Montandon Extension for PySTAC

This project provides a Python library for working with the SpatioTemporal Asset Catalog (STAC) extension for Montandon. It extends the capabilities of PySTAC to handle disaster and hazard-related data using the Montandon schema.

Features

• Extend STAC Collections and Items with Montandon-specific properties.
• Support for hazard detail objects.
• Integration with GDACS data sources.
• Utilities for pairing and correlation ID generation.

Installation

To install the library, use pip:

pip install pystac_monty

To install the tool jq, use the following:

Debian/Ubuntu/Mint environment

sudo apt-get update
sudo apt-get install jq

MacOS environment

brew install jq

To check if it is install correctly

jq --version

Usage

Batch export (CLI)

To export upstream source files to on-disk Monty STAC, first initialise the submodule:

git submodule update --init --recursive

Then run the CLI. SOURCE is one of glide, gfd, gdacs; --input accepts a source-specific file (see the convert_* docstrings in pystac_monty/sources/batch_export.py):

pystac-monty SOURCE --input path/to/input --output path/to/output/

The output directory will contain role collections ({slug}-events/, {slug}-hazards/, etc.), each with a collection JSON and flat item files. Raw source payloads live in monty-stac-extension/docs/model/sources/ — the examples/ folders are published STAC output, not inputs.

To add more sources or use the exporter programmatically, see pystac_monty/exporter.py.

Extending a STAC Item

The library provides classes and functions to work with Montandon STAC objects. Here is an example of how to create a Montandon Item:

import pystac
from pystac_monty.extension import MontyExtension

item = pystac.Item(...)  # Create or load a STAC Item
monty_ext = MontyExtension.ext(item)
monty_ext.episode_number = 1
print(monty_ext.episode_number)

Working with GDACS data

To transform GDACS event data into STAC Items:

from pystac_monty.sources.gdacs import GDACSTransformer, GDACSDataSource

data_source = GDACSDataSource(source_url="...", data="...", type=GDACSDataSourceType.EVENT)
transformer = GDACSTransformer(data=[data_source])
items = transformer.make_items()

Development

To set up the development environment:

pip install uv
uv sync

To run the tests:

1. Make the test with actual calls to http and write them in the cassette files:

uv run pytest -v -s --record-mode rewrite

2. Run the tests with the recorded calls:

uv run pytest -v -s

Contributing

Contributions are welcome! Please open an issue or submit a pull request.

License

This project is licensed under the Apache License, Version 2.0. See the LICENSE file for more details.

Links

• Documentation
• Repository
• Issues