Metadata-Version: 2.4
Name: globato
Version: 0.2.5
Summary: A suite of specialized data processors (Multibeam, Lidar, Raster), etc. for the Fetchez ecosystem.
Project-URL: Homepage, https://github.com/continuous-dems/globato
Project-URL: Repository, https://github.com/continuous-dems/globato
Author-email: Matthew Love <matthew.love@colorado.edu>
Maintainer-email: Matthew Love <matthew.love@colorado.edu>
License: MIT License
        
        Copyright (c) 2010-2026 Regents of the University of Colorado
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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        SOFTWARE.
License-File: LICENSE
Keywords: etl,fetchez,geospatial,lidar,multibeam
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: GIS
Requires-Python: >=3.12
Requires-Dist: click
Requires-Dist: fetchez>=0.5.3
Requires-Dist: fiona
Requires-Dist: h5py
Requires-Dist: laspy[laszip,lazrs]
Requires-Dist: numpy>1.24
Requires-Dist: pandas
Requires-Dist: pyproj>3.6.1
Requires-Dist: pyshp
Requires-Dist: pyyaml
Requires-Dist: rasterio>1.4.0
Requires-Dist: requests
Requires-Dist: scipy
Requires-Dist: shapely
Requires-Dist: transformez>=0.3.2
Provides-Extra: full
Requires-Dist: gdal; extra == 'full'
Requires-Dist: pygmt; extra == 'full'
Requires-Dist: pykrige; extra == 'full'
Requires-Dist: scikit-learn; extra == 'full'
Requires-Dist: verde; extra == 'full'
Provides-Extra: gdal
Requires-Dist: gdal; extra == 'gdal'
Provides-Extra: gmt
Requires-Dist: pygmt; extra == 'gmt'
Provides-Extra: h3
Requires-Dist: h3; extra == 'h3'
Provides-Extra: interpolations
Requires-Dist: pykrige; extra == 'interpolations'
Requires-Dist: verde; extra == 'interpolations'
Provides-Extra: ml
Requires-Dist: scikit-learn; extra == 'ml'
Description-Content-Type: text/markdown

<p align="center">
	<a href="https://github.com/continuous-dems">
		<img src="https://raw.githubusercontent.com/continuous-dems/globato/refs/heads/main/docs/source/_static/continuous_dems_logo_mini.svg" height="80" alt="Continuous DEMs Logo">
	</a>
</p>
<h1 align="center">GloBaTo</h1>
<p align="center"><em>Domo Arigato, Multi-Resolution Globato.</em></p>

<p align="center">
  <a href="https://github.com/continuous-dems/globato"><img src="https://img.shields.io/badge/version-0.2.5-blue.svg" alt="Version"></a>
  <a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-green.svg" alt="License"></a>
  <a href="https://www.python.org/"><img src="https://img.shields.io/badge/python-3.12+-yellow.svg" alt="Python"></a>
  <a href="https://badge.fury.io/py/globato"><img src="https://badge.fury.io/py/globato.svg" alt="PyPI version"></a>
  <a href="https://cudem.zulip.org"><img src="https://img.shields.io/badge/zulip-join_chat-brightgreen.svg" alt="Project Chat"></a>
</p>

**Globato** is the user-facing geospatial engine of the Continuous-DEMs ecosystem. It is designed for the rapid development, blending, and processing of high-accuracy Topo-Bathy Digital Elevation Models (DEMs).

Built on top of the `fetchez` (orchestration) and `transformez` (horizontal and vertical datums) libraries, `globato` abstracts away the complexity of DEM development. It allows users to generate massive, seamless DEMs using declarative YAML recipes or intuitive command-line tools.

---

## ❓ Why Globato?

Traditional DEM generation is often a disjointed, manual process of hunting down, organizing and processing disparate datasets using a wide variety of software and one-off processing scripts.

**Globato standardizes this workflow** by unifying data fetching, spatial filtering, datum transformations, and gridding into a single, memory-safe streaming pipeline. Using declarative YAML recipes, it allows you to orchestrate massive, reproducible Topo-Bathy DEMs directly from your terminal!

---

## 📦 Installation
Install via pip (this will automatically pull in the `fetchez` and `transformez` dependencies):

```bash
pip install globato
```

## 🐄 Quickstart

If you are new to Globato, the best place to start is the Quickstart guide, which will take you from installation to generating your first DEM in under 5 minutes.

* **[Quickstart: From Zero to DEM in 1 arc-second](https://globato.readthedocs.io/user_guide/quickstart.md)**

---

## 📚 Documentation
Would you like to know more? Check out our [Official Documentation](https://globato.readthedocs.io) to learn about:

* **The Python API:** Build custom Digital Elevation Models and process elevation data in your apps.

* **The Globato CLI:** Generate and run globato recipes, fetch elevation data sources, visualize your data all in the command line.

* **DEM Recipes:** Build reproducable DEMs using simple YAML recipes.

---

## ⚖ License

This project is licensed under the MIT License - see the [LICENSE](https://github.com/continuous-dems/fetchez/blob/main/LICENSE) file for details.

Copyright (c) 2010-2026 Regents of the University of Colorado
