Contributing

Contributions are welcome, and they are greatly appreciated! Every little bit helps, and credit will always be given.

We have a `code of conduct<code-of-conduct.md>`_, so please follow it in all your interactions with the project.

You can contribute in many ways:

Types of Contributions

Report Bugs

Report bugs at https://github.com/opendatacube/datacube-ows/issues.

If you are reporting a bug, please include:

• Your operating system name and version.

• Any details about your local setup that might be helpful in troubleshooting.

• Detailed steps to reproduce the bug.

Fix Bugs

Look through the GitHub issues for bugs. Anything tagged with “bug” and “help wanted” is open to whoever wants to implement it.

Implement Features

Look through the GitHub issues for features. Anything tagged with “enhancement” and “help wanted” is open to whoever wants to implement it.

Write Documentation

datacube-ows could always use more documentation, whether as part of the official datacube-ows docs, in docstrings, or even on the web in blog posts, articles, and such.

Submit Feedback

The best way to send feedback is to file an issue at https://github.com/opendatacube/datacube-ows/issues .

If you are proposing a feature:

• Explain in detail how it would work.

• Keep the scope as narrow as possible, to make it easier to implement.

• Remember that this is a volunteer-driven project, and that contributions are welcome :)

Get Started!

1. Fork the datacube-ows repo on GitHub.

2. Clone your fork locally:

   $ git clone git@github.com:your_name_here/datacube-ows.git
   

3. Follow the instructions in `README.rst<https://datacube-ows.readthedocs.io/en/latest/readme.html>`_ to build a working python environment.

4. Create a branch for local development:

   $ git checkout -b name-of-your-bugfix-or-feature
   

   Now you can make your changes locally.

5. When you’re done making changes, check that your changes pass flake8 and the tests, including testing other Python versions with tox:

   $ flake8 datacube-ows tests
   $ python setup.py test or py.test
   $ tox
   

   To get flake8 and tox, just pip install them into your virtualenv.

6. Commit your changes and push your branch to GitHub:

   $ git add .
   $ git commit -m "Your detailed description of your changes."
   $ git push origin name-of-your-bugfix-or-feature
   

7. Submit a pull request through the GitHub website.

Pull Request Guidelines

Before you submit a pull request, check that it meets these guidelines:

1. The pull request should include tests (and should pass them - and all pre-existing tests!)

2. If the pull request adds or modifies functionality, the docs should be updated.

3. The pull request should work for Python 3.7+. Check the results of the github actions and make sure that your PR passes all checks and does not decrease test coverage.

Integration test data and cfg update

setting a NEW db dump

# bring up indexing and db container
docker-compose -f docker-compose.index.yaml -f docker-compose.cleandb.yaml up

building on top of existing db dump

docker-compose -f docker-compose.yaml -f docker-compose.index.yaml -f docker-compose.db.yaml up

checkpoint

by this point, there should be 3 docker container running: - 1 for database - 1 for indexing - 1 for ows

to check the containers that are running use docker ps

indexing and create db dump

# start by going to index container
docker exec -ti datacube-ows-index-1 bash
datacube system init # OPTIONAL: no need to run this command if building off existing db
datacube product add https://raw.githubusercontent.com/digitalearthafrica/config/master/products/esa_s2_l2a.odc-product.yaml
stac-to-dc --bbox='123.92427299922684,-14.559406653491095,124.94716787178676,-13.560932176423318' --collections='sentinel-s2-l2a-cogs' --datetime='2021-12-20/2022-01-10'
... # anything extra to index
exit # after indexing is complete, exit

# now go to ows container
docker exec -it datacube-ows_ows_1 bash
datacube-ows-update --schema --role <db_read_role>
datacube-ows-update --views
datacube-ows-update
exit

# return to index container
docker exec -it index_index_1 bash # if using chained docker-compose the container name is datacube-ows_index_1
pg_dump -U localhost -p 5432 -h localhost odc > dump.sql
# enter password on prompt: mysecretpassword or check .env file
exit


# copy the new dump to datacube-ows/docker/database folder
docker cp datacube-ows_ows_1:/dump.sql datacube-ows/docker/database

If the integration test is based on a new product and require new config translation, continue the following.

# enter ows container
docker exec -it datacube-ows_ows_1 bash
datacube-ows-cfg extract -m /tmp/messages.po
datacube-ows-cfg translation -n -D ows_cfg -d /tmp/translations -m /tmp/messages.po en de

manually modify translation for de for assert test to pass, then create ows_cfg.mo

datacube-ows-cfg compile -D ows_cfg -d /tmp/translations en de
exit
# from outside of the container, cp all the translation files to local.
docker cp datacube-ows_ows_1:/tmp/translations datacube-ows/integrations/cfg/

Generating database relationship diagram

docker run -it --rm -v "$PWD:/output" --network="host" schemaspy/schemaspy:snapshot -u $DB_USERNAME -host localhost -port $DB_PORT -db $DB_DATABASE -t pgsql11 -schemas wms -norows -noviews -pfp -imageformat svg

Merge relationship diagram and orphan diagram

python3 svg_stack.py --direction=h --margin=100 ../wms/diagrams/summary/relationships.real.large.svg ../wms/diagrams/orphans/orphans.svg > ows.merged.large.svg

cp svg_stack/ows.merged.large.svg ../datacube-ows/docs/diagrams/db-relationship-diagram.svg

Links

In case you haven’t found them yet, please checkout the following resources:

• Documentation

• Slack