Welcome to Geospatial Analysis Pipelines (GAPs)!
Geospatial Analysis Pipelines (GAPs) is a framework designed to assist researchers and software developers add execution tools to their geospatial python models. Born from the open-source reV model, GAPs is a robust and easy-to-use engine that provides a rich set of features such as command-line interface (CLI) generation and documentation, basic High-Performance Computing (HPC) scaling capabilities, configuration file generation, job status monitoring, and more.
Who should use GAPs
GAPs is intended to be used by researchers and/or software developers who have implemented a working python model but have not yet added any external model execution tools. Within minimal effort, developers can use GAPs to add a variety of utility for end-users, including a complete set of CLI commands and documentation pulled from the model run function docstrings. In addition, GAPs provides basic HPC execution capabilities, particularly catered towards embarrassingly parallel geospatial models (e.g. single-location models such as the System Advisor Model). GAPs can automatically distribute the execution of such models over a large geospatial extent (e.g. CONUS) across many parallel HPC nodes.
GAPs is NOT a workflow management system (WMS), and therefore does not provide any of the in-depth tools/capabilities expected from a proper WMS. However, GAPs-supported models can sometimes be included as part of the workflow in WMS tools like Torc.
To get started, take a look at the examples for analysts or model developers or dive straight into the full documentation.
Installing GAPs
The quickest way to install GAPs for users is from PyPi:
pip install nlr-gaps
If you are a developer contributing to GAPs, we recommend using pixi:
pixi shell
For detailed instructions, see the installation documentation.
Development
Please see the Development Guidelines if you wish to contribute code to this repository.
Acknowledgments
Paul Pinchuk and Grant Buster. Geospatial Analysis Pipelines. 2023. https://doi.org/10.11578/dc.20230426.7
The authors of this code would like to thank ExxonMobil Corporation for their contributions to this effort.
Release files for NLR-GAPs 0.11.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| nlr_gaps-0.11.0.tar.gz | 175.7 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| nlr_gaps-0.11.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 277.3 kB
Release files / nlr_gaps-0.11.0.tar.gz
| Download URL | nlr_gaps-0.11.0.tar.gz |
|---|---|
| Size | 175.7 kB |
| Tags | Source |
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SHA-256 checksum How to use checksums |
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| Size | 101.6 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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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.
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