Skip to main content

Provide classes for DBnomics entities and a storage abstraction

Project description

DBnomics Data Model

In DBnomics, once data has been downloaded from providers, it is converted in a common format: the DBnomics data model.

This Python package provides:

  • model classes defining DBnomics entities (provider, dataset, series, etc.) with their business logic and validation rules
  • a data storage abstraction to load and save those entities
  • adapters implementing the data storage abstraction (e.g. dbnomics_data_model.storage.adapters.filesystem)

This package is used in particular by the convert script of fetchers in order to save data.

Documentation

Please read https://db.nomics.world/docs/data-model/

Validate data

To validate a directory containing data written by (or compatible with) the "filesystem" adapter:

dbnomics-validate-storage <storage_dir>

This script outputs the data validation errors it finds.

Run tests

To run unit tests:

pytest

Code quality:

flake8 .

See also: https://git.nomics.world/dbnomics-fetchers/documentation/wikis/code-style

Publish a new version

For package maintainers:

git tag x.y.z
git push
git push --tags

GitLab CI will publish the package to https://pypi-hypernode.com/project/dbnomics-data-model/ (see .gitlab-ci.yml).

Project details


Release history Release notifications | RSS feed

Download files

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

Source Distribution

dbnomics_data_model-0.13.33.tar.gz (48.7 kB view details)

Uploaded Source

Built Distribution

dbnomics_data_model-0.13.33-py3-none-any.whl (62.9 kB view details)

Uploaded Python 3

File details

Details for the file dbnomics_data_model-0.13.33.tar.gz.

File metadata

  • Download URL: dbnomics_data_model-0.13.33.tar.gz
  • Upload date:
  • Size: 48.7 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: poetry/1.2.2 CPython/3.10.11 Linux/5.10.0-14-amd64

File hashes

Hashes for dbnomics_data_model-0.13.33.tar.gz
Algorithm Hash digest
SHA256 8c48ea4620bf4f90e1c279c28586660be6e198901c10cd2832cc1d717cd9aeee
MD5 95b84bc27f1c0040bc80552c8068886e
BLAKE2b-256 00a8e38e726c94c8e4b243c164d2c32a479093ab19b79d3c51014f8e5c528d04

See more details on using hashes here.

File details

Details for the file dbnomics_data_model-0.13.33-py3-none-any.whl.

File metadata

File hashes

Hashes for dbnomics_data_model-0.13.33-py3-none-any.whl
Algorithm Hash digest
SHA256 3b229cf8c35f2aa550f3ba875e4075fab593827555cfabaa29bdb4b1a4bc8802
MD5 3fbb514d6423712e5b3f3e06f55b3e7c
BLAKE2b-256 622aa09e24594aaca3068508e6d9eb5b472fbb40d2d0c9659d3464e476fa0448

See more details on using hashes here.

Supported by

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