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Setup

Table of contents generated with markdown-toc

Tools to Install

All these steps install tools to your computer, you will use them for this project, but you will also use them for your futur data-science projects !

Python

python3 --version
Python 3.8.12

It should be 3.8.XX

If it's not follow these instructions:

Click to expand!
  1. Run the following commands as root or user with sudo access to update the packages list and install the prerequisites:
sudo apt update
sudo apt install software-properties-common
  1. Add the deadsnakes PPA to your system’s sources list:
sudo add-apt-repository ppa:deadsnakes/ppa

When prompted press Enter to continue:

Output
Press [ENTER] to continue or Ctrl-c to cancel adding it.
  1. Once the repository is enabled, install Python 3.8 with:
sudo apt install python3.8
  1. Verify that the installation was successful by typing:
python3.8 --version
Output
Python 3.8.X

pip

Install pip first

curl https://bootstrap.pypa.io/get-pip.py -o get-pip.py
python3.8 get-pip.py

If you want to learn more about pip, here is a great place: https://realpython.com/what-is-pip/

Miniconda

Use miniconda for your python environments (it's usually unnecessary to install full anaconda environment, miniconda should be enough). It makes it easier to install some dependencies, like cudatoolkit for GPU support. It also allows you to acccess your environments globally.

Example installation:

wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh

For more explanation on this tool you should read this page https://virtualenv.pypa.io/en/latest/

direnv

With direnv you will not have to think about your virtualenv anymore. It will also be easy to manage secrets as environment variables.

See this link: https://direnv.net/docs/installation.html

It should be something like curl -sfL https://direnv.net/install.sh | bash depending on your OS.

For more explanation on this tool you should read this page: https://direnv.net/.

AWS CLI

The AWS Command Line Interface will be necessary to push your data to the remote s3 storage.

Here are the steps you should follow for this: https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html

Initialize your repository

Now all these steps are specifics to this project, and this project only !

You should first git clone this project, and then cd to it's top directory for running all the following commands.

Create a conda environment

Create new conda environment:

conda create -n myenv python=3.8
conda activate myenv

Launch the script to initialize your project

If it's not with execute rights, you should add them

chmod +x .42AI/init.sh

Then you can run the script

.42AI/init.sh

Verify you can launch the project

with this command

python train.py logger=mlflow