These are files with which I experiemted using the Julia programming language, a powerful programming alternative to python.
Julia can be run in many ways:
- As a standalone application in the computer (terminal mode)
- Through a programming workbook environment like Jupyter Lab
- Through an online programming workbook environment like Google Colab
- Through an Intergrated programming environment like
As a result, Files created are in one of the following formats:
- .ipynb workbook for Jupyter Notebook, Jupyter Labs or Google Colab
- *.jl source file for julia terminal or IDE (Integrated Development Environment)
Run Julia in Google Colab
- create the following file, save it with the ipynb extension, and upload it into Google Colab.
{
"nbformat": 4,
"nbformat_minor": 0,
"metadata": {
"colab": {
"name": "Julia on Colab.ipynb",
"version": "0.3.2",
"provenance": []
},
"kernelspec": {
"name": "julia-1.2",
"display_name": "Julia 1.2"
},
"accelerator": "GPU"
},
"cells": [
{
"metadata": {
"id": "oMSuTc3pDlHv",
"colab_type": "code",
"colab": {}
},
"cell_type": "code",
"source": [
""
],
"execution_count": 0,
"outputs": []
}
]
}
- Insert the following code in the colab file you just created:
!curl -sSL "https://julialang-s3.julialang.org/bin/linux/x64/1.2/julia-1.2.0-linux-x86_64.tar.gz" -o julia.tar.gz
!tar -xzf julia.tar.gz -C /usr --strip-components 1
!rm -rf julia.tar.gz*
!julia -e 'using Pkg; pkg"add IJulia; precompile"'
!echo "DONE"
- You are basically done. Test this installation by running a simple code like:
function mandelbrot(a)
z = 0
for i=1:50
z = z^2 + a
end
return z
end
for y=1.0:-0.05:-1.0
for x=-2.0:0.0315:0.5
abs(mandelbrot(complex(x, y))) < 2 ? print("*") : print(" ")
end
println()
end