wet-net 0.3.0

WetNet helps Aigües de Barcelona (Barcelona Water Company) predict anomalous water consumption, using machine learning.

WetNet

WetNet helps Aigües de Barcelona (Barcelona Water Company) predict anomalous water consumption, using machine learning.

Setup

1. Install uv

Our project uses uv to manage dependencies in a reproducible way. See Installing uv documentation for installation instructions.

[!TIP] You can skip the rest of the setup if you just want to run the scripts and see the project in action! Run uvx https://github.com/ZachParent/wet-net.git --help to see the available commands in the CLI.

2. Clone the repository

git clone https://github.com/ZachParent/wet-net.git
cd wet-net

3. Install the project dependencies

uv sync --locked

Usage

Run the scripts

The easiest way to verify that the project is working is to run the scripts. These command line interfaces include help documentation.

uv run wet-net pre-process --help
uv run wet-net train --help
uv run wet-net evaluate --help

The code for the scripts can be found in the src/wet_net/scripts directory.

Notebooks

We use Jupyter notebooks to show the process of preparing the data, training the model, and evaluating the model, with descriptions and code. You can run the notebooks by opening them up in your favorite IDE. Be sure to choose the .venv kernel which is created and managed by uv. The notebooks can be found in the notebooks directory.

01_pre_process.ipynb

The 01_pre_process.ipynb notebook shows the process of preparing the data. It includes:

• Loading the data
• Pre-processing the data
• Saving the pre-processed data

02_train.ipynb

The 02_train.ipynb notebook shows the process of training the model. It includes:

• Loading the pre-processed data
• Training the model
• Saving the trained model

03_evaluate.ipynb

The 03_evaluate.ipynb notebook shows the process of evaluating the model. It includes:

• Loading the trained model
• Evaluating the model
• Saving the evaluation results

Contributing

We welcome contributions to the project. Please feel free to submit an issue or pull request.

For more information on contributing, including how to set up pre-commit hooks and how to cut a new release, see CONTRIBUTING.md.