five

Using HydroShare Buckets to Access Resource Files

收藏
DataONE2025-07-23 更新2025-08-02 收录
下载链接:
https://search.dataone.org/view/sha256:b25a0f5e5d62530d70ecd6a86f1bd3fa2ab804a8350dc7ba087327839fcb1fb1
下载链接
链接失效反馈
官方服务:
资源简介:
This resource contains a draft Jupyter Notebook that has example code snippets showing how to access HydroShare resource files using HydroShare S3 buckets. The user_account.py is a utility to read user hydroshare cached account information in any of the JupyterHub instances that HydroShare has access to. The example notebook uses this utility so that you don't have to enter your hydroshare account information in order to access hydroshare buckets. Here are the 3 notebooks in this resource: - hydroshare_s3_bucket_access_examples.ipynb: The above notebook has examples showing how to upload/download resource files from the resource bucket. It also contains examples how to list files and folders of a resource in a bucket. - python-modules-direct-read-from-bucket/hs_bucket_access_gdal_example.ipynb: The above notebook has examples for reading raster and shapefile from bucket using gdal without the need of downloading the file from the bucket to local disk. - python-modules-direct-read-from-bucket/hs_bucket_access_non_gdal_example.ipynb The above notebook has examples of using h5netcdf and xarray for reading netcdf file directly from bucket. It also contains examples of using rioxarray to read raster file, and pandas to read CSV file from hydroshare buckets.
创建时间:
2025-07-26
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作