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.
Before diving into the various processing functions usage, here are some must-know design choices of this library.
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.
Here is a example usage of the [Meta] that may come in handy when using
this library.
```rust use locspan::Meta;
// build a value associated with its metadata. let valuewithmetadata = Meta("value", "metadata");
// get a reference to the value. let value = valuewithmetadata.value();
// get a reference to the metadata. let metadata = valuewithmetadata.metadata();
// deconstruct. let Meta(value, metadata) = valuewithmetadata; ```
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.
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:
```rust
use staticiref::iri;
use rdftypes::IriVocabularyMut;
use contextual::WithContext;
let mut vocabulary: rdftypes::IndexVocabulary = rdftypes::IndexVocabulary::new(); let i = vocabulary.insert(iri!("https://docs.rs/contextual")); let value = rdf_types::Subject::Iri(i);
println!("{}", value.with(&vocabulary)) ```
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 [ExpandedDocument]s, you may also
want to check out the [Object] type representing a JSON object.
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.
```rust use iref::IriBuf; use staticiref::iri; use locspan::Span; use jsonld::{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::
// Expand the "remote" document. let expanded = input .expand(&mut loader) .await .expect("expansion failed");
for object in expanded.intovalue() { if let Some(id) = object.id() { let name = object.asnode().unwrap() .getany(&iri!("http://xmlns.com/foaf/0.1/name")).unwrap() .asstr().unwrap();
println!("id: {id}");
println!("name: {name}");
} } ```
Here is another example using RemoteDocumentReference.
```rust use staticiref::iri; use jsonld::{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 = jsonld::FsLoader::default();
loader.mount(iri!("https://example.com/").toowned(), "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.
``rust
use rdf_types::{IriVocabularyMut, Subject};
use contextual::WithContext;
// Creates the vocabulary that will map eachrdftypes::vocabulary::Index
// to an actualIriBuf`.
let mut vocabulary: rdftypes::IndexVocabulary = rdf_types::IndexVocabulary::new();
let iriindex = vocabulary.insert(iri!("https://example.com/sample.jsonld")); let input = RemoteDocumentReference::iri(iriindex);
// 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.intovalue() { if let Some(id) = object.id() { let name = object.asnode().unwrap() .getany(&nameid).unwrap() .asvalue().unwrap() .asstr().unwrap();
println!("id: {}", id.with(&vocabulary));
println!("name: {name}");
} } ```
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:
- If you want to get a compact representation for an arbitrary remote
document, simply use the [JsonLdProcessor::compact]
(or [JsonLdProcessor::compact_with]) method.
- Otherwise to compact an [ExpandedDocument] you can use the
[Compact::compact] method.
Here is an example compaction an arbitrary [RemoteDocumentReference]
using [JsonLdProcessor::compact].
```rust use staticiref::iri; use jsonld::{JsonLdProcessor, Options, RemoteDocumentReference, syntax::Print};
let input = RemoteDocumentReference::iri(iri!("https://example.com/sample.jsonld").to_owned());
let context = RemoteDocumentReference::contextiri(iri!("https://example.com/context.jsonld").toowned());
// Use FsLoader to redirect any URL starting with https://example.com/ to
// the local example directory. No HTTP query.
let mut loader = jsonld::FsLoader::default();
loader.mount(iri!("https://example.com/").toowned(), "examples");
let compact = input .compact(context, &mut loader) .await .expect("compaction failed");
println!("output: {}", compact.pretty_print()); ```
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:
- If you want to get a compact representation for an arbitrary remote
document, simply use the [JsonLdProcessor::flatten]
(or [JsonLdProcessor::flatten_with]) method.
This will return a JSON-LD document.
- Otherwise to compact an [ExpandedDocument] you can use the
[Flatten::flatten] (or [Flatten::flatten_with]) method.
This will return the list of nodes as a [FlattenedDocument].
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.
Here is an example compaction an arbitrary [RemoteDocumentReference]
using [JsonLdProcessor::flatten].
```rust use staticiref::iri; use jsonld::{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 = jsonld::FsLoader::default();
loader.mount(iri!("https://example.com/").toowned(), "examples");
let mut generator = rdftypes::generator::Blank::new().withmetadata( // 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()); ```
Many thanks to Spruce for sponsoring this project!
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