Map an openEO process graph to a job based on OpenDataCube and Xarray functions.
The openeo-odc
package converts a job from the openEO syntax to an executable Python file, where each openEO process is mapped to its related Xarray function defined in the openeo-processes-python repository. Two processes (load_collection
and load_results
) map to functions depending on Open Data Cube.
Package dependencies:
Note: opendatacube
, xarray
and openeo-processes-python
are not dependencies because this package simply creates a python file that can be executed in the correct environment where these dependencies are resolved.
-
At the moment, this package is only installable from source. So start with cloning the repository:
git clone https://github.com/Open-EO/openeo-odc.git cd openeo-odc
-
It is recommended to install this package in a virtual environment, e.g. by using
venv
(from the Python standard library),virtualenv
, a conda environment, ... For example, to create a new virtual environment usingvenv
(in a folder called.venv
) and to activate it:python3 -m venv .venv source .venv/bin/activate
(You might want to use a different bootstrap python executable instead of
python3
in this example.) -
Install the package in the virtual environment using one of the following ways, as you prefer:
- traditional way:
python setup.py install
- with pip:
pip install .
- if you plan to do development on the
openeo-pg-parser-python
package itself, install it in "development" mode withpython setup.py develop
orpip install -e .
(Note that in this step we are using
python
andpip
from the virtual environment.) - traditional way:
source .venv/bin/activate
python setup.py test
This project has been set up using PyScaffold 3.1. For details and usage information on PyScaffold see https://pyscaffold.org/.