im-data-manager-metadata 1.0.1b1

A framework for Informatics Matters dataset metadata

A metadata framework package for the Data Tier Data Manager service. The im-data-manager-metadata package is a set of utilities employed by the Informatics Matters Data-Manager service as a metadata framework for molecular datasets.

Dependencies

• PyYAML>=5.3

Running the Unit Tests

>>> python -m venv ~/.venv/data-manager-metadata
>>> source ~/.venv/data-manager-metadata/bin/activate
>>> pip install --upgrade pip
>>> pip install -r package-requirements.txt
>>> python -m unittest test.test_metadata
>>> python -m unittest test.test_api

Running the Command Line Interface md-manage.py

The data manager metadata command line interface can be used by applications to add annotations to the Metadata by means of an annotations.json files that can be uploaded.

• help functions. Note that the annotation_type (lb, fd or se) is required.

>>> python md_manage.py -h
>>> python md_manage.py lb -h
>>> python md_manage.py fd -h
>>> python md_manage.py se -h

• Creates a label annotation in an annotations.json file placed in test/output. Note that the label is required. Running the command again will create a second annotation in the same file (i.e. a list of two).

>>> python md_manage.py lb test/output/results.sdf 'foo' -lv='bar'

• Creates a FieldsDescriptorAnnotation in an annotations.json file placed in test/output. If the annotations.json file exists it will add it to the list of annotations in the file.

>>> python md_manage.py fd test/output/results.sdf -fo='squonk2-job'
                        -fp='minimizedAffinity,number,Binding affinity
                        predicted by smina using the vinardo scoring function,true,true'
                        -fd='Run smina docking'

• Creates a service execution annotation in an annotations.json file placed in test/output.

>>> python md_manage.py se test/output/results.sdf -su=bob -sys='run-smina'
                       -sy='test/input/virtual-screening.yaml'
                       -sp param1=val1 param2=val2 -fo='squonk2-job'
                       -fp='minimizedAffinity,number,Binding affinity predicted,true,true'
                       -fd='Run smina docking'

Contributing

The project uses: -

• pre-commit to enforce linting of files prior to committing them to the upstream repository

• Commitizen to enforce a [Convention Commit] commit message format

• Black as a code formatter

You MUST comply with these choices in order to contribute to the project.

To get started review the pre-commit utility and the conventional commit style and then set-up your local clone by following the Installation and Quick Start sections: -

>>> pip install -r package-requirements.txt
>>> pre-commit install -t commit-msg -t pre-commit

Now the project’s rules will run on every commit, and you can check the current health of your clone with: -

>>> pre-commit run --all-files