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reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"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":[],"created_at":"2024-10-28T13:35:21.154Z","updated_at":"2026-02-21T17:33:03.825Z","avatar_url":"https://github.com/jmacd.png","language":"Rust","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Duckpond\n\nDuckpond is a very small data lake. :-)\n\nDuckpond is built by the [Caspar Water System](https://github.com/jmacd/caspar.water).\n\nDuckpond writes timeseries data into multi-Parquet file databases and\nassembles them for export using DuckDB.  A sibling project [Noyo Blue\nEconomy](https://github.com/jmacd/noyo-blue-econ) shows how to combine\nthis output within [Observable\nFramework](https://observablehq.com/framework/) markdown.\n\nWarning! Work-in-progress. This works and needs testing! :-)\n\n![Caspar, California Duck Pond](./caspar_duckpond.jpg)\n\n## Resource categories\n\n### HydroVu\n\nA receiver for www.hydrovu.com environmental monitoring data.  To\ninstantiate one of these, for example:\n\n```\napiVersion: www.hydrovu.com/v1\nkind: HydroVu\nname: noyo-harbor\ndesc: Noyo Harbor Blue Economy\nspec:\n  key: ...\n  secret: ...\n```\n\nThis downloads the complete set of data for all locations and\ninstruments.  Configure key and secret fields using values supplied by\nthe HydroVu system.\n\n### Backup\n\nAn exporter for backing up all files in the Pond to a storage bucket.\n\n```\napiVersion: github.com/jmacd/duckpond/v1\nkind: Backup\nname: cloudflare\ndesc: Backup to Cloudflare R2\nspec:\n  bucket: noyoharbor\n  region: ...\n  key: ...\n  secret: ...\n  endpoint: ...\n```\n\nConfigure region, key, secret, and endpoint fields using values\nsupplied by your service provider.\n\n### Copy\n\nLoads from a Backup storage bucket.\n\n```\napiVersion: github.com/jmacd/duckpond/v1\nkind: Copy\nname: cloudflare\ndesc: Backup from storage\nspec:\n  bucket: noyoharbor\n  region: ...\n  key: ...\n  secret: ...\n  endpoint: ...\n  backup_uuid: 6fe1e0e1-b262-4d99-ae6f-3cae39e1196a\n```\n\nConfigure region, key, secret, and endpoint the same as you \nwould for the corresponding Backup.\n\n### Inbox\n\nIngest files from a local directory on the host file system.\n\n```\napiVersion: github.com/jmacd/duckpond/v1\nkind: Inbox\nname: csvin\ndesc: CSV inbox\nspec:\n  pattern: /home/user/inbox/csv/**\n```\n\nThe files will be placed in a directory named `/Inbox/{UUID}`.\n\n### Derive\n\nRegister a SQL query to transform arbitrary data (e.g., from the\nInbox) into a desired representation.  The query will be executed once\nper target file matching the pattern in the Pond.\n\n```\napiVersion: github.com/jmacd/duckpond/v1\nkind: Derive\nname: csvextract\ndesc: Extract from CSV\nspec:\n  collections:\n  - pattern: /Inbox/csvdata/*surface*.csv\n    name: SurfaceMeasurements\n    query: \u003e\n      \n      WITH INPUT as ... \n\t  SELECT ... \n\t  FROM read_csv('$1')\n\t  ...\n```\n\nThe placeholder `$1` is replaced by the real path of each file\nmatching the configured pattern, and the resulting derived files are\npopulated with the results of the `query` in a synthetic Pond\ndirectory named `/Derive/{UUID}/{spec.name}`.\n\n### Combine\n\nUse the Combine resource to merge a set of files with different names\nand identical schemas.  This is accomplished by an automatically\ngenerated UNION statement executed by DuckDB.\n\n```\napiVersion: www.hydrovu.com/v1\nkind: Combine\nname: noyo-data\ndesc: Noyo harbor instrument collections\nspec:\n  scopes:\n  - name: FieldStation-Surface\n    series:\n    - pattern: /Derive/othersource/SurfaceMeasurements/*\n```\n\n### Template\n\nUse the Template resource to synthesize content generated through the\nRust `Tera` template engine.  Each named collection applies the\nsupplied pattern, which must capture a single variable.  For each\nmatch, the captured value becomes the basename of a file with the\ncontents of the expanded template.\n\n```\napiVersion: github.com/jmacd/duckpond/v1\nkind: Template\nname: website\ndesc: observable\nspec:\n  collections:\n  - name: details\n    in_pattern: \"/Combine/noyodata/*/combine\"\n    out_pattern: \"$0.md\"\n    template: |-\n      ---\n      title: Detail with combined data\n      ---\n\t  {% for field in schema.fields %}\n\t\t{{ field.name }}\n\t  {% endfor %}\n```\n\nThe template context includes the schema of the matching file in a\nvariable named \"schema\".  