{"id":21165081,"url":"https://github.com/denbonte/cloudyday","last_synced_at":"2025-03-14T16:37:17.423Z","repository":{"id":219391534,"uuid":"618023443","full_name":"denbonte/cloudyday","owner":"denbonte","description":"Dummy benchmarking for common cloud download tools.","archived":false,"fork":false,"pushed_at":"2023-03-24T10:41:24.000Z","size":321,"stargazers_count":3,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-01-21T10:07:29.680Z","etag":null,"topics":["cloud","cloudcomputing","data-science","google-cloud-platform","medical-image-processing","medical-imaging"],"latest_commit_sha":null,"homepage":"","language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/denbonte.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null}},"created_at":"2023-03-23T15:40:18.000Z","updated_at":"2023-09-28T14:06:09.000Z","dependencies_parsed_at":"2024-01-27T06:00:20.831Z","dependency_job_id":"3ea3be39-e771-4679-a5ca-8ee443b699ec","html_url":"https://github.com/denbonte/cloudyday","commit_stats":null,"previous_names":["denbonte/cloudyday"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/denbonte%2Fcloudyday","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/denbonte%2Fcloudyday/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/denbonte%2Fcloudyday/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/denbonte%2Fcloudyday/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/denbonte","download_url":"https://codeload.github.com/denbonte/cloudyday/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":243612741,"owners_count":20319399,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["cloud","cloudcomputing","data-science","google-cloud-platform","medical-image-processing","medical-imaging"],"created_at":"2024-11-20T14:19:09.261Z","updated_at":"2025-03-14T16:37:17.394Z","avatar_url":"https://github.com/denbonte.png","language":"Jupyter Notebook","readme":"# Cloud Download Benchmarks 🌦️\n\nDummy benchmarking for common Google Storage Buckets download tools (`s5cmd`, `gsutil`, `gcloud storage`).\n\n\n# Running the Benchmarking\n\n## Google Colab\nIf you don't want to install or configure anything on your local system, check out the benchmarking in this Colab notebook 👇\n\n[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/denbonte/cloudyday/blob/main/notebooks/download_benchmark.ipynb)\n\n## Local Node\nTo run the benchmark on your local node, you will need to install Google's `gsutil` and `gcloud`, both part of the `google-cloud-sdk` that can be installed (and configured) following [this guide](https://cloud.google.com/storage/docs/gsutil_install).\n\nTo install `s5cmd`, follow the instructions in the [official repository](https://github.com/peak/s5cmd) or check out how we did it in [our Colab notebook](https://github.com/denbonte/cloudyday/blob/main/notebooks/download_benchmark.ipynb):\n\n```\nwget https://github.com/peak/s5cmd/releases/download/v2.0.0/s5cmd_2.0.0_Linux-64bit.tar.gz\nmkdir -p s5cmd \u0026\u0026 tar zxf s5cmd_2.0.0_Linux-64bit.tar.gz -C s5cmd\ncp s5cmd/s5cmd /usr/bin \u0026\u0026 rm s5cmd_2.0.0_Linux-64bit.tar.gz\n```\n\nFor a quick introduction on how to run `s5cmd`, you can check out the tutorial at [this webpage](https://learn.canceridc.dev/data/downloading-data/downloading-data-with-s5cmd).\n\nThe very simple scripts used for benchmarking are found in the `src` folder. You might need to change a couple of paths for this to work.\n\n# Data\n\nThe manifestos specifying the data to pull can be found in the `data` folder.\n\nThe benchmark was run using, as a test case, a number of DICOM files hosted by the [Imaging Data Commons](https://portal.imaging.datacommons.cancer.gov/) (IDC) Google Storage Buckets. Similarly, the Colab notebook fetches data from the IDC buckets following the instructions found in the [IDC Tutorials](https://github.com/ImagingDataCommons/IDC-Tutorials).\n\nIf you want to learn more about the Imaging Data Commons, you can do so starting from their [documentation page](https://learn.canceridc.dev/).\n\n# Notes\n\nChatGPT suggested \"cloudy with a chance of downloads\" as a repo name, but I felt like the name was too long.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenbonte%2Fcloudyday","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdenbonte%2Fcloudyday","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdenbonte%2Fcloudyday/lists"}