Harmony-Py is a Python library for integrating with NASA's Harmony Services.
Harmony-Py provides a Python alternative to directly using Harmony's RESTful API. It handles NASA Earthdata Login (EDL) authentication and optionally integrates with the CMR Python Wrapper by accepting collection results as a request parameter. It's convenient for scientists who wish to use Harmony from Jupyter notebooks as well as machine-to-machine communication with larger Python applications.
Harmony-Py is a work-in-progress, is not feature complete, and should only be used if you would like to test its functionality. We welcome feedback on Harmony-Py via GitHub Issues
- Python 3.7+
The library is available from PyPI and can be installed with pip:
$ pip install -U harmony-py
This will install harmony-py and its dependencies into your current Python environment. It's recommended that you install harmony-py into a virtual environment along with any other dependencies you may have.
- Python 3.7+, ideally installed via a virtual environment
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Install dependencies:
$ make install -
Optionally register your local copy with pip:
$ pip install -e ./path/to/harmony_py
Jupyter notebooks in the examples subdirectory show how to use the Harmony Py library. Start up the Jupyter Lab notebook server and run these examples:
The Jupyter Lab server will start and open in your browser. Double-click on a notebook in the file-browser sidebar and run the notebook. Note that some notebooks may have cells which prompt for your EDL username and password. Be sure to use your UAT credentials since most of the example notebooks use the Harmony UAT environment.
$ make examples
Documentation on the Read The Docs site is generated automatically. It is generated by using sphinx with reStructuredText (.rst) and other files in the docs directory. To generate the docs locally and see what they look like:
$ make docs
You can then view the documentation in a web browser under ./docs/_build/html/index.html.
IMPORTANT: The documentation uses a notebook from the examples directory rendered as HTML. If you've modified that notebook (see Makefile for notebook that is currently rendered), you will need to run make docs locally. You will see a change to the docs/user/notebook.html file after doing so. This file should be committed to the git repo since it is used when the latest docs are pushed to the Read The Docs site (it can't currently be generated as part of the build).
Run the linter on the project source:
$ make lint
Run unit tests and test coverage. This will display terminal output and generate an HTML coverage report in the htmlcov directory.
$ make test
For development, you may want to run the unit tests continuously as you update tests and the code-under-test:
$ make test-watch
The harmony.Request constructor can accept parameters that are defined in the Harmony OGC API schema. If this schema has been changed and the Request constructor needs to be updated, you may run the generator utility. This tool reads the Harmony schema and generates a partial constructor signature with docstrings:
$ python internal/genparams.py ${HARMONY_DIR}/app/schemas/ogc-api-coverages/1.0.0/ogc-api-coverages-v1.0.0.yml
Either set HARMONY_DIR or replace it with your Harmony project directory path. You may then write standard output to a file and then use it to update the harmony.Request constructor and code.
Harmony-py uses GitHub Actions to run the Linter & Unit Tests. The test coverage output is saved as a build artifact.
If a new version of Harmony-Py will be released then the master branch should be tagged with an updated version:
$ git checkout master
$ git tag -a v1.2.3 # where v1.2.3 is the next version number
In order to generate new package and wheel files, do the following:
$ make build
make reads the current version number based on git tag, populates the version in harmony/__init__.py, and setup.py reads the version number from harmony/__init__.py for packaging purposes.
This leaves us with a modifed __init__.py which must be committed and pushed to master.
$ git add harmony/__init__.py
$ git commit -m "Version bump to v1.2.3"
$ git tag -f
$ git push
Then, provided API tokens are in order, the following runs the build target and publishes to PyPI:
$ make publish