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

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

> pip install pystac

if you'd like to enable the validation feature utilizing the jsonschema project, install with the optional validation requirements:

> pip install pystac[validation]

From source repository:

> git clone https://github.com/azavea/pystac.git
> cd pystac
> pip install .

To install a specific versions of STAC, install the matching version of pystac.

> pip install pystac==0.5.*

The table below shows the corresponding versions between pystac and STAC:

See the documentation page for the latest docs.

To ensure development libraries are installed, install everything in requirements-dev.txt:

> pip install -r requirements-dev.txt

Unit tests are in the tests folder. To run unit tests, use unittest:

> python -m unittest discover tests

To run linters, code formatters, and test suites all together, use test:

> ./scripts/test

PySTAC uses flake8 and yapf for code formatting and style checks.

To run the flake8 style checks:

> flake8 pystac
> flake8 tests

To format code:

> yapf -ipr pystac
> yapf -ipr tests

You can also run the ./scripts/test script to check flake8 and yapf.

To build and develop the documentation locally, make sure sphinx is available (which is installed with requirements-dev.txt), and use the Makefile in the docs folder:

> cd docs
> make html
> make livehtml

Use 'make' without arguments to see a list of available commands.

Note: nbsphinx requires that a local pystac is installed; use pip install -e ..

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.