Skip to content

Latest commit

 

History

History
106 lines (64 loc) · 3.65 KB

installation_steps.md

File metadata and controls

106 lines (64 loc) · 3.65 KB
Raw

Installation instructions for Python calling Julia to solve optimization problem in JuMP

Step 1: Anaconda Installation

  • Download the Python (64-bit(x86)) installer from

    https://www.anaconda.com/download/#linux

  • In bash terminal, type the command:

    bash Anaconda-latest-Linux-x86_64.sh

  • Follow the prompts on the installer screens

  • To make the changes take effect, close and then re-open your Terminal window.

Step 2: Download and install Julia

  • Download the Julia version 1.0.3 (64-bit Generic Linux Binaries for x86) installer from

    https://julialang.org/downloads/

  • Then, extract the .tar.gz file downloaded in the previous step to a folder on your computer

  • Next step is to add Julia's bin folder to your system PATH environment variable , go to your home directory and open .bashrc file.

  • Add the following line to the .bashrc file:

    export PATH="$PATH:/path/to/julia/folder/julia-1.0.3/bin"

  • Open a new terminal window and install Julia using:

    `sudo apt install julia`

Step 3: IJulia and JuMP Installation

  • Open a terminal and launch julia with the command: julia

  • Install IJulia with the following commands

    using Pkg Pkg.add("IJulia")

  • Further help on IJulia notebook: here

  • Install JuMP with the following commands (in the terminal where julia was launched):

    Pkg.add("JuMP")

  • Install PyCall Pkg.add("PyCall")

Step 4: Installing Solvers

  • Execute the following set of commands:

    Pkg.add("Cbc") Pkg.add("GLPK") Pkg.add("MathOptInterface") Pkg.add("Interface")`

    Step 4.1 If you do not have svn already installed on your machine then execute the following commands:

    sudo apt-get update

    sudo apt-get install subversion

    Step 4.2 If you do not have fortran compiler already installed on your machine then execute the following command:

    sudo apt-get install gfortran

Step 5: Creating virtual environment for Julia in Python

  • In a new bash terminal, run the following command to create a new virtual environment named ju_py conda create --name ju_py

  • Activate the newly created python virtual environment using the command: source activate ju_py

  • Install python's julia package for calling julia functions in python conda install -c conda-forge julia python2 -m pip install julia

  • Adding the python virtualenv (ju_py) to the ipython notebook, run the following set of commands: pip install ipykernel ipython kernel install --user --name=ju_py

  • In Julia >= 0.7, above two paths to libpython have to match exactly in order for PyJulia to work. To configure PyCall.jl to use Python interpreter "/path/to/anaconda3/envs/ju_py/bin/python", run the following commands in the Julia interpreter (to get to Julia interpreter, open a new terminal and type julia) and then type the following commands:

    ENV["PYTHON"] = "/path/to/anaconda3/envs/ju_py/bin/python" using Pkg Pkg.build("PyCall")

Step 6: Installing Julia Plugin for PyCharm

  • If you are using PyCharm IDE for running your python code, then install the Julia plugin

  • go to File $$\to$$ Settings $$\to$$ Plugins $$\to$$ towards the end $$\to$$ Browse Repositories... $$\to$$ search "Julia"

  • install the Julia plugin and restart Pycharm

    Step 6.1: Setting up project interpreter for running Julia file inside PyCharm

  • go to File $$\to$$ Settings $$\to$$ Languages & Frameworks $$\to$$ Julia

  • In Julia executable field, enter the path to the julia executable:

    /path/to/your/downloaded/julia/folder/julia-1.0.3/bin/julia