Julia-Experiments

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

kathuman/Julia-Experiments

Julia-Experiments

Run Julia in Google Colab