Welcome to the DraftCoreDataModel repository. This repository contains an alpha version of the CoreVariantClass and GoldStandardDatabase. The CoreVariantClass is an internal core class developed to facilitate seamless bidirectional translations between various standards, including FHIR, VRS, SPDI, and HGVS. This repository also includes bidirectional translations between VRS and SPDI, HGVS and VRS, and SPDI and HGVS. These translations are achieved using external packages and APIs acknowledged bellow. The GoldStandardDatabase (GSDB) is a human-curated database designed to provide reliable and accurate data for various applications. This repository is in the early stages of development and may undergo occasional changes as progress is made.
To interact with the notebooks without installing or cloning the repository, you can utilize Codespaces. Instructions on how to use Codespaces tools are provided below.
If you're new to using Codespace, you may find the following resources helpful:
- Start off by clicking the Codespaces badge above to get started.
- A prompt to build a code space will pop up with certain specifications.
- Click on Create Codespace.
- NOTE: This will take a few minutes to build your virtual machine.
- Navigate to notebooks and select a notebook you wish to run.
- Locate the "Select Kernel" option on the top right-hand side of the interface.
- Click on "Select Kernel".
- After clicking "Select Kernel", choose "Python Environment...".
- From the dropdown menu, select the Pipenv Environment labeled:
DraftCoreDataModel-.
- Once the appropriate kernel is selected, you can proceed to run the cells inside of the Jupyter notebooks.
- On the bottom left corner of your browser, click on "CodeSpaces:".
- Then click "Stop Current Codespace".
- Once this is done, you have successfully deactivated your Codespace.
To run pytest scripts within a Codespace environment the following steps need to be followed:
To execute the test scripts, it is essential to ensure that you are operating within the virtual environment configured by Pipenv.
# Activate pipenv virtual environment
pipenv shellOnce the virutal environment is activated, navigate to the test directory via the terminal. You can then execute pytest by specifying the particular files you intend to test.
# Execute the specified test file
pytest file_name.pyThis project utilizes several external packages and APIs. The following packages were used: