# rdf-lens > Look into a dataset with RDF-Lens. Here the term Lens, is the same concept of Haskell lenses available in [this well known library](https://hackage.haskell.org/package/lens). Latest version **1.3.7** (published 2026-03-25) · MIT license · 0 weekly downloads ## Install ```sh npm install rdf-lens pnpm add rdf-lens yarn add rdf-lens bun add rdf-lens ``` ## Health **Score 60/100 (C)** — status: active. Positive: has types; esm support; no vulnerabilities; high quality score. Warnings: low downloads. ## Facts | | | |---|---| | Version | 1.3.7 | | Published | 2026-03-25 | | First published | 2023-09-13 | | Weekly downloads | 0 | | License | MIT | | TypeScript types | bundled | | Module format | ESM + CommonJS | | Dependencies | 3 | | Unpacked size | 102.5 KB | | Known vulnerabilities | 0 | | Install scripts | no | | Maintainers | ajuvercr | ## Links - npm: https://www.npmjs.com/package/rdf-lens - npm.io page: https://npm.io/package/rdf-lens ## Dependencies (3) - [@rdfjs/types](https://npm.io/package/@rdfjs/types.md) ^2.0.1 - [@treecg/types](https://npm.io/package/@treecg/types.md) ^0.4.6 - [rdf-data-factory](https://npm.io/package/rdf-data-factory.md) ^2.0.2 ## Recent versions - 1.3.7 (latest) — 2026-03-25 - 1.3.6 — 2025-08-14 - 1.3.5 — 2025-01-29 - 1.3.4 — 2025-01-23 - 1.3.3 — 2024-12-23 - 1.3.2 — 2024-12-23 - 1.3.1 — 2024-12-16 - 1.3.0 — 2024-08-28 - 1.2.9 — 2024-08-26 - 1.2.8 — 2024-05-15 - 1.2.7 — 2024-05-15 - 1.2.6 — 2024-04-25 - 1.2.5 — 2024-04-09 - 1.2.4 — 2024-04-09 - 1.2.3 — 2024-04-08 - … 11 more at https://npm.io/package/rdf-lens/versions ## README # RDF-Lens Look into a dataset with RDF-Lens. Here the term Lens, is the same concept of Haskell lenses available in [this well known library](https://hackage.haskell.org/package/lens). A lens looks at a point in a dataset, for RDF-Lens this usually is looking at a Term inside a store. Lenses can be combined to from a point, look furthur inside the dataset, as long as the types allow for it. Currently two lenses exist in RDF-Lens `BasicLens` and `BasicLensM` (M stands for Multiple: `BasicLensM` is a subclass of `BasicLens`). C stands for Container, a combination of the store and the current target. T stands for resulting type. `BasicLens` can be combined with `BasicLens` and will result in `BasicLens`. ## Examples ### Pred A very common Lens is created with `pred` and takes in a predicate term and returns `BasicLensM`. So it starts pointing inside the dataset and results in pointing to multiple things inside the dataset. Using the function `.thenFlat` another predicate can be chained to explore the dataset deper. ### Extracting data RDF-Lens tries to make it developer friendly and typed to extract data from a RDF store. This example shows how to extract a point with two coordinates from the data. ```typescript import { pred } from "rdf-lens"; import { DataFactory, Parser } from "n3"; const { namedNode } = DataFactory; const extractX = pred(namedNode("x")) // Follow predicate .one() // We expect only to find one term .map(({id}) => ({x: id.value})); // Map that term to a Json Object const extractY = pred(namedNode("y")) // Follow predicate .one() // We expect only to find one term .map(({id}) => ({y: id.value})); // Map that term to a Json Object const pointLens = extractX.and(extractY) // Combine both lenses .map(([{x}, {y}]) => ({x, y})); // Map them together to a point object const turtle = " 42; 43."; const quads = new Parser().parse(turtle); // Parser quads const point = pointLens.execute({id: namedNode("a"), quads}); // Execute the lens over the dataset ``` ### Extracting RDF list items Extracting point data is not very exciting, this example shows how to extract all items from a RDF List. ```typescript const RDFListElement = pred(RDF.first).one().and(pred(RDF.rest).one()); // RdfList is a Lens that takes in a Container pointing to a Term and returns a list of Terms const RdfList: BasicLens = new BasicLens((c) => { if (c.id.equals(RDF.nil)) { return []; } const [first, rest] = RDFListElement.execute(c); const els = RdfList.execute(rest); els.unshift(first.id); return els; }); ``` ### Extracting starting from shacl shapes Shacl shapes are used widely to constrain rdf data to some shape. With rdf-lens you can extract data starting from a shape to a plain old javascript object. The field names are defined by the `sh:name`, that is part of the `sh:property` object. This examples shows how to define and extract a point. ```turtle # The shacl shape for a point [] a sh:NodeShape; sh:targetClass ; # Derive a lens for js:Point sh:property [ sh:name "x"; # Field x sh:path ; # is found at path `js:x` sh:datatype xsd:integer; # and is an integer sh:maxCount 1; sh:minCount 1; ], [ sh:datatype xsd:integer; sh:path ; sh:name "y"; sh:maxCount 1; sh:minCount 1; ]. ``` ```turtle # Data that adheres to that shape a ; 5; 8. ``` Let's use this data to extract a point. ```typescript const shapes = extractShapes(shapeQuads); const quads = parseQuads(dataQuads); const lens = shapes.lenses["Point"]; // The lens that extracts a point const point = lens.execute({id: namedNode("MyPoint"), quads}); console.log(point); // { "x": 5, "y": 8 } ``` **Deep objects** are also supported, let's reuse the point shape to extract a line. ```turtle [] a sh:NodeShape; sh:targetClass ; sh:property [ sh:name "start"; // The start is a point sh:path ; sh:class ; sh:maxCount 1; sh:minCount 1; ], [ sh:name "end"; // The end is a point sh:path ; sh:class ; sh:maxCount 1; sh:minCount 1; ]. ``` Note: `sh:datatype` is used for literals, `sh:class` is used for objects. * `sh:minCount` tells rdf-lens that this property is required, and will fail to parse an object that does not adhere to the shape. * `sh:maxCount` tells rdf-lens whether or not to expect multiple objects. If this is not set or is bigger than 1, the Javascript object will have an array as its value. **Special implemented classes** Sometimes a plain old javascript objects is not enough, some special classes work out of the box. `@prefix rdfs: .` * `rdfl:CBD`: Provides a list of quads bounded by the cbd algorithm. * `rdfl:PathLens`: Parses a shacl Path and returns a Lens that resolves this path. * `rdfl:Context`: Provides a reference to the list of all data quads. * `rdfl:TypeExtract`: Extracts according to the `rdf:type` object (including class hierarchy), by using the shape that corresponds to that type. --- _Source: https://npm.io/package/rdf-lens · Machine-readable twin of the npm.io package page. Health data is recomputed on every publish._