Fetchez
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.
📦 Installation
pip install fetchez
Optional Extensions: To enable module specific library dependencies, install with the desired extras:
pip install fetchez[full]
🐄 Quickstart
Compose and run an ad-hoc geospatial pipeline directly from registered Fetchez components.
CLI
Fetch Copernicus topography and NOAA multibeam bathymetry for Miami and apply a global audit hook:
fetchez build -R loc:"Miami, FL" audit copernicus multibeam
Components 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 \
multibeam
Registered bundles can also be filtered directly from the CLI:
fetchez build \
-R loc:"Miami, FL" \
glob-tnm --select products=1m/1_9as
Export an ad-hoc pipeline as a reusable YAML recipe:
fetchez build \
-R loc:"Miami, FL" \
--export miami.yaml \
audit copernicus multibeam
Run the saved recipe later:
fetchez run miami.yaml
Use fetchez modules list, fetchez modules bundles list, fetchez hooks list, and fetchez hooks presets list to discover available components.
Python
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'])
DEM Building with Globato
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.
📚 Documentation
Would you like to know more? Check out our Official Documentation to learn about:
-
Modules & Bundles: Discover more than more than 100 public geospatial data sources and compose curated source collections.
-
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.
-
Bundle Selection: Select subsets of reusable data bundles using declarative configuration fields from YAML or the CLI.
-
Recipe Modifiers: Mutate assembled recipes before execution to apply workflow-level policy or conditional composition.
-
Domain Schemas: Validate recipes against reusable domain-specific requirements.
-
Python API: Search for components, retrieve data, and construct processing workflows directly from Python.
-
Plugins & Extensions: Add custom Modules, Hooks, Readers, Streams, Bundles, Presets, Schemas, and domain-specific extensions without modifying Fetchez core.
-
Execution Lifecycle: Learn how Fetchez moves data through manifest, file, stream, and collection processing stages.
🛠️ Used By
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!
⚖ License
This project is licensed under the MIT License - see the LICENSE file for details.
Copyright (c) 2010-2026 Regents of the University of Colorado
Metadata
Release files for fetchez 0.10.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fetchez-0.10.0.tar.gz | 1.5 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fetchez-0.10.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 3.2 MB
Release files / fetchez-0.10.0.tar.gz
| Download URL | fetchez-0.10.0.tar.gz |
|---|---|
| Size | 1.5 MB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
dee78c52a9cd4f411754ad505c08201e1add06dfa2dbea6eb687536369ddecd2
|
|
BLAKE2b-256 checksum How to use checksums |
f87e9ee112e96dda137fca5bbf69317ded61e1eb1fc94fb07b0984fe456d677f
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 6, 2026.
Transparency logRelease files / fetchez-0.10.0-py3-none-any.whl
| Download URL | fetchez-0.10.0-py3-none-any.whl |
|---|---|
| Size | 1.6 MB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
236dfb31aa8a78e8453183942f6b6dc5ed78d0aa938188ee12ff936a13f71a24
|
|
BLAKE2b-256 checksum How to use checksums |
60452b5ad88e33919365001089b9da0199992d0214b768f55f068199fd85502b
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
Yes |
| Uploaded via |
twine/7.0.0 CPython/3.13.14
|
Provenance
Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.
PyPI Publish Attestation
PyPI verified that this artifact, at this checksum, originated from the publisher listed below.
Signed by GitHub Actions, verified by PyPI on Oct 6, 2026.
Transparency log