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| Type: | Resource | |
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| Created: | Sep 07, 2025 at 5:17 p.m. (UTC) | |
| Last updated: | Sep 07, 2025 at 7:36 p.m. (UTC) | |
| Citation: | See how to cite this resource |
| Sharing Status: | Public |
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Abstract
This resource provides code examples for working directly with HydroShare S3 buckets (also referred to as HydroShare cloud storage buckets or simply HydroShare buckets) to access and manage resource files, without the need to download them locally first. Working directly with S3 buckets can offer better performance.
This resource includes the following notebooks:
1- hydroshare_s3_bucket_access_examples.ipynb: Examples for working directly with HydroShare S3 buckets to access and manage resource files.
2- hs_bucket_access_gdal_example.ipynb: Examples for reading raster and shapefile directly from HydroShare S3 buckets using gdal.
3- hs_bucket_access_non_gdal_example.ipynb: Examples of using h5netcdf and xarray for reading netcdf files, rioxarray for reading raster files, and pandas for reading CSV files, all directly from HydroShare S3 buckets.
This research was supported by the Cooperative Institute for Research to Operations in Hydrology (CIROH) with funding under award NA22NWS4320003 from the NOAA Cooperative Institute Program. The statements, findings, conclusions, and recommendations are those of the author(s) and do not necessarily reflect the opinions of NOAA.
Subject Keywords
Content
README.md
Using HydroShare Buckets to Access Resource Files
This resource includes the following files:
- hydroshare_s3_bucket_access_examples.ipynb: Examples for working directly with HydroShare S3 buckets to access and manage resource files, without the need to download them locally first.
- hs_bucket_access_gdal_example.ipynb: Examples for reading raster and shapefile directly from HydroShare S3 buckets using
gdal, without the need to download them locally first. - hs_bucket_access_non_gdal_example.ipynb: Examples of using 1-
h5netcdfandxarrayfor reading netcdf files, 2-rioxarrayto read raster files, and 3-pandasto read CSV files, all directly from HydroShare S3 buckets, without the need to download them locally first. - user_account.py: A utility for reading cached HydroShare account information in any JupyterHub instance accessible by HydroShare. The example notebooks use this utility so that users do not have to enter their hydroshare account information manually to access hydroshare buckets.
- conda_env: A folder containing the CondaEnvironmentSetup.ipynb notebook with instructions and scripts for setting up a custom Conda environment.
- README.md: Explains the contents of this resource.
To use this resource in HydroShare, select Open With on one of the available application servers to launch the corresponding JupyterHub environment. Then, open the desired Jupyter Notebook and follow the instructions.
Related Resources
| Title | Owners | Sharing Status | My Permission |
|---|---|---|---|
| Interactive Science Use Cases Showcasing HydroShare’s Cloud-Native Features | Irene Garousi-Nejad · Anthony Castronova | Public & Shareable | Open Access |
Credits
Funding Agencies
This resource was created using funding from the following sources:
| Agency Name | Award Title | Award Number |
|---|---|---|
| National Oceanic and Atmospheric Administration (NOAA), University of Alabama | CIROH: Enabling collaboration through data and model sharing with CUAHSI HydroShare | NA22NWS4320003 to University of Alabama, subaward A23-0266-S001 to Utah State University |
How to Cite
This resource is shared under the Creative Commons Attribution CC BY.
http://creativecommons.org/licenses/by/4.0/
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