In this post, I would like to share Julia Programming which is different in terms of interpreters used that been used in Python or Ruby. Some people will find that Julia Programming is a flexible dynamic language and a useful for any scientific and numerical computing.
When Julia Performance is running slow, the user can revise by went through the Performance Tips which can be found here. For new in Julia like me, I found out that Julia Features are multiple dispatches, achieved using type inference and good performance.
Some advantages that Julia Programming might have comparing to the programming:
- MIT Licensed
- Types of User-Defined can be considered as fast and compact as built-ins
- Vectorize code for performance will be not needed while devectorized code can be faster
- Lightweight “green” threading
- Julia can be considered as Powerful type system
- There have efficient support for the Unicode Usage and limited to UTF-8
Download and Installation of Julia Programming
For those are interested to use Julia Programming, you can install it via the website here
In my case, I will be using Github Source to download and install Julia Programming within my machine. The user who want to use Github Source, the URL link can be seen over here
The command that will be use for download Julia Programming from Github look like below:
sudo git clone https://github.com/JuliaLang/julia.git
It will take just a few minutes depending on the internet connection.
Once the downloading is complete, the user can dive into the folder to look what have been stored for Julia Programming.
The user should have notice that there are a lot of folder in Julia Folder.
Source: Julia Website