{"id":18697597,"url":"https://github.com/jarnorfb/radolan-scraper","last_synced_at":"2025-11-08T16:30:40.437Z","repository":{"id":53531766,"uuid":"203410334","full_name":"JarnoRFB/radolan-scraper","owner":"JarnoRFB","description":"Pipeline to scrape and transform history rain radar data into netcdf","archived":false,"fork":false,"pushed_at":"2022-10-24T18:51:06.000Z","size":4804,"stargazers_count":1,"open_issues_count":3,"forks_count":1,"subscribers_count":2,"default_branch":"master","last_synced_at":"2024-12-28T04:15:04.627Z","etag":null,"topics":["netcdf4","opendata","radar","radolan","rain","weather"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/JarnoRFB.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null}},"created_at":"2019-08-20T16:07:05.000Z","updated_at":"2022-06-03T09:15:31.000Z","dependencies_parsed_at":"2023-01-20T11:00:45.051Z","dependency_job_id":null,"html_url":"https://github.com/JarnoRFB/radolan-scraper","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JarnoRFB%2Fradolan-scraper","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JarnoRFB%2Fradolan-scraper/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JarnoRFB%2Fradolan-scraper/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/JarnoRFB%2Fradolan-scraper/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/JarnoRFB","download_url":"https://codeload.github.com/JarnoRFB/radolan-scraper/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":239558926,"owners_count":19658929,"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":["netcdf4","opendata","radar","radolan","rain","weather"],"created_at":"2024-11-07T11:24:54.624Z","updated_at":"2025-11-08T16:30:40.373Z","avatar_url":"https://github.com/JarnoRFB.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# RADOLAN Scraper\nA pipeline to scrape and transform [RADOLAN](https://www.dwd.de/DE/leistungen/radolan/radolan.html) data into netcdf. RADOLAN is a product from the [*Deutscher Wetter Dienst*](https://www.dwd.de/DE/Home/home_node.html) that provides high resolution precipitation records from 2005 - present\nfor Germany.\n\nWhile the data is openly available, it is not in a format that can be easily processed.\nThe included pipeline downloads and transforms data into a single netcdf file, that can\nbe processed by standard tools like [`xarray`](http://xarray.pydata.org/en/stable/).\n\n## Installation\nCreate an environment, using the environment manager of your choice and run\n\n    pip install -r requirements.txt\n\n\n## Usage\nAdd a `.env` file in the top level directory specifying a path to store the data.\nAdditionally, you can specify a logging configuration, but that is not required as a sensible default \nis included. \n\n    BASE_DATA_DIR=/my/data/dir/\n    LOG_CFG=logging.yaml  # Not required. \n\nBy default the pipeline will download all data for the year 2005 - 2018. While\nthe pipelines has constant memory requirements, it will create files consuming ~50G disk space.\nTo only download data for a subset of years, edit the `__main__` section in `pipeline.py` directly.\nThen run\n\n    python radonlan_scraper/pipeline.py\n\n\n## Further processing\nOnce the pipeline ran through, you can visualize the data, for example using `xarray`\n```python\nimport xarray as xr\nds = xr.open_dataset(\"path/to/combined.nc\")\nds[\"rain\"][2000:2006].plot.imshow(\"x\", \"y\", col=\"time\", col_wrap=3, robust=True, origin=\"upper\")\n```\n![example rain visualization](rain.png)","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjarnorfb%2Fradolan-scraper","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjarnorfb%2Fradolan-scraper","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjarnorfb%2Fradolan-scraper/lists"}