pystac-client 0.3.2

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

STAC Client

A Python client for working with STAC Catalogs and APIs.

Installation

Install from PyPi. Other than PySTAC itself, the only dependencies for pystac-client is the Python requests and dateutil libraries.

$ pip install pystac-client

Documentation

See the documentation page for the latest docs.

Development

For development, clone the repository and use the standard Python method for installing the library as an "editable link", then install the development dependencies:

$ git clone https://github.com/stac-utils/pystac-client.git
$ cd pystac-client
$ pip install -e .
$ pip install -r requirements-dev.txt

To run just the tests

$ pytest -v -s --block-network --cov pystac_client --cov-report term-missing

The pystac-client tests use vcrpy to mock API calls with "pre-recorded" API responses. When adding new tests use the @pytest.mark.vcr decorator function to indicate vcrpy should be used. Record the new responses and commit them to the repository.

$ pytest -v -s --record-mode new_episodes --block-network
$ git add <new files here>
$ git commit -a -m 'new test episodes'

To update pystac-client to use future versions of STAC API, the existing recorded API responsees should be "re-recorded":

$ pytest -v -s --record-mode rewrite --block-network
$ git commit -a -m 'updated test episodes'

Pull Requests

To make Pull Requests to pystac-client, the code must pass linting, formatting, and code tests. To run the entire suit of checks and tests that will be run the GitHub Action Pipeline, use the test script.

$ scripts/test

If automatic formatting is desired (incorrect formatting will cause the GitHub Action to fail), use the format script and commit the resulting files:

$ scripts/format
$ git commit -a -m 'formatting updates'

To build the documentation, install the documentation requirements, then use the build-docs script:

$ pip install -r requirements-docs.txt
$ scripts/build-docs