A Hitchhiker's Guide to Installing candis on Linux OS - HelikarLab/candis GitHub Wiki

From Zero to Hero - Achilles Rasquinha

To the best of my knowledge, this will be the only page you'd ever require to install candis right from scratch. This script also believes to be a foolproof setup to have candis onto your system. In case if you run into some problems, feel free to raise an issue here.

NOTE: To see if your Linux OS has been tested for the following script, check here. You're free to revise this page in order to add your Mac OS X version if you're successful with this script too (psst, helps others).

First, open your Terminal (Ctrl + Alt + T)

• Keep your OS, up-to date

$ # Update, Upgrade, Distribution Upgrade
$ sudo apt-get update && sudo apt-get upgrade && sudo apt-get dist-upgrade

• Install git

$ sudo apt-get install git

• ...and check if git has been correctly installed.

$ git --version

You should then see the version information only.

• Clone candis (Optional - Add the --recursive flag to clone candis-res, a repository with sample genomic data) using git.

$ git clone --recursive https://github.com/HelikarLab/candis.git

This just goes ahead and pulls the source files from the remote git repository.

• Ensure you're pointing to candis's root directory

$ cd candis

Add candis to your $PYTHONPATH Environment Variable as follows:

$ # Add Environment Variable to ~/.bashrc
$ echo "export PYTHONPATH=path/to/candis/candis:$PYTHONPATH" >> ~/.bashrc
$ # Refresh ~/.bashrc
$ source ~/.bashrc                                                 

where path/to/candis is the absolute path to your candis source directory. Note that $PYTHONPATH points to candis's Python source directory (path/to/candis/candis) and not its root source directory (path/to/candis).

candis's API (CLI as well as the RIA server) is built using Python (3.6+); while from Data Manipulation to Model Deployment uses Python wrappers for R and WEKA (which requires Java). In addition, candis requires graphviz installed (to generate Graph Visualisations for models like Decision Trees, etc.).

Run candis as a module

(venv) $ python -m candis

Open your favourite browser, type localhost:5000 on the address bar and press Enter (Return). You should then see something like this.

NOTE: If you're attempting to revise this page after successfully installing and running candis, kindly add the required details in the following format only.