ramodels 32.3.4

Pydantic data models for OS2mo

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

• Poetry
• Pre-commit

Getting Started

1. Clone the repository: git clone [e-mail]: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