This demonstrator is available here.

This project uses poetry. It's a modern dependency management tool.

To run the project use this set of commands:

poetry install
poetry run python -m power_systems_data_api_demonstrator

This will start the server on the configured host.

You can find swagger documentation at /api/docs.

You can read more about poetry here: https://python-poetry.org/

You can start the project with docker using this command:

docker-compose  up --build

This command exposes the web application on port 8000, mounts current directory and enables autoreload.

But you have to rebuild image every time you modify poetry.lock or pyproject.toml.

$ tree "power_systems_data_api_demonstrator"
power_systems_data_api_demonstrator
├── __main__.py
├── settings.py
├── src
│   ├── api
│   │   ├── docs
│   │   ├── grid_node
│   │   └── router.py
│   ├── application.py
│   ├── lib
│   │   ├── db
│   └── lifetime.py
└── tests
    ├── conftest.py
    └── test_****.py

This application can be configured with environment variables.

You can create .env file in the root directory and place all environment variables here.

All environment variables should start with "POWERSYSTEMS_DATA_API_DEMONSTRATOR" prefix.

For example if you see in your "power_systems_data_api_demonstrator/settings.py" a variable named like random_parameter, you should provide the "POWER_SYSTEMS_DATA_API_DEMONSTRATOR_RANDOM_PARAMETER" variable to configure the value. This behaviour can be changed by overriding env_prefix property in power_systems_data_api_demonstrator.settings.Settings.Config.

You can read more about BaseSettings class here: https://pydantic-docs.helpmanual.io/usage/settings/

An example of .env file:

POWER_SYSTEMS_DATA_API_DEMONSTRATOR_PORT="8000"

If you want to use this env file, you will need to run docker in the following way:

docker-compose --env-file .env up

To install pre-commit simply run inside the shell:

pre-commit install

pre-commit is very useful to check your code before publishing it. It's configured using .pre-commit-config.yaml file.

By default it runs:

• black (formats your code);
• mypy (validates types);
• isort (sorts imports in all files);
• flake8 (spots possibe bugs);

You can read more about pre-commit here: https://pre-commit.com/

If you want to run it in docker, simply run:

docker-compose -f docker-compose.yml --project-directory . run --rm api pytest -vv .
docker-compose -f docker-compose.yml --project-directory . down

For running tests on your local machine.

2. Run the pytest.

pytest -vv .

The data has been seeded by pulling from a variety of public sources. The data was extracted using python in notebooks that can be accessed using the following command. :

poetry run jupyter notebook data/

However these scripts require API keys so you will need to set the following variables:

# for ELEXON
export BMRS_API_KEY=ABC

# for EIA
export EIA_API_KEY=DEF

To seed this data you need to run the following command:

docker-compose run --rm api python power_systems_data_api_demonstrator/seed/seed.py