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 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.
- PostgreSQL 10+
- Python 3.8+
- Clone:
git clone https://github.com/opendatacube/datacube-core.git
- Create a Python environment for using the ODC. We recommend conda as the easiest way to handle Python dependencies.
conda 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
./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 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 test in docker container
docker run -ti -v /home/ubuntu/datacube-core:/code opendatacube/datacube-tests: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