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Pydantic data models for OS2mo

Project description

MoLoRa Data Models

RAModels - MoLoRa data validation models powered by pydantic.

Versioning

This project uses Semantic Versioning with the following strategy:

  • MAJOR: Incompatible changes to existing data models
  • MINOR: Backwards compatible updates to existing data models OR new models added
  • PATCH: Backwards compatible bug fixes

Authors

Magenta ApS https://magenta.dk

License

  • This project: MPL-2.0
  • Dependencies:
    • pydantic: MIT

This project uses REUSE for licensing. All licenses can be found in the LICENSES folder of the project.

Development

Prerequisites

Getting Started

  1. Clone the repository: git clone git@git.magenta.dk:rammearkitektur/ra-data-models.git

  2. Install all dependencies: poetry install

  3. Set up pre-commit: pre-commit install

Running the tests

You use poetry and pytest to run the tests:

poetry run pytest

You can also run specific files

poetry run pytest tests/<test_folder>/<test_file.py>

and even use filtering with -k

poetry run pytest -k "Manager"

You can use the flags -vx where v prints the test & x makes the test stop if any tests fails (Verbose, X-fail)

Pre-commit usage

Pre-commit must either be used via your virtual environment or globally. If you want to pre-commit globally, the following extra dependencies are needed: pip install mypy pydantic

Models

LoRa

LoRa implements the OIO standard version 1.1. The standard with specification

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