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Note that you want to install miniconda in a network lab directory as it will quickly fill up your home directory!

Step-by-step guide

  1. Connect to head.arcc.albany.edu via SSH (see: How-to: Connect via SSH (PuTTY, macOS terminal, X2Go)
  2. Run the following commands, line by line. Make sure you change [lab_directory] to be your lab directory name. 


    Code Block
    languagebash
    titleInstalling miniconda
    cat ~/.bashrc >> ~/.bash_profile
    wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda.sh
    bash ~/miniconda.sh -b -p /network/rit/lab/[lab_directory]/miniconda
    /network/rit/lab/[lab_directory]/miniconda/bin/conda init
    cat ~/.bashrc >> ~/.bash_profile
    source ~/.bash_profile
  3. Some helpful hints
    1. Do not install packages in your (base) environment (e.g. conda activate base). It is best to create separate environments for different packages, or conda is at a risk of breaking (e.g.
      conda create -n tensorflow python=3)
    2. Sharing conda across lab group members is possible, make sure the folder is g+rwx (chmod -R g+rwx /network/rit/lab/[lab_directory]/miniconda)
    3. Always check if conda has a software package available. There are many different channels, but researchers and software developers commonly publish to conda-forge (e.g. 
      conda install -c conda-forge ffmpeg)
    4. Read the docs: https://conda.io/projects/conda/en/latest/user-guide/index.html

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