aind-metadata-extractor 0.3.1

Generated from aind-library-template

aind-metadata-extractor

Install

You should only install the dependencies for the specific extractor you plan to run. You can see the list of available extractors in the pyproject.toml file or in the folders in src/aind_metadata/extractor

During installation pass the extractor as an optional dependency:

pip install 'aind-metadata-extractor[<your-extractor>]'

Develop

Testing

When testing locally you only need to run your own tests (i.e. coverage run -m unittest discover -s tests/<new-extractor>). Do not modify the tests for other extractors in your PRs.

Before opening a PR, modify the file test_and_lint.yml and add a new test-group:

test-group: ['core', 'smartspim', 'mesoscope', 'utils', '<new-extractor>']

Then add the test-group settings below that:

    - test-group: '<new-extractor>'
    dependencies: '[dev,<new-extractor>]'
    test-path: 'tests/<new-extractor>'
    test-pattern: 'test_*.py'

When running on GitHub, all of the test groups will be run independently with their separate dependencies and then their coverage results are gathered together in a final step.

Run

Each extractor uses a JobSettings object to collect necessary information about data and metadata files to create an Extractor which is run by calling .extract(). For example, for smartspim:

from pathlib import Path

from aind_metadata_extractor.smartspim.job_settings import JobSettings
from aind_metadata_extractor.smartspim.extractor import SmartspimExtractor

DATA_DIR = Path("<path-to-your-data>)

job_settings=JobSettings(
    subject_id="786846",
    metadata_service_path="http://aind-metadata-service/slims/smartspim_imaging",
    input_source=DATA_DIR+"SmartSPIM_786846_2025-04-22_16-44-50",
    slims_datetime="2025-0422T18:30:08.915000Z"
)
extractor = SmartspimExtractor(job_settings=job_settings)
response = extractor.extract()