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odc.stac

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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

Metadata

Release files for odc-stac 0.5.3

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

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Table of built distributions (wheels) for odc-stac 0.5.3
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