The did-python library is a versioned database API built to manage DID documents and associated binary data.
Basic usage is recommended via Jupyter Notebook. Any Jupyter install should work but Anaconda (Python 3) is an easy way to get started with Jupyter.
did-python uses pipenv for package management, it can be installed with pip.
# Install dependencies (use the --dev flag if you plan to run the linter, test suite, or docs)
$ pipenv install
# Activate virtualenv
$ pipenv shell
# Verify virtual environment (OPTIONAL)
(ndi-python) $ which jupyter
# Start Jupyter Notebook
(ndi-python) $ jupyter notebookThe Python package makes use of native namespace packages available in Python 3.3 and later.
The test suite can be run from the pipenv shell with python -m pytest.
This library is documented in the Jupyter Notebook at ./example/Core_API.