An analysis environment for satellite and other earth observation data
Project description
Open Data Cube Core
Overview
The Open Data Cube Core provides an integrated gridded data analysis environment for decades of analysis ready earth observation satellite and related data from multiple satellite and other acquisition systems.
Documentation
See the user guide for installation and usage of the datacube, and for documentation of the API.
Join our Slack if you need help setting up or using the Open Data Cube.
Please help us to keep the Open Data Cube community open and inclusive by reading and following our Code of Conduct.
Requirements
System
PostgreSQL 9.5+
Python 3.6+
Developer setup
Clone:
git clone https://github.com/opendatacube/datacube-core.git
Create a Python environment to use ODC within, we recommend conda as the easiest way to handle Python dependencies.
conda create -n odc -c conda-forge python=3.6 datacube pre_commit conda activate odc
Install a develop version of datacube-core.
cd datacube-core pip install --upgrade -e .
Install the pre-commit hooks to help follow ODC coding conventions when committing with git.
pre-commit install
Run unit tests + PyLint ./check-code.sh
(this script approximates what is run by Travis. You can alternatively run pytest yourself). Some test dependencies may need to be installed, attempt to install these using:
pip install --upgrade -e '.[test]'
If install for these fails please lodge them as issues.
(or) Run all tests, including integration tests.
./check-code.sh integration_tests
Assumes a password-less Postgres database running on localhost called
agdcintegration
Otherwise copy integration_tests/agdcintegration.conf to ~/.datacube_integration.conf and edit to customise.
Alternatively one can use opendatacube/datacube-tests docker image to run tests. This docker includes database server pre-configured for running integration tests. Add --with-docker command line option as a first argument to ./check-code.sh script.
./check-code.sh --with-docker integration_tests
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