Load STAC items into xarray
Datasets. Process locally or distribute data
loading and computation with Dask.
catalog = pystac_client.Client.open(...)
query = catalog.search(...)
xx = odc.stac.load(
query.items(),
bands=["red", "green", "blue"],
)
xx.red.plot.imshow(col="time")
For more details see Documentation and Sample Notebooks, or try it out on Binder.
pip install odc-stac
To install with botocore
support (for working with AWS):
pip install 'odc-stac[botocore]'
This package is be available on conda-forge
channel:
conda install -c conda-forge odc-stac
To use development version of odc-stac
install dependencies from conda
, then
install odc-stac
with pip
.
Sample environment.yml
is provided below.
channels:
- conda-forge
dependencies:
- odc-geo
- xarray
- numpy
- dask
- pandas
- affine
- rasterio
- toolz
- pystac
- pystac-client
- pip
- pip:
- "git+https://github.com/opendatacube/odc-stac/"
To develop odc-stac
locally using pip (assuming you have virtualenvwrapper installed):
git clone https://github.com/opendatacube/odc-stac
cd odc-stac
mkvirtualenv odc-stac
pip install -e .
pip install -r requirements-dev.txt
Run tests with pytest:
pytest
Linting is provided by mypy, pylint, and black:
black --check .
pylint -v odc
mypy odc