arcform 0.2.1

Local-first data pipeline engine for analytical workflows
Documentation 
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{
  "registry_commit": "80bed7b173cd",
  "probed": "2026-10-14",
  "platforms": ["linux_amd64", "osx_arm64"],
  "extensions": [
    {
      "name": "dta",
      "licence": "MIT",
      "repository": "codedthinking/duckdb-dta",
      "duckdb_versions": ["v1.5.6"],
      "proof": "read a Stata file; write one and read it back"
    },
    {
      "name": "finetype",
      "licence": "MIT",
      "repository": "meridian-online/finetype",
      "duckdb_versions": ["v1.5.6"],
      "proof": "the semantic type of a column and of a value is inferred from what it holds"
    },
    {
      "name": "h3",
      "licence": "Apache-2.0",
      "repository": "isaacbrodsky/h3-duckdb",
      "duckdb_versions": ["v1.5.6"],
      "proof": "the hexagonal cell for a point"
    },
    {
      "name": "http_client",
      "licence": "MIT",
      "repository": "query-farm/httpclient",
      "duckdb_versions": ["v1.5.6"],
      "proof": "an HTTP GET returning status and body"
    },
    {
      "name": "minijinja",
      "licence": "Apache-2.0",
      "repository": "query-farm/minijinja",
      "duckdb_versions": ["v1.5.6"],
      "proof": "a template is rendered once for each row and once over all of them"
    },
    {
      "name": "mlpack",
      "licence": "MIT",
      "repository": "eddelbuettel/duckdb-mlpack",
      "duckdb_versions": ["v1.5.6"],
      "proof": "train a random forest, store it and score new rows; a logistic regression; k-means"
    },
    {
      "name": "onager",
      "licence": "MIT OR Apache-2.0",
      "repository": "CogitatorTech/onager",
      "duckdb_versions": ["v1.5.6"],
      "proof": "shortest paths and components from an edge table"
    },
    {
      "name": "rapidfuzz",
      "licence": "MIT",
      "repository": "query-farm/rapidfuzz",
      "duckdb_versions": ["v1.5.6"],
      "proof": "a token-sort ratio between two strings"
    },
    {
      "name": "splink_udfs",
      "licence": "MIT",
      "repository": "moj-analytical-services/splink_udfs",
      "duckdb_versions": ["v1.5.6"],
      "proof": "names are blocked by the soundex of the surname and compared without diacritics"
    },
    {
      "name": "stats_duck",
      "licence": "Apache-2.0",
      "repository": "KoliStat/the-stats-duck",
      "duckdb_versions": ["v1.5.6"],
      "proof": "a two-sample t-test"
    },
    {
      "name": "stochastic",
      "licence": "Apache-2.0",
      "repository": "query-farm/stochastic",
      "duckdb_versions": ["v1.5.6"],
      "proof": "the normal distribution at its known points"
    },
    {
      "name": "subtoken",
      "licence": "MIT",
      "repository": "meridian-online/subtoken",
      "duckdb_versions": ["v1.5.6"],
      "proof": "embed text and rank by cosine similarity"
    },
    {
      "name": "textplot",
      "licence": "Apache-2.0",
      "repository": "query-farm/textplot",
      "duckdb_versions": ["v1.5.6"],
      "proof": "a text plot from SQL"
    },
    {
      "name": "us_address_standardizer",
      "licence": "MIT",
      "repository": "ericmanning/duckdb-address-standardizer",
      "duckdb_versions": ["v1.5.6"],
      "proof": "a US address parsed into its parts"
    },
    {
      "name": "webbed",
      "licence": "MIT",
      "repository": "teaguesterling/duckdb_webbed",
      "duckdb_versions": ["v1.5.6"],
      "proof": "parse XML into rows; write rows as XML"
    },
    {
      "name": "zipfs",
      "licence": "MIT",
      "repository": "isaacbrodsky/duckdb-zipfs",
      "duckdb_versions": ["v1.5.6"],
      "proof": "read a file inside a zip archive"
    }
  ]
}