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        "author": "Common workflow language working group",
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        "description": "|Linux Build Status| |Code coverage| |Documentation Status| |CII Best Practices|\n\n.. |Linux Build Status| image:: https://github.com/common-workflow-language/schema_salad/actions/workflows/ci-tests.yml/badge.svg?branch=main\n   :target: https://github.com/common-workflow-language/schema_salad/actions/workflows/ci-tests.yml\n.. |Code coverage| image:: https://codecov.io/gh/common-workflow-language/schema_salad/branch/main/graph/badge.svg\n   :target: https://codecov.io/gh/common-workflow-language/schema_salad\n.. |Documentation Status| image:: https://readthedocs.org/projects/schema-salad/badge/?version=latest\n   :target: https://schema-salad.readthedocs.io/en/latest/?badge=latest\n   :alt: Documentation Status\n.. |CII Best Practices| image:: https://bestpractices.coreinfrastructure.org/projects/1867/badge\n   :target: https://bestpractices.coreinfrastructure.org/projects/1867\n\nSchema Salad\n------------\n\nSalad is a schema language for describing JSON or YAML structured\nlinked data documents.  Salad schema describes rules for\npreprocessing, structural validation, and hyperlink checking for\ndocuments described by a Salad schema. Salad supports rich data\nmodeling with inheritance, template specialization, object\nidentifiers, object references, documentation generation, code\ngeneration, and transformation to RDF_. Salad provides a bridge\nbetween document and record oriented data modeling and the Semantic\nWeb.\n\nThe Schema Salad library is Python 3.7+ only.\n\nInstallation\n------------\n\n::\n\n   pip3 install schema_salad\n\nIf you intend to use the `schema-salad-tool --codegen=python` feature, please\ninclude the `[pycodegen]` extra::\n\n   pip3 install schema_salad[pycodegen]\n\nTo install from source::\n\n   git clone https://github.com/common-workflow-language/schema_salad\n   cd schema_salad\n   pip3 install .\n   # or pip3 install .[pycodegen] if needed\n\nCommands\n--------\n\nSchema salad can be used as a command line tool or imported as a Python module::\n\n   $ schema-salad-tool\n   usage: schema-salad-tool [-h] [--rdf-serializer RDF_SERIALIZER] [--skip-schemas]\n                         [--strict-foreign-properties] [--print-jsonld-context]\n                         [--print-rdfs] [--print-avro] [--print-rdf] [--print-pre]\n                         [--print-index] [--print-metadata] [--print-inheritance-dot]\n                         [--print-fieldrefs-dot] [--codegen language] [--codegen-target CODEGEN_TARGET]\n                         [--codegen-examples directory] [--codegen-package dotted.package]\n                         [--codegen-copyright copyright_string] [--print-oneline]\n                         [--print-doc] [--strict | --non-strict]\n                         [--verbose | --quiet | --debug] [--only ONLY] [--redirect REDIRECT]\n                         [--brand BRAND] [--brandlink BRANDLINK] [--brandstyle BRANDSTYLE]\n                         [--brandinverse] [--primtype PRIMTYPE] [--version]\n                         [schema] [document]\n\n   $ python\n   >>> import schema_salad\n\nValidate a schema::\n\n   $ schema-salad-tool myschema.yml\n\nValidate a document using a schema::\n\n   $ schema-salad-tool myschema.yml mydocument.yml\n\nGenerate HTML documentation::\n\n   $ schema-salad-tool --print-doc myschema.yml > myschema.html\n   $ # or\n   $ schema-salad-doc myschema.yml > myschema.html\n\nGet JSON-LD context::\n\n   $ schema-salad-tool --print-jsonld-context myschema.yml mydocument.yml\n\nConvert a document to JSON-LD::\n\n   $ schema-salad-tool --print-pre myschema.yml mydocument.yml > mydocument.jsonld\n\nGenerate Python classes for loading/generating documents described by the schema\n(Requires the `[pycodegen]` extra)::\n\n   $ schema-salad-tool --codegen=python myschema.yml > myschema.py\n\nDisplay inheritance relationship between classes as a graphviz 'dot' file and\nrender as SVG::\n\n   $ schema-salad-tool --print-inheritance-dot myschema.yml | dot -Tsvg > myschema.svg\n\n\nQuick Start\n-----------\n\nLet's say you have a 'basket' record that can contain items measured either by\nweight or by count.  Here's an example::\n\n   basket:\n     - product: bananas\n       price: 0.39\n       per: pound\n       weight: 1\n     - product: cucumbers\n       price: 0.79\n       per: item\n       count: 3\n\nWe want to validate that all the expected fields are present, the\nmeasurement is known, and that \"count\" cannot be a fractional value.\nHere is an example schema to do that::\n\n   - name: Product\n     doc: |\n       The base type for a product.  This is an abstract type, so it\n       can't be used directly, but can be used to define other types.\n     type: record\n     abstract: true\n     fields:\n       product: string\n       price: float\n\n   - name: ByWeight\n     doc: |\n       A product, sold by weight.  Products may be sold by pound or by\n       kilogram.  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The 'basket' field will\n       validate subtypes of 'Product' (ByWeight and ByCount).\n     type: record\n     documentRoot: true\n     fields:\n       basket:\n         type:\n           type: array\n           items: Product\n\nYou can check the schema and document in schema_salad/tests/basket_schema.yml\nand schema_salad/tests/basket.yml::\n\n   $ schema-salad-tool basket_schema.yml basket.yml\n   Document `basket.yml` is valid\n\n\nDocumentation\n-------------\n\nSee the specification_ and the metaschema_ (salad schema for itself).  For an\nexample application of Schema Salad see the Common Workflow Language_.\n\n\nRationale\n---------\n\nThe JSON data model is an popular way to represent structured data.  It is\nattractive because of it's relative simplicity and is a natural fit with the\nstandard types of many programming languages.  However, this simplicity comes\nat the cost that basic JSON lacks expressive features useful for working with\ncomplex data structures and document formats, such as schemas, object\nreferences, and namespaces.\n\nJSON-LD is a W3C standard providing a way to describe how to interpret a JSON\ndocument as Linked Data by means of a \"context\".  JSON-LD provides a powerful\nsolution for representing object references and namespaces in JSON based on\nstandard web URIs, but is not itself a schema language.  Without a schema\nproviding a well defined structure, it is difficult to process an arbitrary\nJSON-LD document as idiomatic JSON because there are many ways to express the\nsame data that are logically equivalent but structurally distinct.\n\nSeveral schema languages exist for describing and validating JSON data, such as\nJSON Schema and Apache Avro data serialization system, however none\nunderstand linked data.  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