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A JSON-LD implementation for Rust

CI Crate informations License Documentation

This crate is a Rust implementation of the JSON-LD data interchange format.

Linked Data (LD) is a World Wide Web Consortium (W3C) initiative built upon standard Web technologies to create an interrelated network of datasets across the Web. The JavaScript Object Notation (JSON) is a widely used, simple, unstructured data serialization format to describe data objects in a human readable way. JSON-LD brings these two technologies together, adding semantics to JSON to create a lightweight data serialization format that can organize data and help Web applications to inter-operate at a large scale.

Table of Contents

Design

Before diving into the various processing functions usage, here are some must-know design choices of this library.

Code mapping and metadata

One important feature of this library is the preservation of the code mapping information extracted from any source JSON document through the diverse transformation algorithms. This is done using:

  • The locspan parsing utility library that provides the Meta type associating a value to some metadata. The metadata is intended to be code mapping information, but you ultimately can decide what it is.
  • The json_syntax library that parse JSON documents while preserving the code mapping information using the Meta type.

This is particularly useful to provide error messages that can pinpoint the source of the error in the original source file.

Example

Here is a example usage of the Meta that may come in handy when using this library.

use locspan::Meta;

// build a value associated with its metadata.
let value_with_metadata = Meta("value", "metadata");

// get a reference to the value.
let value = value_with_metadata.value();

// get a reference to the metadata.
let metadata = value_with_metadata.metadata();

// deconstruct.
let Meta(value, metadata) = value_with_metadata;

IRIs and Blank Node Identifiers

This library gives you the opportunity to use any datatype you want to represent IRIs an Blank Node Identifiers. Most types have them parameterized. To avoid unnecessary allocations and expensive comparisons, it is highly recommended to use a cheap, lightweight datatype such as rdf_types::vocabulary::Index. This type will represent each distinct IRI/blank node identifier with a unique index. In this case a rdf_types::IndexVocabulary that maps each index back/to its original IRI/Blank identifier representation can be passed to every function.

You can also use your own index type, with your own rdf_types::Vocabulary implementation.

Displaying vocabulary-dependent values

Since using vocabularies separates IRIs and Blank ids from their textual representation, it complicates displaying data using them. Fortunately many types defined by json-ld implement the contextual::DisplayWithContext trait that allow displaying value with a "context", which here would be the vocabulary. By importing the contextual::WithContext which provides the with method you can display such value like this:

use static_iref::iri;
use rdf_types::IriVocabularyMut;
use contextual::WithContext;

let mut vocabulary: rdf_types::IndexVocabulary = rdf_types::IndexVocabulary::new();
let i = vocabulary.insert(iri!("https://docs.rs/contextual"));
let value = rdf_types::Subject::Iri(i);

println!("{}", value.with(&vocabulary))

Usage

The entry point for this library is the JsonLdProcessor trait that provides an access to all the JSON-LD transformation algorithms (context processing, expansion, compaction, etc.). If you want to explore and/or transform ExpandedDocuments, you may also want to check out the [Object] type representing a JSON object.

Expansion

If you want to expand a JSON-LD document, first describe the document to be expanded using either RemoteDocument or RemoteDocumentReference:

  • RemoteDocument wraps the JSON representation of the document alongside its remote URL.
  • RemoteDocumentReference may represent only an URL, letting some loader fetching the remote document by dereferencing the URL.

After that, you can simply use the JsonLdProcessor::expand function on the remote document.

Example

use iref::IriBuf;
use static_iref::iri;
use locspan::Span;
use json_ld::{JsonLdProcessor, Options, RemoteDocument, syntax::{Value, Parse}};

// Create a "remote" document by parsing a file manually.
let input = RemoteDocument::new(
  // We use `IriBuf` as IRI type.
  Some(iri!("https://example.com/sample.jsonld").to_owned()),

  // Optional content type.
  Some("application/ld+json".parse().unwrap()),
  
  // Parse the file.
  Value::parse_str(r#"
    {
      "@context": {
        "name": "http://xmlns.com/foaf/0.1/name"
      },
      "@id": "https://www.rust-lang.org",
      "name": "Rust Programming Language"
    }"#,
    |span| span // keep the source `Span` of each element as metadata.
  ).expect("unable to parse file")
);

// Use `NoLoader` as we won't need to load any remote document.
let mut loader = json_ld::NoLoader::<IriBuf, Span>::new();

// Expand the "remote" document.
let expanded = input
  .expand(&mut loader)
  .await
  .expect("expansion failed");

for object in expanded.into_value() {
  if let Some(id) = object.id() {
    let name = object.as_node().unwrap()
      .get_any(&iri!("http://xmlns.com/foaf/0.1/name")).unwrap()
      .as_str().unwrap();

    println!("id: {id}");
    println!("name: {name}");
  }
}

Here is another example using RemoteDocumentReference.

