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metreeca/qest

@metreeca/qest

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Minimalist foundations for client-driven, queryable REST/JSON APIs.

@metreeca/qest standardizes critical capabilities that vanilla REST/JSON APIs typically lack or implement in ad‑hoc, non‑portable ways:

  • Client-driven — clients specify what they need, retrieving complex envelopes in a single call
  • Queryable — advanced filtering and aggregation, supporting faceted search and analytics

Developers seek these features in frameworks like GraphQL; @metreeca/qest brings them to REST/JSON, achieving:

  • Familiar patterns — standard REST and JSON conventions, no new paradigms to learn
  • Simple clients — no specialized libraries, preprocessors, or code generators
  • Automated servers — model-driven development, dramatically reducing implementation effort
  • Standard caching — compatibility with CDNs and browser caches using standard GET requests
  • URL-based versioning — standard REST versioning without field deprecation complexity

Installation

npm install @metreeca/qest

Warning

TypeScript consumers must use "moduleResolution": "nodenext"/"node16"/"bundler" in tsconfig.json. The legacy "node" resolver is not supported.

Usage

Note

This section introduces essential concepts; for complete coverage, see the API reference:

@metreeca/qest types define payload semantics and formats for standard REST operations:

Method Type Description
GET Resource Resource retrieval
GET Query Client-driven resource retrieval
POST Resource Resource creation
PUT Resource Complete resource state update
PATCH Patch Partial resource state update
DELETE IRI Resource deletion

Resources and Patches

A Resource is a property map describing data returned by a REST endpoint, with optional links to other endpoints:

GET https://data.example.com/products/123
{
  "id": "https://data.example.com/products/123",
  "name": "Widget",
  "category": "Electronics",
  "tags": [
    "gadget",
    "featured"
  ],
  "vendor": "https://data.example.com/vendors/456",
  "price": 99.99,
  "inStock": true
}

The same format is used for complete resource updates:

PUT https://data.example.com/products/123
({
    "name": "Widget",
    "category": "Electronics",
    "tags": ["gadget", "premium"],
    "vendor": "https://data.example.com/vendors/456",
    "price": 79.99
    // inStock                     // not included → deleted
})

A Patch describes partial updates with the same effect:

PATCH https://data.example.com/products/123
({
    "tags": ["gadget", "premium"], // updated
    "price": 79.99,                // updated
    "inStock": null                // deleted
})

Properties set to null are deleted; properties not included are unchanged.

Client-Driven Retrieval

A Query is a declarative specification that controls how resources are retrieved: which properties to include and how deeply to expand linked resources. For collections, queries also support filtering, sorting, pagination, and computed projections including aggregates supporting faceted search and analytics.

GET https://data.example.com/products/?<query>

where <query> is the following URL-encoded JSON:

({
    "items": [
        {
            "id": "",
            "name": "",
            "price": 0,
            "vendor": {
                "id": "",
                "name": ""
            },
            ">=price": 50,     // filter: price ≥ 50
            "<=price": 150,    // filter: price ≤ 150
            "^price": "asc",   // sort: by price ascending
            "#": 25            // limit: 25 results
        }
    ]
})

A single call returns exactly what the client requested:

  • projected: product id, name, price
  • expanded: linked vendor with only id and name (not its full state)
  • filtered: price between 50 and 150
  • sorted: by price ascending
  • paginated: up to 25 results

Expansions and nested queries can be arbitrarily deep. No over-fetching of unwanted fields, no under-fetching requiring additional calls to resolve linked resources:

{
  "items": [
    {
      "id": "https://data.example.com/products/456",
      "name": "Gadget",
      "price": 59.99,
      "vendor": {
        "id": "https://data.example.com/vendors/145",
        "name": "Acme"
      }
    },
    {
      "id": "https://data.example.com/products/123",
      "name": "Widget",
      "price": 99.99,
      "vendor": {
        "id": "https://data.example.com/vendors/145",
        "name": "Acme"
      }
    },
    {
      "id": "https://data.example.com/products/789",
      "name": "Gizmo",
      "price": 129.99,
      "vendor": {
        "id": "https://data.example.com/vendors/236",
        "name": "Globex"
      }
    }
  ]
}

This is the core contribution of @metreeca/qest: vanilla REST/JSON APIs lack a standard way for clients to control retrieval, forcing them to accept fixed server responses or rely on ad-hoc query parameters. The Query model fills this gap, giving clients precise control over responses while remaining fully compatible with standard HTTP caching.

Important

Client-driven retrieval is fully optional. When clients don't provide a query, servers may provide a default one, typically derived from the underlying data model. This preserves standard REST/JSON behavior while enabling advanced retrieval capabilities when needed.

Integrated Ecosystem

Important

@metreeca/qest defines data types only; applications are absolutely free to handle validation, storage, and publishing as they see fit.

But @metreeca/qest is also the foundation of an integrated ecosystem for rapid application development, turning those same types into a complete model-driven stack:

Package Description
@metreeca/qest Data types for client-driven, queryable REST/JSON APIs
@metreeca/blue (upcoming) Shape-based validation for resources, patches, and queries
@metreeca/keep (upcoming) Shape-driven storage across various backends
@metreeca/gate (upcoming) Shape-driven REST/JSON API publishing

JSON-LD Interoperability

@metreeca/qest is built on a controlled subset of JSON-LD (JSON for Linked Data), a W3C standard that extends JSON with web identifiers (IRIs). This enables property names and values to reference shared vocabularies, giving data a precise, machine-readable meaning that survives when combined with data from other sources — a capability at the heart of the Web Data Activity (Semantic Web) and modern knowledge graphs.

The subset is designed to feel like plain idiomatic JSON, letting JavaScript developers work with linked data using familiar REST/JSON patterns without mastering JSON-LD technicalities, while retaining full compatibility with standard JSON-LD processors.

The JSON-LD subset is defined by the following constraints:

  • only the compacted document form is supported, using short property names and nested objects just like regular JSON

  • property names (JSON-LD terms) are restricted to ECMAScript identifiers, enabling property access with dot notation; this excludes JSON-LD keywords (@id, @type, etc.), blank node identifiers (_:), and arbitrary property names; mapping from property names to IRIs and keywords may still be managed by an application-provided @context object

  • values are native JSON primitives (boolean, number, string) without support for typed literals with arbitrary datatypes; property-specific datatype coercion may still be handled by an application-provided @context object

  • JSON-LD @language containers, don't support @none keys for plain literals; for mixed non-localized/localized content use string | Dictionary union types or zxx tags

Support

  • open an issue to report a problem or to suggest a new feature
  • start a discussion to ask a how-to question or to share an idea

License

This project is licensed under the Apache 2.0 License – see LICENSE file for details.

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