Tooling for converting STAC metadata to ODC data model
Project description
odc.stac
Load STAC items into xarray Datasets. Process locally or distribute data loading and computation with Dask.
Usage
odc.stac.load
catalog = pystac_client.Client.open(...)
query = catalog.search(...)
xx = odc.stac.load(
query.get_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.
Installation
Using pip
pip install odc-stac
Using Conda
This package is be available on conda-forge channel:
conda install -c conda-forge odc-stac
From unreleased source
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:
- datacube >=1.8.6
- xarray >= 0.20.1
- numpy
- pandas
- affine
- rasterio
- toolz
- jinja2
- pystac
- pystac-client
- pip =20
- pip:
- "git+https://github.com/opendatacube/odc-stac/"
Developing
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
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