pystac 1.2.0

Python library for working with Spatiotemporal Asset Catalog (STAC).

PySTAC

PySTAC is a library for working with SpatioTemporal Asset Catalog in Python 3.

Installation

PySTAC requires Python >= 3.7. This project follows the recommendations of NEP-29 in deprecating support for Python versions. This means that users can expect support for Python 3.7 to be removed from the main branch after Dec 26, 2021 and therefore from the next release after that date.

Note that while we support Python 3.10.*, wheels for the orjson library are not always immediately available for all platforms. If you install PySTAC with the orjson extra, you may need to have the Rust toolchain installed (e.g. via rustup) in order to build the package from source.

PySTAC has a single required dependency (python-dateutil). PySTAC can be installed from pip or the source repository.

> pip install pystac

If you would like to enable the validation feature utilizing the jsonschema project, install with the optional validation requirements:

> pip install pystac[validation]

If you would like to use the orjson instead of the standard json library for JSON serialization/deserialization, install with the optional orjson requirements:

> pip install pystac[orjson]

orjson wheels are only available for Linux in Python 3.10. If you are using the orjson extra with Python 3.10 you will need to have the Rust nightly toolchain installed as your default toolchain in order to build the package wheel.

From source repository:

> git clone https://github.com/stac-utils/pystac.git
> cd pystac
> pip install .

Versions

To install a version of PySTAC that works with a specific versions of the STAC specification, install the matching version of PySTAC from the following table.

PySTAC	STAC
1.x	1.0.x
0.5.x	1.0.0-beta.*
0.4.x	0.9.x
0.3.x	0.8.x

For instance, to work with STAC v0.9.x:

pip install pystac==0.4.0

STAC spec versions below 0.8 are not supported by PySTAC.

Documentation

See the documentation page for the latest docs.

Developing

See contributing docs for details on contributing to this project.

Running the quickstart and tutorials

There is a quickstart and tutorials written as jupyter notebooks in the docs/tutorials folder. To run the notebooks, run a jupyter notebook with the docs directory as the notebook directory:

> PYTHONPATH=`pwd`:$PYTHONPATH jupyter notebook --ip 0.0.0.0 --port 8888 --notebook-dir=docs

You can then navigate to the notebooks and execute them.

Requires Jupyter be installed.