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.
See the user guide for installation and usage of the datacube, and for documentation of the API.
Join our Discord 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.
This is a 1.9.x
series release of the Open Data Cube. If you are migrating from a 1.8.x
series release, please refer to the
1.8.x to 1.9.x Migration Notes.
- PostgreSQL 15+
- Python 3.10+
- Clone:
git clone https://github.com/opendatacube/datacube-core.git
- Create a Python environment for using the ODC. We recommend Mambaforge as the easiest way to handle Python dependencies.
mamba env create -f conda-environment.yml conda activate cubeenv
- 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
Install test dependencies using:
pip install --upgrade -e '.[test]'
If install for these fails, please lodge them as issues.
Run unit tests with:
./check-code.sh
(this script approximates what is run by GitHub Actions. You can alternatively run
pytest
yourself).
(or) Run all tests, including integration tests.
./check-code.sh integration_tests
- Assumes the sexistence of two password-less Postgres databases running on localhost called
pgintegration
andpgisintegration
. - Otherwise copy
integration_tests/integration.conf
to~/.datacube_integration.conf
and edit to customise. - For instructions on setting up a password-less Postgres database, see
- the developer setup instructions.
- Assumes the sexistence of two password-less Postgres databases running on localhost called
Alternatively one can use the 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
To run individual tests in a docker container
docker build --tag=opendatacube/datacube-tests-local --no-cache --progress plain -f docker/Dockerfile . docker run -ti -v $(pwd):/code opendatacube/datacube-tests-local:latest pytest integration_tests/test_filename.py::test_function_name
Building a Python virtual environment on Ubuntu suitable for development work.
Install dependencies:
sudo apt-get update sudo apt-get install -y \ autoconf automake build-essential make cmake \ graphviz \ python3-venv \ python3-dev \ libpq-dev \ libyaml-dev \ libnetcdf-dev \ libudunits2-dev
Build the python virtual environment:
pyenv="${HOME}/.envs/odc" # Change to suit your needs mkdir -p "${pyenv}" python3 -m venv "${pyenv}" source "${pyenv}/bin/activate" pip install -U pip wheel cython numpy pip install -e '.[dev]' pip install flake8 mypy pylint autoflake black