harmony-py 0.1.0

The NASA Harmony Python library

harmony-py

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

Using Harmony Py

Prerequisites

• Python 3.7+

Installing

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 virtualenv along with any other dependencies you may have.

Running Examples & Developing on Harmony Py

Prerequisites

• Python 3.7+
• (optional,recommended) pyenv and pyenv-virtualenv

Installing Development & Example Dependencies

First, it's recommended that you create a Python virtualenv so that Harmony Py and its dependencies are isolated in their own environment. To do so, you can either create and activate a Python virtual environment with venv, or--if you have pyenv and pyenv-virtualenv installed--use pyenv to create and activate one for you (harmony-py). There are make targets for both of these options--choose one.

1a. Create a virtualenv with venv:

    $ make venv-setup
    $ source .venv/bin/activate

To deactivate it:

    $ source deactivate

1b. Use pyenv & pyenv-virtualenv. This will install Python 3.9 & create a virtualenv using that version of Python. Important: if this is your first time using pyenv to install Python, be sure that you have the Python build requirements installed first.

    $ make pyenv-setup

If you've setup pyenv with your shell properly, it should automatically activate the environment. You can check if it's activated by:

    $ pyenv version

It should show harmony-py. Pyenv does auto-activation by creating a .python-version file in the project directory. Most shells can be setup to automatically activate & deactivate virtual environments when cd'ing into & out of directories by using the value found in .python-version. This is convenient since it ensures that the correct virtualenv has been activated (and deactivated) when starting work on a project. See the pyenv docs for more details. If you need to manually activate & deactivate:

    $ pyenv activate harmony-py
    $ pyenv deactivate

2. Install dependencies:

    $ make install
   

3. Optionally register your local copy with pip:

    $ pip install -e ./path/to/harmony_py
   

Running the Example Jupyter Notebooks

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 all of the example notebooks use the Harmony UAT environment.

    $ make examples

Developing

Generating Documentation

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).

Running the Linter & Unit Tests

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

Generating Request Parameters

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.

CI

Harmony-py uses GitHub Actions to run the Linter & Unit Tests. The test coverage output is saved as a build artifact.

Building and Releasing

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