Smarter Mobility Data Challenge

This repository contains the code for forecasting occupation of charging stations in Paris, in order for utilities to optimize their production units in accordance with charging needs.

Installation

To install the necessary dependencies, create a virtual environment and activate it:

pip install virtualenv

Create a new virtual environment by running the following command:

virtualenv codalab_env

This will create a new virtual environment named myenv in the current directory. You can specify a different name if you want.

Activate the virtual environment by running the following command:

source codalab_env/bin/activate

Once the virtual environment is activated, you should see the name of the environment in parentheses at the beginning of the command prompt, like this:

(codalab_env) $

You can now install the necessary packages and run the code in the virtual environment. Then, run the following command:

pip install -r requirements.txt

This will install all the required packages listed in the requirements.txt file.

Code style

Usage

To run the charging status forecast task, use the following command:

python src/main.py

This will execute the code in the src/main.py file and generate the charging status forecast.

Notes

You may need to modify the src/main.py file to specify the input data and parameters for the task. The charging status forecast results will be saved in the output directory.