• Python 3.10+
• Pip ^21.x

The following directory structure should be considered:

.   # Current directory
├── conf  # project settings
├── docs  # useful docs
├── examples  # example scripts (includes simulation decoupled from DB + REST)
├── src  # project source code
├── .coveragerc  # code coverage configs
├── .flake8  # flake8 configs
├── .gitignore  # gitignore file
├── .gitlab-ci.yml  # gitlab-ci file
├── docker-compose.yml  # docker-compose file
├── Dockerfile  # project dockerfile
├── dotenv  # template for environment variables
├── pytest.ini  # pytest configs
├── README.md
├── requirements.txt  # project dependencies
├── run_menu.py  # interactive menu for running the market
├── tasks.py  # CLI interface for running the market

It is possible to execute the collaborative forecasting engine in standalone mode, without the need for a REST-API or database integration. For that, please check the examples directory, which includes a script for running the market pipeline in standalone mode.

Please check the explanation and tutorial available on the Examples README file.

NOTE: The commands below assume that you are running them from the root directory of the project (data-sharing-barter-incentives-forecast/)

The dotenv file provides a template for all the environment variables needed by this project. To configure the environment variables, copy the dotenv file to .env and fill in the values for each variable.

   $ cp dotenv .env

NOTE: In windows, just copy-paste the dotenv file and rename it to .env.

To launch the docker containers stack:

   $ docker compose build

NOTE: This will create the market image, which will be then executed later

If you prefer using your local python interpreter (instead of docker), you'll need to manually perform the installation steps. Also, only 'simulation' functionalities (i.e., without integration with the data market REST / DB) will be available.

1. Install poetry (if not already installed)

      $ pip install poetry   

2. Install the python dependencies

      $ poetry install
      $ poetry shell

3. Run the 'run_menu.py' script to open the interactive market menu

       $ poetry run python run_menu.py

NOTE: If you're already working in a virtual environment (e.g., conda or pyenv), you can skip the poetry shell command.

An interactive menu is available to preview and execute the multiple functionalities of this module.

NOTE 1: The following instructions assume that the data market database and REST API are already initialized (available in other projects).

NOTE 2: The commands below assume that you are running them from the root directory of the project (data-sharing-barter-incentives-forecast/)

   $ docker compose run --rm app python run_menu.py

    $ python run_menu.py

Alternatively, you can run the market pipeline directly, relying on the CLI interface. This is useful for running the market pipeline in a non-interactive way (e.g., in a production environment).

NOTE 1: The commands below assume that you are running them from the root directory of the project (data-sharing-barter-incentives-forecast/)

NOTE 2: The following instructions assume that the data market database and REST API are already initialized (available in other projects).

WARNING: The following command will run the market pipeline with the settings specified in the .env file.

   $ docker compose run --rm app python tasks.py open_session

   $ docker compose run --rm app python tasks.py approve_market_bids

   $ docker compose run --rm app python tasks.py run_session

    $ docker compose run --rm app python tasks.py validate_transfer_out

If you have any questions regarding this project, please contact the following people:

Developers (SW source code / methodology questions):

• José Andrade [email protected]
• André Garcia [email protected]
• Giovanni Buroni [email protected]
• Carla Gonçalves [email protected]

Contributors / Reviewers (methodology questions):

• Ricardo Bessa [email protected]