Google Earth Engine Adapter Microservice

This repository implements the Google Earth Engine Adapter services that are available in the Skydipper API.

Quick Overview

Create a GEE Dataset

To create a new GEE dataset it's necessary to execute the following request.

Important:

• the connectorType value has to be "rest"
• the provider value has to be "gee"

POST: /dataset -> payload:
{
	"dataset": {
		"application": [<application-name>],
		"name": <dataset-name>,
		"connectorType": "rest",
		"provider": "gee",
		"tableName": <table-name>
	}
}

Example (copy&paste)

POST: https://api.skydipper.com/dataset -> payload:
{
	"dataset": {
		"application": ["skydipper"],
		"name": "Data about whatever",
		"connectorType": "rest",
		"provider": "gee",
		"tableName": "ft:1qpKIcYQMBsXLA9RLWCaV9D0Hus2cMQHhI-ViKHo"
	}
}

Once the dataset has been saved (a few seconds after the creation) you can start doing queries to GEE.

Fields

This endpoint returns the available fields in the dataset

GET: /fields/:dataset

Example (copy&paste)

GET: https://api.skydipper.com/fields/68353d61-0f47-4836-9699-72e008cd9f5f

Query

This endpoint returns the execution of the SQL query (sql queryParam is required)

GET: /query/:dataset?sql=<slq_query>

Example (copy&paste)

GET: https://api.skydipper.com/query/68353d61-0f47-4836-9699-72e008cd9f5f?sql=select * from ft:1qpKIcYQMBsXLA9RLWCaV9D0Hus2cMQHhI-ViKHo where width > 100

Download

Download the data in json format (csv coming soon)

GET: /download/:dataset?sql=<slq_query>

Example (copy&paste)

GET: https://api.skydipper.com/download/68353d61-0f47-4836-9699-72e008cd9f5f?sql=select * from ft:1qpKIcYQMBsXLA9RLWCaV9D0Hus2cMQHhI-ViKHo where width > 100

Tests

As this microservice relies on Google Earth Engine, tests require a valid storage.json or equivalent file. At the time of this writing, actual tests use mock calls, so the real credential are only needed because Google's library actually validates the credentials on startup.

Before you run the tests, be sure to install the necessary development libraries, using pip install -r requirements_dev.txt.

Actual test execution is done by running the pytest executable on the root of the project.