/CS_422_p1

Primary LanguageJupyter Notebook

Time Series Forecasting and Benchmarks Repository

Revision History

Zane Globus-O'Harra - 2023-05-04 - Add brief overview, authors, technologies, requirements, installation instructions.

Zane Globus-O'Harra - 2023-05-05 - Add contact Zach W if installation or runtime problems occur. Minor layout update.

System Overview

The purpose of this application is to act as a central repository for time series (TS) data. Contributors will be able to upload their TS data along with a forecasting task for other users to complete.

Data scientists or machine learning engineers can download the TS training data sets and create some predicted data. The data scientists can upload their solution data and see how it compares to the TS test data sets that the contributor uploaded.

For in-depth documentation, see documentation/

Authors:

CS 422 at the University of Oregon

Team 1, "zeakz"

Technologies

  • Django: High-level Python web framework
  • SQLite Database: Built-in to Django
  • HTML, CSS, JavaScript: For webpage display and UI design

Requirements

  • Python 3
  • pip
  • virtualenv

Installation

We assume that the user is using a Linux-based system. For installation steps that might be different on other operating systems, links to additional instructions are provided.

  • Django 4.2
  • Pandas
  • Grapher
  • matplotlib

Install the requirements:

$ sudo apt install python3
$ python3 -m pip install --user --upgrade pip
$ python3 -m pip install --user virtualenv

Note: if you are using Windows, follow the instructions here to install Python and here to install pip.

Clone the repository:

$ git clone https://github.com/zfgo/CS_422_p1.git

Navigate to the folder where the project was cloned:

$ cd CS_422_p1

Set up and run the virtual environment:

$ python3 -m venv env 
$ source env/bin/activate
$ python3 -m pip install -r requirements.txt

Note: if you are using Windows, follow the instructions here for setting up a virtual environment.

Run the project:

$ python3 Django/mysite/zach_test/manage.py runserver

Navigate to the webpage, http://127.0.0.1:8000/home.

If any issues occur while installing or running the application, please contact Zachary Weisenbloom at zweisenb@uoregon.edu.

Frontend Only Webapp

To run the app with all current functionality, follow the above instructions. To see our intended design, with no backend functionality, navigate to this website.