sharktopus

Cloud-native GFS cropper — crop GRIB2 before you download

What is sharktopus?

sharktopus is an open-source Python library that fetches Global Forecast System (GFS) data and crops GRIB2 files in the cloud — by bounding box, variables, and vertical levels — before they hit your disk. It deploys a small serverless wgrib2 worker to AWS Lambda, Google Cloud Run, or Azure Functions; each user runs on their own cloud account and pays their own (typically near-zero) bill.

sharktopus is consumer-agnostic: the output is a valid cropped GRIB2 file. Typical use cases:

The typical win for a 72-hour regional domain: ~12 GB → ~200 MB of transfer, ~20 min → ~30 s wall time. Defaults ship WRF-canonical variable and level sets because that's the lineage — override with your own lists for any other consumer.

GitHub PyPI

Legal & policies

Who maintains it?

sharktopus was originally developed to support the CONVECT project“Convective Systems Forecasting: Integrated Analysis of Numerical Modeling, Radar and Satellites” (“Previsão de sistemas convectivos: análise integrada da modelagem numérica, radar e satélites”, CNPq Extreme Events Call 15/2023), coordinated by Dr. Tânia Ocimoto Oda. CONVECT is executed at IEAPM (Instituto de Estudos do Mar Almirante Paulo Moreira, Brazilian Navy) with partner institutions UENF (Universidade Estadual do Norte Fluminense Darcy Ribeiro) and UFPR (Universidade Federal do Paraná). sharktopus itself is maintained as an independent open-source project. Governance is merit-based and documented in GOVERNANCE.md. Contributors retain their own institutional affiliation — see AUTHORS.md.

sharktopus is not a product of, endorsed by, or representing the Brazilian Navy, CNPq, IEAPM, UENF, or UFPR. Institutional acknowledgement and project funding context are not institutional ownership.

Contact

Issues and pull requests: github.com/sharktopus-project/sharktopus/issues
Project email: sharktopus.convect@gmail.com