The schema is an array of fields:\n\n```\npub struct Schema {\n    fields: Vec\u003cField\u003e,\n}\n\npub struct Field {\n    name: String,\n    instrument: String,\n    unit: String,\n}\n```\n\nTODO: The schema is structured according to the HydroVu data model,\nwhich is not general purpose.\n\n#### Template functions\n\n##### Group\n\nThe `group(by=..., in=...)` built-in groups any array of objects,\nreturning a map of arrays of objects.  It can be used to group fields\nby instrument name, for example.\n\n```\n{% for key, fields in group(by=\"name\",in=schema.fields) %}\n  Name is {{ key }}\n  {% for field in fields %}\n    Instrument is {{ field.instrument }}\n  {% endfor %}\n{% endfor %}\n```\n\n### Reduce\n\nUse the Reduce resource to aggregate timeseries into larger time\nbuckets.  Each collection's datasets are synthesized, expanding the\ninput wildcard (e.g., `.../*/...`) to the output placeholder (e.g.,\n`output-$0`).\n\nMultiple datasets may be listed within a collection, which must not\ngenerate overlapping output names.\n\n```\napiVersion: duckpond/v1\nkind: Reduce\nname: downsampled\ndesc: Downsampled datasets\nspec:\n  collections:\n  - name: single_instrument\n    resolutions: [1h, 2h, 4h, 12h, 24h]\n    datasets:\n    - in_pattern: \"/Combine/noyodata/*/combine\"\n      out_pattern: \"reduce-$0\"\n      columns:\n      - \"AT500_Bottom.DO.mg/L\"\n      - \"AT500_Surface.DO.mg/L\"\n```\n\n### Scribble\n\nSynthetic data generator for testing.\n\n```\napiVersion: github.com/jmacd/duckpond/v1\nkind: Scribble\nname: first-scribble\ndesc: Test data generator\nspec:\n  count_min: 5\n  count_max: 10\n  probs:\n    tree: 0.05\n    table: 0.4\n```\n\n## Usage\n\n### Init\n\nTo initialize a new pond in the current working directory or `$POND`,\nif set.  The pond directory is named \".pond\".  To create a new pond:\n\n```\nduckpond init\n```\n\n### Apply\n\nTo apply a resource definition, such as to create a new temporal data\nset.  For example:\n\n```\nduckpond apply -f noyo.yaml\n```\n\n### Run\n\nFetches new data from registered resources.  For example:\n\n```\nduckpond run\n```\n\n### Check\n\nDetermines whether expected files are present in the pond and various\nother consistency checks.  WIP: Simply prints the unexpected files.\n\n```\nduckpond check\n```\n\n### List\n\nProduces a directory listing.  Accepts shell wildcards.\n\n```\nduckpond list PATTERN\n```\n\n### Cat\n\nWrites a file to the standard output.\n\n```\nduckpond cat PATH\n```\n\n### Export\n\nWrites a sert of matching files to corresponding paths in the host\nfile system from one or more patterns.\n\n```\nduckpond export -d OUTPUT_DIR -p PATTERN [-p PATTERN ...] --temporal=year,month\n```\n\nIf the file is tabular and the `--temporal` flag is set , data will be\nexported in date-partitioned Parquet files.  The `--temporal` argument\ndetermines the partition keys for the output (which must include\n`year`).\n\nThe set of files exported by each pattern are placed into the\n`Template` context object, under the `export` key, making it possible\nfor exported templates to refer to exported files. For each wildcard\nin the export pattern, a nested map is built for the captured\nvariable.  If a pattern `/var/*/data/*` matched a path\n`/var/log/data/messages`, the `export` context would include a list of\ngenerated files, for example, like this:\n\n```\n{\n  \"log\": {\n    \"messages\": [\n  \t  {\n  \t\t\"file\": \"log/messages/year=2024/month=1/data_01.parquet\"\n\t    \"start_time\": 1234,\n\t    \"end_time\": 5678,\n\t  },\n  \t  ...\n\t],\n  }\n}\n```\n\nTODO: This example belongs with `Template`. Also document `args`, the \nmatching wildcard variables.\n\n## Configuration template expansion\n\nConfiguration values that are String typed have template expansion applied,\nmeaning that a line of configuration such as:\n\n```\nproperty: \"{{ variable }}\"\n```\n\ncan be configured during `duckpond apply`.  As an special case, the\nTemplate resource's `template` field itself is not expanded.  For example,\n\n```\nduckpond apply -f config.yaml -v variable=value\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjmacd%2Fduckpond","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fjmacd%2Fduckpond","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fjmacd%2Fduckpond/lists"}