"MCL Sickbay" is the data model and object-relational mapping for the clinical data application of the Consortium for Molecular and Cellular Characterization of Screen-Detected Lesions.
The "Sickbay" software provides a Python based API into a data model (a series of related classes) and takes advantage of SQLAlchemy as the object-relational mapper. This section will help you get started.
For this project, we're using PostgreSQL. You can create a PostgreSQL database to use with this software as follows:
dropdb --if-exists clinical_data
dropuser --if-exists mcl
createuser \
--createdb \
--inherit \
--login \
--no-createrole \
--no-superuser \
mcl
createdb --encoding=UTF8 --owner=mcl clinical_data
To use this software, simply add mcl.sickbay
as a dependency to your project or install it into your Python virtual environment.
You can develop, build, and test the package locally as follows:
python3 -m venv venv
venv/bin/pip install --quiet --upgrade setuptools pip wheel build
venv/bin/pip install --editable .
You can run venv/bin/create-clinical-db
to populate a PostgreSQL database with the schema of the Sickbay data model. Add --add-test-data
to include some test data or --add-sample-data
to add some sample data (or use both!).
To build and publish this software, try build and Twine.
We use the SemVer philosophy for versioning this software. For versions available, see the release history.
Some resources that provide further context for this software are as follows:
Well it's wide open right now, but later you might look at open issues, forking the project, and submitting a pull request.
The project is licensed under the Apache version 2 license.