Virtual Brain Lab Aquarium
Collection of Pydantic models describing data objects passed between Virtual Brain Lab projects.
Corresponding JSON schema and C# files are generated automatically and are
located in the models directory.
Usage
For C# structs or JSON schemas, copy or reference whatever models you need from
the models directory.
To use the Pydantic models directly in Python, install the package with
pip install vbl-aquarium
Then import the models with
from vbl_aquarium.models.module_name import ModelName
replacing .module_name and ModelName with the desired model.
Further Documentation
For more information regarding updating models and each model's specification, see the VBL Aquarium documentation.
Release files for vbl-aquarium 1.2.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| vbl_aquarium-1.2.0.tar.gz | 39.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| vbl_aquarium-1.2.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 52.2 kB
Release files / vbl_aquarium-1.2.0.tar.gz
| Download URL | vbl_aquarium-1.2.0.tar.gz |
|---|---|
| Size | 39.0 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
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|
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BLAKE2b-256 checksum How to use checksums |
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| Upload date | |
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Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
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Transparency logRelease files / vbl_aquarium-1.2.0-py3-none-any.whl
| Download URL | vbl_aquarium-1.2.0-py3-none-any.whl |
|---|---|
| Size | 13.2 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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|
|
BLAKE2b-256 checksum How to use checksums |
d92593cd095c41d9772553830d7912ecd284ca24a904612415f74922fe44e1e3
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Dec 23, 2025.
Transparency log
