streamsight 0.2.7

RecSys toolkit for evaluation in a fair manner.

Streamsight

The purpose of this Final Year Project is to design and implement a toolkit for evaluating Recommendation System (RecSys) which respects the temporal aspect during the data splitting process and incrementally release data as close to a live production setting as possible.

Package

Table Table of Contents

• Streamsight
  • Table Table of Contents
  • Installation with code base
    • Installation with poetry
    • Installation with pip
  • Installation from open source
  • Documentation

Installation with code base

The package can be installed quickly with python poetry or the traditional pip method. The recommended way of installation would be through poetry as it will help install the dependencies along with the package. We assume that the repository has already been cloned else you can run the following code on terminal before continuing.

git clone https://github.com/HiIAmTzeKean/Streamsight.git
cd Streamsight

Installation with poetry

The following code assumes that you do not have poetry installed yet. If you using MacOS, you might want to consider installing poetry with homebrew instead.

pip install poetry
# MacOS can consider using brew install poetry
poetry install

Installation with pip

The following code below assumes that you have pip installed and is in system PATH.

pip install -e .

Installation from open source

Alternatively streamsight is available on PyPi and can be installed through either of the commands below

# To install via pip
pip install streamsight

# To install with streamsight as a dependency
poetry add streamsight

Documentation

The documentation can be found here and repository on Github.