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.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
To install with botocore support (for working with AWS):
pip install 'odc-stac[botocore]'
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:
- odc-geo
- xarray
- numpy
- dask
- pandas
- affine
- rasterio
- toolz
- pystac
- pystac-client
- pip
- pip:
- "git+https://github.com/opendatacube/odc-stac/"
Developing
To develop odc-stac locally it’s best to use provided devcontainer.
git clone https://github.com/opendatacube/odc-stac
code odc-stac
Once running inside the dev container, run tests with pytest:
pytest
Linting is provided by mypy, pylint, and black:
black --check .
pylint -v odc
mypy odc
Project details
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