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link=\"https://github.com/riboseinc/structured_csv/actions/workflows/main.yml\"]\n\n== Purpose\n\nThe `structured_csv_to_yaml` script converts a \"`Structured CSV`\" file into a YAML file.\n\nWhen you have data of a yet-undefined data structure, it is useful to manage\nthem inside a CSV file which can be viewed and edited by a CSV editor,\nsuch as Excel.\n\nThis is extremely useful in developing a normalized structure for such data,\nas you can ensure that the existing data can be normalized according to a\ndefined structure.\n\nUltimately, the data is to be meant to exported to a YAML file.\n\nThis script supports UTF-8 CSV files.\n\nNOTE: This was originally developed to create over 50 normalized data models for ITU Operational Bulletin data. See https://github.com/ituob/ for more details.\n\n\n== Installation\n\nAdd this line to your application's `Gemfile`:\n\n[source,ruby]\n----\ngem 'structured_csv'\n----\n\nand then run:\n\n[source,sh]\n----\nbundle install\n----\n\nOr install it without a `Gemfile`:\n\n[source,sh]\n----\ngem install structured_csv\n----\n\n\n== Usage\n\n[source,sh]\n----\n$ structured_csv_to_yaml [input-file.csv]\n----\n\nWhere,\n\n`input-file.csv`:: is the input CSV file, the output will be named as `input-file.yaml`.\n\n\n== Details\n\nA Structured CSV file has these properties:\n\nTwo structured sections. A section is defined by the first column on an otherwise empty row that is either the first row or a row preceded by an empty row. Two section types are allowed: `METADATA` and `DATA`.\n\nThe `METADATA` section has values organized like key-value pairs:\n\n* Column 1 is the name of key\n* Column 2 is the value\n\nThe `key` can be a normal string or namespaced:\n\n* `foobar`, this maps to the YAML key `foobar:`\n\n* `foo.bar.boo`, this maps to the YAML structure: +\n+\n[source,yaml]\n----\nfoo:\n  bar:\n    boo:\n----\n\nA typical YAML output is like:\n\n[source,yaml]\n----\n---\nmetadata:\n  locale:\n    bar:\n      en: beef\n      fr: boeuf\n      jp: 牛肉\ndata:\n  foo:\n    bar:\n    ...\n----\n\n\n\nA sample METADATA section looks like this table:\n\n[cols,\"a,a\"]\n|===\n|METADATA |\n|locale.bar.en | beef\n|locale.bar.fr | boeuf\n|locale.bar.jp | 牛肉\n|===\n\nAnd generates this YAML:\n\n[source,yaml]\n----\n---\nmetadata:\n  locale:\n    bar:\n      en: beef\n      fr: boeuf\n      jp: 牛肉\n----\n\n\nThe `DATA` section has values organized in a table form. The first row is the header row.\nThe first column is assumed to be the key.\n\n\nA sample DATA section looks like this table:\n\n[cols,\"a,a,a,a\"]\n|===\n|DATA | | |\n|foo.bar.en | foo.bar.fr | foo.bar.jp | description\n|beef | boeuf | 牛肉 | Yummy!\n|pork | porc | 豚肉 | Delicious!\n|===\n\nBy default, this table generates this YAML format:\n\n[source,yaml]\n----\n---\ndata:\n  beef:\n    foo:\n      bar:\n        en: beef\n        fr: boeuf\n        jp: 牛肉\n    description: Yummy!\n  pork:\n    foo:\n      bar:\n        en: pork\n        fr: porc\n        jp: 豚肉\n    description: Delicious!\n  ...\n----\n\nIn cases where there is no DATA key, you have to specify the `type=array` to generate an array:\n\n[cols,\"a,a,a,a\"]\n|===\n|DATA | type=array | |\n|foo.bar.en | foo.bar.fr | foo.bar.jp | description\n|beef | boeuf | 牛肉 | Yummy!\n|pork | porc | 豚肉 | Delicious!\n|===\n\n[source,yaml]\n----\n---\ndata:\n  - foo:\n      bar:\n        en: beef\n        fr: boeuf\n        jp: 牛肉\n    description: Yummy!\n  - foo:\n      bar:\n        en: pork\n        fr: porc\n        jp: 豚肉\n    description: Delicious!\n  ...\n----\n\n\nYou are also allowed to specify the data types of columns. 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