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energy-data-centre-visualisation

Back-end Application

https://github.com/jack-richards/energy-data-visualisation-api

Front-end Application

https://github.com/jack-richards/energy-data-visualisation-ui

Getting started

Prerequisites

Clone the repositories

git clone https://github.com/jack-richards/energy-data-visualisation-api.git
git clone https://github.com/jack-richards/energy-data-visualisation-ui.git

Download the dataset

You have to download and unzip the dataset files provided as part of the paper:

Canet, A., Qadrdan, M., Jenkins, N. et al. Spatial and temporal data to study residential heat decarbonisation pathways in England and Wales. Sci Data 9, 246 (2022). https://doi.org/10.1038/s41597-022-01356-9

It has a section on the data/files (which this project requires) and where to download them.

Once acquired, you must unzip and place the files into the /data directory. After, set the DATA_DIR environment variable to equal /data.

You may prefer setting it up on the environment variable your IDE, or you can do it on the command line:

On Linux/MacOS:

export DATA_DIR=/data

On Windows:

$env:DATA_DIR = "/data"

Install dependencies for the frontend

cd into the frontend directory, then run:

pnpm install

Set environment variables for the frontend

For the contact form to work you will need to set the following .env variables with valid values:

NUXT_MAILHOST=?
NUXT_MAILPORT=587
NUXT_MAILUSER=?
NUXT_MAILPASSWORD=?
NUXT_CONTACTMAIL=?

Run the frontend

cd into the frontend directory, then run:

pnpm dev

You can then access the frontend at http://localhost:3000.

Run the frontend in production mode

cd into the frontend directory, then run:

pnpm build
node .output/server/index.mjs

You can then access the frontend at http://localhost:3000.

Install dependencies for the backend

cd into the backend directory, then run:

pip install -r requirements.txt

Set environment variables for the backend

Assuming you have already set the DATA_DIR environment variable, you must also set the following environment variables:

  • REDIS_URI - The URI of the Redis server, for example, redis://localhost:6379.

Initialise the database

Assuming you have already set the DATA_DIR and REDIS_URI environment variables set,

cd into the backend directory, then run:

python initialise_csv.py

Run the backend

Assuming you have already set the DATA_DIR and REDIS_URI environment variables set,

cd into the backend directory, then run:

uvicorn main:app --reload

This will start the backend server on port 8000 while binding to localhost.