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Salad is a schema language for describing JSON or YAML structuredlinked data documents. Salad schema describes rules forpreprocessing, structural validation, and hyperlink checking fordocuments described by a Salad schema. Salad supports rich datamodeling with inheritance, template specialization, objectidentifiers, object references, documentation generation, codegeneration, and transformation toRDF. Salad provides a bridgebetween document and record oriented data modeling and the SemanticWeb.

The Schema Salad library is Python 3.10+ only.

pip3 install schema_salad

If you intend to use the schema-salad-tool --codegen=python feature, pleaseinclude the [pycodegen] extra:

pip3 install schema_salad[pycodegen]

To install from source:

git clone https://github.com/common-workflow-language/schema_saladcd schema_saladpip3 install .# or pip3 install .[pycodegen] if needed

Schema salad can be used as a command line tool or imported as a Python module:

$ schema-salad-toolusage: schema-salad-tool [-h] [--rdf-serializer RDF_SERIALIZER] [--skip-schemas]                      [--strict-foreign-properties] [--print-jsonld-context]                      [--print-rdfs] [--print-avro] [--print-rdf] [--print-pre]                      [--print-index] [--print-metadata] [--print-inheritance-dot]                      [--print-fieldrefs-dot] [--codegen language] [--codegen-target CODEGEN_TARGET]                      [--codegen-examples directory] [--codegen-package dotted.package]                      [--codegen-copyright copyright_string] [--print-oneline]                      [--print-doc] [--strict | --non-strict]                      [--verbose | --quiet | --debug] [--only ONLY] [--redirect REDIRECT]                      [--brand BRAND] [--brandlink BRANDLINK] [--brandstyle BRANDSTYLE]                      [--brandinverse] [--primtype PRIMTYPE] [--version]                      [schema] [document]$ python>>> import schema_salad

Validate a schema:

$ schema-salad-tool myschema.yml

Validate a document using a schema:

$ schema-salad-tool myschema.yml mydocument.yml

Generate HTML documentation:

$ schema-salad-tool --print-doc myschema.yml > myschema.html$ # or$ schema-salad-doc myschema.yml > myschema.html

Get JSON-LD context:

$ schema-salad-tool --print-jsonld-context myschema.yml mydocument.yml

Convert a document to JSON-LD:

$ schema-salad-tool --print-pre myschema.yml mydocument.yml > mydocument.jsonld

Generate Python classes for loading/generating documents described by the schema(Requires the [pycodegen] extra):

$ schema-salad-tool --codegen=python myschema.yml > myschema.py

Display inheritance relationship between classes as a graphviz 'dot' file andrender as SVG:

$ schema-salad-tool --print-inheritance-dot myschema.yml | dot -Tsvg > myschema.svg

The examples in the tables below are helpful to see how to use the output of schema-salad-tool --codegenin different languages for loading and/or creating/editing/saving objects.

First set of examples is using theCWL v1.2 schema:

Second set of examples is for theGalaxy Workflow Format 2 schema:

Let's say you have a 'basket' record that can contain items measured either byweight or by count. Here's an example:

basket:  - product: bananas    price: 0.39    per: pound    weight: 1  - product: cucumbers    price: 0.79    per: item    count: 3

We want to validate that all the expected fields are present, themeasurement is known, and that "count" cannot be a fractional value.Here is an example schema to do that:

- name: Product  doc: |    The base type for a product.  This is an abstract type, so it    can't be used directly, but can be used to define other types.  type: record  abstract: true  fields:    product: string    price: float- name: ByWeight  doc: |    A product, sold by weight.  Products may be sold by pound or by    kilogram.  Weights may be fractional.  type: record  extends: Product  fields:    per:      type:        type: enum        symbols:          - pound          - kilogram      jsonldPredicate: '#per'    weight: float- name: ByCount  doc: |    A product, sold by count.  The count must be a integer value.  type: record  extends: Product  fields:    per:      type:        type: enum        symbols:          - item      jsonldPredicate: '#per'    count: int- name: Basket  doc: |    A basket of products.  The 'documentRoot' field indicates it is a    valid starting point for a document.  The 'basket' field will    validate subtypes of 'Product' (ByWeight and ByCount).  type: record  documentRoot: true  fields:    basket:      type:        type: array        items: Product

You can check the schema and document in schema_salad/tests/basket_schema.ymland schema_salad/tests/basket.yml:

$ schema-salad-tool basket_schema.yml basket.ymlDocument `basket.yml` is valid

See thespecification and themetaschema (salad schema for itself). For anexample application of Schema Salad see the Common WorkflowLanguage.

The JSON data model is an popular way to represent structured data. It isattractive because of it's relative simplicity and is a natural fit with thestandard types of many programming languages. However, this simplicity comesat the cost that basic JSON lacks expressive features useful for working withcomplex data structures and document formats, such as schemas, objectreferences, and namespaces.

JSON-LD is a W3C standard providing a way to describe how to interpret a JSONdocument as Linked Data by means of a "context". JSON-LD provides a powerfulsolution for representing object references and namespaces in JSON based onstandard web URIs, but is not itself a schema language. Without a schemaproviding a well defined structure, it is difficult to process an arbitraryJSON-LD document as idiomatic JSON because there are many ways to express thesame data that are logically equivalent but structurally distinct.

Several schema languages exist for describing and validating JSON data, such asJSON Schema and Apache Avro data serialization system, however noneunderstand linked data. As a result, to fully take advantage of JSON-LD tobuild the next generation of linked data applications, one must maintainseparate JSON schema, JSON-LD context, RDF schema, and human documentation,despite significant overlap of content and obvious need for these documents tostay synchronized.

Schema Salad is designed to address this gap. It provides a schema languageand processing rules for describing structured JSON content permitting URIresolution and strict document validation. The schema language supports linkeddata through annotations that describe the linked data interpretation of thecontent, enables generation of JSON-LD context and RDF schema, and productionof RDF triples by applying the JSON-LD context. The schema language alsoprovides for robust support of inline documentation.