Fetch. Cache. Deliver.
Fetchez is a modular and extensible geospatial data engineering framework for discovering, retrieving, caching, transforming, and composing spatial data workflows.
Originally developed as the core fetching engine for the CUDEM project, Fetchez has evolved into a standalone geospatial ETL and workflow platform. Registered data Modules, Bundles, processing Hooks, Presets, recipe Modifiers, and Schemas can be composed through Python, YAML recipes, or the registry-driven command-line interface.
pip install fetchezOptional Extensions: To enable module specific library dependencies, install with the desired extras:
pip install fetchez[full]Compose and run an ad-hoc geospatial pipeline directly from registered Fetchez components.
Fetch Copernicus topography and NOAA multibeam bathymetry for Miami and apply a global audit hook:
fetchez build -R loc:"Miami, FL" audit copernicus multibeamComponents are chained from left to right. Hooks and presets before the first data source are global; hooks and presets following a module or bundle apply only to that source.
For example, apply raster processing only to Copernicus while auditing the complete workflow:
fetchez build \
-R loc:"Miami, FL" \
audit \
copernicus raster_warp --res 1s \
multibeamRegistered bundles can also be filtered directly from the CLI:
fetchez build \
-R loc:"Miami, FL" \
glob-tnm --select products=1m/1_9asExport an ad-hoc pipeline as a reusable YAML recipe:
fetchez build \
-R loc:"Miami, FL" \
--export miami.yaml \
audit copernicus multibeamRun the saved recipe later:
fetchez run miami.yamlUse fetchez modules list, fetchez modules bundles list, fetchez hooks list, and fetchez hooks presets list to discover available components.
import fetchez
# Fetch Electronic Nautical Chart data from NOAA
files = fetchez.get("charts", region=[-120, -118, 33, 34], hooks=['unzip', 'filename_filter:match=.000', 'audit'])Fetchez provides the generic discovery, retrieval, streaming, processing, recipe, and execution framework. Its sister project and Fetchez extension, Globato, adds the elevation-source vocabulary, DEM-oriented presets, MultiStack accumulation, and multi-resolution interpolation workflows used to build reproducible coastal and topobathymetric DEMs.
Globato reuses the Fetchez pipeline model while exposing a curated DEM-focused command-line interface.
Would you like to know more? Check out our Official Documentation to learn about:
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Modules & Bundles: Discover more than more than 100 public geospatial data sources and compose curated source collections.
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Pipeline Building: Build ad-hoc workflows directly from registered Modules, Bundles, Hooks, and Presets with
fetchez build. -
Recipes & YAML: Save, share, reproduce, and execute complete workflows with
fetchez run. -
Hooks & Presets: Stream, filter, transform, inspect, and process data throughout the Fetchez execution lifecycle.
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Bundle Selection: Select subsets of reusable data bundles using declarative configuration fields from YAML or the CLI.
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Recipe Modifiers: Mutate assembled recipes before execution to apply workflow-level policy or conditional composition.
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Domain Schemas: Validate recipes against reusable domain-specific requirements.
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Python API: Search for components, retrieve data, and construct processing workflows directly from Python.
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Plugins & Extensions: Add custom Modules, Hooks, Readers, Streams, Bundles, Presets, Schemas, and domain-specific extensions without modifying Fetchez core.
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Execution Lifecycle: Learn how Fetchez moves data through manifest, file, stream, and collection processing stages.
This project is used by the following open-source projects:
- Globato — A Fetchez extension for reproducible coastal and topobathymetric DEM construction using curated elevation sources, MultiStack accumulation, and multi-resolution interpolation workflows.
- IVERT — The ICESat-2 Validation of Elevations Reporting Tool.
- Transformez — A geospatial reference transformation framework for vertical and spatial datum workflows, with Fetchez integration.
Are you using this project? Open a Pull Request to add your project to the list!
This project is licensed under the MIT License - see the LICENSE file for details.
Copyright (c) 2010-2026 Regents of the University of Colorado