Greenferries

Overview

GreenFerries is a project aimed at improving the environmental impact transparency of passenger ships. It provides a public website, datasette for API and data exploration, and a Python library for fetching and processing raw data from THETIS and wikidata. The project also includes Jupyter Python notebooks for exploring the different datasets.

Features

• Public website: greenferries.org
• Datasette API & data explorer: data.greenferries.org
• Download SQLite files: files.greenferries.org
• Netlify status lint standard JS/www greenferries.org frontend website
• Python library: greenferries
• Jupyter Python notebooks
• Data platform: data.greenferries.org

Installation

To install the GreenFerries project, follow these steps:

1. Install Node.js by running make install-node.
2. Deploy the main monorepository master branch to Netlify to automatically build and deploy the 11ty website from the www subdirectory.
3. Install the greenferries Python library by running make install-python.
4. Register on wikidata and add your credentials to greenferries/.env.
5. Run the full_pipeline make command from the root of the repository to download, convert, and process all necessary files for the frontend website and the datasette platform.
6. Explore the different datasets using the Jupyter Python notebooks with the make notebooks-server command.
7. Access the data platform at data.greenferries.org to explore the processed data using the datasette and csvs-to-sqlite tools.
8. To run the datasette platform locally, use the make datasette-dev command from the repository root.

Summary

GreenFerries is a project focused on enhancing the transparency of passenger ships’ environmental impact. It offers various features, including a public website, datasette for API and data exploration, a Python library for data processing, and Jupyter Python notebooks for dataset exploration. The project also provides a data platform where users can access and explore the processed data. The installation process involves setting up the necessary dependencies and deploying the website and data platform.