Skip to main content

Generated from aind-library-template

Project description

aind-data-schema-models

License Code Style semantic-release: angular Interrogate Coverage Python

Installation

aind-data-schema-models is a dependency of aind-data-schema. You should not need to install it directly.

Contributing

Install the dev dependencies:

pip install -e .[dev]

How to add a new model class

tl;dr

Add new classes to the _generators/models/*.csv files or create new files containing Enum-derived classes directly in the src folder.

Run ./run_all.sh in the top-level folder to rebuild models from their CSV files.

Details

The model class files, brain_atlas.py etc, are auto-generated. You should never need to modify the class files directly.

Instead, take a look at the jinja2 templates in the folder _generators/templates. The filename of the template is used to pull the corresponding .csv file and populate the data DataFrame. In the template you can pull data from the various columns and use them to populate each of the fields in your class.

To re-build all the models, run the run_all.sh bash script in the root folder, which loops through the template files and runs them through the generate_code function.

There are a few special cases, e.g. if data are missing in columns they will show up as float: nan. See the organizations.txt template for examples of how to handle this.

Documentation

Internal registries need to be enumerated in the aind-data-schema file src/aind_data_schema/utils/docs/registries_generator.py in the variable registries. This list controls what classes will have documentation automatically generated and cross-referenced correctly.

If you add a new external registry, you need to write the documentation manually in the aind-data-schema file docs/source/aind_data_schema_models/external.md.

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

aind_data_schema_models-5.4.3.tar.gz (341.2 kB view details)

Uploaded Source

Built Distribution

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

aind_data_schema_models-5.4.3-py3-none-any.whl (310.0 kB view details)

Uploaded Python 3

File details

Details for the file aind_data_schema_models-5.4.3.tar.gz.

File metadata

  • Download URL: aind_data_schema_models-5.4.3.tar.gz
  • Upload date:
  • Size: 341.2 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.12

File hashes

Hashes for aind_data_schema_models-5.4.3.tar.gz
Algorithm Hash digest
SHA256 242b8838e1efbbf60f924cc592eee25086c4611bed5d6bc59ef965a38ba03d10
MD5 90cd208f48c4d7c2dee45227577c710a
BLAKE2b-256 5d5d26fe475626566fb5795224f535a8edbf2f714dfd35ff6b0971496186cd26

See more details on using hashes here.

File details

Details for the file aind_data_schema_models-5.4.3-py3-none-any.whl.

File metadata

File hashes

Hashes for aind_data_schema_models-5.4.3-py3-none-any.whl
Algorithm Hash digest
SHA256 d38f39b3083ee9829938e73686eeccbcf7bd595a37a216a7c13ae729f546ba82
MD5 7c37f6e24b1988c15fc4fefda471291f
BLAKE2b-256 2014a733e1c0879c57cc02f22c12550bec483001feff75e98f1012ea82ba2e54

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