use static_iref::iri;
use json_ld::{JsonLdProcessor, Options, RemoteDocumentReference};

let input = RemoteDocumentReference::iri(iri!("https://example.com/sample.jsonld").to_owned());

// Use `FsLoader` to redirect any URL starting with `https://example.com/` to
// the local `example` directory. No HTTP query.
let mut loader = json_ld::FsLoader::default();
loader.mount(iri!("https://example.com/").to_owned(), "examples");

let expanded = input.expand(&mut loader)
  .await
  .expect("expansion failed");

Lastly, the same example replacing IriBuf with the lightweight rdf_types::vocabulary::Index type.

use rdf_types::{IriVocabularyMut, Subject};
use contextual::WithContext;
// Creates the vocabulary that will map each `rdf_types::vocabulary::Index`
// to an actual `IriBuf`.
let mut vocabulary: rdf_types::IndexVocabulary = rdf_types::IndexVocabulary::new();

let iri_index = vocabulary.insert(iri!("https://example.com/sample.jsonld"));
let input = RemoteDocumentReference::iri(iri_index);

// Use `FsLoader` to redirect any URL starting with `https://example.com/` to
// the local `example` directory. No HTTP query.
let mut loader = json_ld::FsLoader::default();
loader.mount(vocabulary.insert(iri!("https://example.com/")), "examples");

let expanded = input
  .expand_with(&mut vocabulary, &mut loader)
  .await
  .expect("expansion failed");

// `foaf:name` property identifier.
let name_id = Subject::Iri(vocabulary.insert(iri!("http://xmlns.com/foaf/0.1/name")));

for object in expanded.into_value() {
  if let Some(id) = object.id() {
    let name = object.as_node().unwrap()
      .get_any(&name_id).unwrap()
      .as_value().unwrap()
      .as_str().unwrap();

    println!("id: {}", id.with(&vocabulary));
    println!("name: {name}");
  }
}

Compaction

The JSON-LD Compaction is a transformation that consists in applying a context to a given JSON-LD document reducing its size. There are two ways to get a compact JSON-LD document with this library depending on your starting point:

Example

Here is an example compaction an arbitrary RemoteDocumentReference using JsonLdProcessor::compact.

use static_iref::iri;
use json_ld::{JsonLdProcessor, Options, RemoteDocumentReference, syntax::Print};

let input = RemoteDocumentReference::iri(iri!("https://example.com/sample.jsonld").to_owned());

let context = RemoteDocumentReference::context_iri(iri!("https://example.com/context.jsonld").to_owned());

// Use `FsLoader` to redirect any URL starting with `https://example.com/` to
// the local `example` directory. No HTTP query.
let mut loader = json_ld::FsLoader::default();
loader.mount(iri!("https://example.com/").to_owned(), "examples");

let compact = input
  .compact(context, &mut loader)
  .await
  .expect("compaction failed");

println!("output: {}", compact.pretty_print());

Flattening

The JSON-LD Flattening is a transformation that consists in moving nested nodes out. The result is a list of all the nodes declared in the document. There are two ways to flatten JSON-LD document with this library depending on your starting point:

Flattening requires assigning an identifier to nested anonymous nodes, which is why the flattening functions take an rdf_types::MetaGenerator as parameter. This generator is in charge of creating new fresh identifiers (with their metadata). The most common generator is rdf_types::generator::Blank that creates blank node identifiers.

Example

Here is an example compaction an arbitrary RemoteDocumentReference using JsonLdProcessor::flatten.

use static_iref::iri;
use json_ld::{JsonLdProcessor, Options, RemoteDocumentReference, syntax::Print};
use locspan::{Location, Span};

let input = RemoteDocumentReference::iri(iri!("https://example.com/sample.jsonld").to_owned());

// Use `FsLoader` to redirect any URL starting with `https://example.com/` to
// the local `example` directory. No HTTP query.
let mut loader = json_ld::FsLoader::default();
loader.mount(iri!("https://example.com/").to_owned(), "examples");

let mut generator = rdf_types::generator::Blank::new().with_metadata(
  // Each blank id will be associated to the document URL with a dummy span.
  Location::new(iri!("https://example.com/").to_owned(), Span::default())
);

let nodes = input
  .flatten(&mut generator, &mut loader)
  .await
  .expect("flattening failed");

println!("output: {}", nodes.pretty_print());

Sponsor

Many thanks to Spruce for sponsoring this project!

License

Licensed under either of

at your option.

Contribution

Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in the work by you, as defined in the Apache-2.0 license, shall be dual licensed as above, without any additional terms or conditions.

Dependencies

~4–12MB
~229K SLoC