openMINDS Python library
openMINDS Python is a small library to support the creation and use of openMINDS metadata models and schemas in your Python application, with import and export in JSON-LD format.
Installation
pip install openMINDS
Usage
from datetime import date
from openminds import Collection, IRI
import openminds.latest.core as omcore
# Create an empty metadata collection
collection = Collection()
# Create some metadata
mgm = omcore.Organization(
full_name="Metro-Goldwyn-Mayer Studios, Inc.", short_name="MGM", homepage=IRI("https://www.mgm.com")
)
stan = omcore.Person(
given_name="Stan",
family_name="Laurel",
affiliations=omcore.Affiliation(member_of=mgm, start_date=date(1942, 1, 1)),
)
ollie = omcore.Person(
given_name="Oliver",
family_name="Hardy",
affiliations=omcore.Affiliation(member_of=mgm, start_date=date(1942, 1, 1)),
)
# Add the metadata to the collection
collection.add(stan, ollie, mgm)
# Check the metadata are valid
failures = collection.validate()
# Save the collection in a single JSON-LD file
collection.save("my_collection.jsonld")
# Save each node in the collection to a separate file
collection.save("my_collection", individual_files=True) # creates files within the 'my_collection' directory
# Load a collection from file
new_collection = Collection()
new_collection.load("my_collection.jsonld")
License
This work is licensed under the MIT License.
Getting help
In case of questions about openMINDS, please contact us at support@openmetadatainitiative.org. If you find a bug in the Python library or would like to suggest an enhancement or new feature, please open a ticket in the openMINDS Python library issue tracker.
If you identify a problem or would like to suggest changes to the openMINDS specification itself, please open a ticket in the openMINDS issue tracker.
Development
Contributions are welcome, please see our contribution guidelines.
This repository has two main branches: pipeline and main.
The pipeline contains the code for building the Python package from the openMINDS schemas.
The build process is triggered by changes to the schemas, and runs as a GitHub action.
The resultant package is copied to the main branch, and at intervals is published on PyPI.
Acknowledgements
This open source software code was developed in part or in whole in the Human Brain Project, funded from the European Union's Horizon 2020 Framework Programme for Research and Innovation under Specific Grant Agreements No. 720270, No. 785907 and No. 945539 (Human Brain Project SGA1, SGA2 and SGA3), and in the EBRAINS-2.0 project, funded from the European Union's Horizon Europe programme under grant agreement 101147319.
Release files for openMINDS 0.6.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| openminds-0.6.1.tar.gz | 4.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| openminds-0.6.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 11.8 MB
Release files / openminds-0.6.1.tar.gz
| Download URL | openminds-0.6.1.tar.gz |
|---|---|
| Size | 4.9 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.6
|
Release files / openminds-0.6.1-py3-none-any.whl
| Download URL | openminds-0.6.1-py3-none-any.whl |
|---|---|
| Size | 6.8 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
twine/7.0.0 CPython/3.14.6
|