
"Apple"

julia> fruits[2]
"Orange"

julia> push!(fruits,"Papaya")
5-element Vector{String}:
"Apple"
"Orange"
"Banana"
"Grapes"
"Papaya"

Tuple

Tuples in Julia are just like python. They are immutable ordered collections of elements.

julia> cars=("BMW", "Audi", "Mercedes")
("BMW", "Audi", "Mercedes")

julia> cars[1]
"BMW"

julia> push!(cars,"Lamborghini")
ERROR: MethodError: no method matching push!(::Tuple{String, String, String}, ::String)
Closest candidates are:
 push!(::Any, ::Any, ::Any) at abstractarray.jl:3059
 push!(::Any, ::Any, ::Any, ::Any...) at abstractarray.jl:3060
 push!(::Base.InvasiveLinkedListSynchronized{T}, ::T) where T at task.jl:660
 ...
Stacktrace:
[1] top-level scope
  @ REPL[31]:1

Dictionary

Dictionary in Julia Programming Language is a set of related data stored as a Key and Value pair. Dictionary in Julia Programming Language is created using the dict() keyword.

julia> data=Dict("suraj"=> 86, "Deepak" => 98, "Rhythm"=> 82)
Dict{String, Int64} with 3 entries:
 "Deepak" => 98
 "suraj"  => 86
 "Rhythm" => 82
 
julia> pop!(data, "suraj")
86

julia> data
Dict{String, Int64} with 2 entries:
 "Deepak" => 98
 "Rhythm" => 82

Features of Julia Programming Language

Following are the features of the Julia Programming language.

Speed

It is the fastest language for interactive computing out there. Julia became the fourth language to achieve petaflops performances after C, C++, and Fortran. 

Syntax

Python and R are the most popular dynamically typed languages for scientific computing. Since the calculations were being performed by scientists who lacked development experiences, such as physicists, biologists, and financial experts, they chose simpler syntax, even if it meant slower computation speeds. Despite being compiled and dynamically typed, Julia is as quick as statically typed languages like C or Fortran. Julia is straightforwardly to learn and create.

Multiple Dispatch

Multiple dispatches describe the function's capacity to respond differently depending on the kinds of arguments it receives. Each function is capable of having several iterations that are optimized for various parameter types. Many implementations of the function would be dispatched, and the most appropriate would be chosen during runtime.

Dynamic typing

Julia allows for dynamic programming and typing system. Unlike C or C++, variables don’t have any data types. Values have data types. These types are determined at runtime rather than compile time. It allows for multiple dispatches.

Interactive Shell

It has a powerful and interactive shell that allows Julia to manage other processes easily.

Communication

Python, R, and Java are just a few programming languages with which it can effectively interface. It can communicate with Python using PyCall, R using RCall, and Java using JavaCall, for instance. We can directly call a C function without using API or wrappers.

Pros and Cons of Julia Programming Language

Let us look at the pros and cons of Julia.

Pros

High performance

Julia is a high-performance language that was designed with the goal of being as fast as C, while also being easy to use and read. This makes it ideal for tasks that require intensive numerical computations.

Ease of use

Julia has a clean syntax that is easy to learn and understand. Its high-level abstractions make it possible to write code that is both concise and expressive, allowing you to focus on the problem you are trying to solve.

Multiple dispatch

Julia's multiple dispatch system is one of its most unique features. It allows functions to be overloaded based on the types of their arguments, which can lead to more efficient and readable code.

Dynamic typing 

Julia is dynamically typed, meaning that you don't have to declare the type of a variable before you use it. This makes it easier to write and modify code, as you don't have to worry about type-related errors.

Interoperability

Julia can easily interface with other languages like Python, C, and R. This means that you can use your favorite libraries and tools from these languages within your Julia code.

Cons

Less widespread adoption 

Julia is a relatively new language, and as a result, it is less widely adopted than more established languages like Python and R. This means that finding resources and support for Julia may be more difficult.

Limited library support

While Julia has a growing ecosystem, its library support is still more limited than some other languages. This can make it more difficult to find and use specialized tools and libraries for specific tasks.

Immature tooling

Julia's tooling is still relatively immature compared to other languages, which can make it more difficult to set up and work with. However, this is improving rapidly as the language gains popularity.

Less established community

Julia's community is still smaller and less established than other programming communities, which can make it more difficult to find help and support.

Steep learning curve for advanced features 

While Julia is easy to learn for basic programming tasks, its more advanced features, like multiple dispatch, can have a steep learning curve.

Less stable API

As Julia is still evolving, its API is less stable than more established languages. This can make it more difficult to maintain and update code over time.

Less mature ecosystem for machine learning 

While Julia has some great packages for machine learning, its ecosystem is still less mature than more established languages like Python and R. This can make it more difficult to find and use specialized machine learning tools.

Frequently Asked Questions

Why is Julia Programming Language so Popular?

Julia excels at elements of programming that no other language can. Python, for example, sacrifices speed for flexibility and dynamic typing, whereas languages like C, C++, and Java are static and inflexible to be quick at runtime.

What is special about Julia?

Julia is a high-performance programming language designed for numerical and scientific computing that combines the ease of use of high-level programming languages with the speed of low-level languages while also featuring unique features such as multiple dispatch and built-in parallelism.

Is Julia better than Python?

Julia and Python each have their strengths. Julia excels in numerical and scientific computing due to its speed, while Python offers a wider range of libraries and applications.

Can Julia be learned by non programmer?

Julia can be learned by non-programmers, but prior experience with programming concepts can make the learning process easier. There are many resources available, including online courses and tutorials, that can help beginners learn the language.

What is Julia programming language used for?

Julia is a high-level programming language used for numerical and scientific computing. It is commonly used for data analysis, machine learning, simulations, and mathematical modeling.

Conclusion

In this article, we discussed Julia Programming Language in detail. We discussed the history of the Julia Programming Language, how to install Julia Programming Language, the benefits of Julia Programming language, and the Basics of data types, variables, syntax, etc., in Julia Programming Language.

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