Skip to main content

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

Project details


Release history Release notifications | RSS feed

This version

3.3.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

ramodels-3.3.0.tar.gz (14.3 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

ramodels-3.3.0-py3-none-any.whl (29.6 kB view details)

Uploaded Python 3

File details

Details for the file ramodels-3.3.0.tar.gz.

File metadata

  • Download URL: ramodels-3.3.0.tar.gz
  • Upload date:
  • Size: 14.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.11 CPython/3.8.12 Linux/5.4.0-1053-gcp

File hashes

Hashes for ramodels-3.3.0.tar.gz
Algorithm Hash digest
SHA256 2289ffc1298be6494e3bd86cf311165047f4efdd52833a27f352f725680f0011
MD5 108e0b86da5a672fb787a1bb140fd199
BLAKE2b-256 2b58a41e972bf106216e61a99de76a880990a3590aab8069e67fc8a5db8da5f7

See more details on using hashes here.

File details

Details for the file ramodels-3.3.0-py3-none-any.whl.

File metadata

  • Download URL: ramodels-3.3.0-py3-none-any.whl
  • Upload date:
  • Size: 29.6 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.1.11 CPython/3.8.12 Linux/5.4.0-1053-gcp

File hashes

Hashes for ramodels-3.3.0-py3-none-any.whl
Algorithm Hash digest
SHA256 1934cb12d8fc57bed89e37f8327d77983bb333a0912e22554b97eb7f783ee94d
MD5 edbe4227b7d00acd574d230eaf3f395d
BLAKE2b-256 8ecb5e0c3dfea6e5003039d94cd7946ba92f7d455b5687ae0d332db1f930c63d

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page