@spinque/query-api

Library to use the Spinque Query API in your JavaScript/TypeScript project.

The Spinque Query API is an HTTP API to retrieve search results for queries. Also check out the documentation of the Spinque Query API.

Table of contents

• Installing
• Documentation
• Usage
  • Defining queries
  • Fetching results
  • Fetching using custom HTTP-library
  • Authentication
  • Utility functions
  • Faceted search
  • Clustered search
  • Vanilla JavaScript

Installing

Using npm:

$ npm install @spinque/query-api

Note: when using this library with NodeJS, version >= 18 is expected for fetch support.

Documentation

Documentation for this library can be found here.

For documentation on the Spinque Query API itself, please see this.

Usage

Defining queries

Defining a single query:

import { Query } from "@spinque/query-api";

const query: Query = {
  endpoint: "movie_search",
  parameters: { terms: "call me" },
};

Fetching results

Fetching results for a single query using an instance of the Api class and its fetch method:

import { Api, Query } from "@spinque/query-api";

// Configure the API with workspace, configuration and API name
const api = new Api({
  workspace: "my-workspace",
  config: "default",
  api: "movies",
});

// Construct the query to fetch results for
const query: Query = {
  endpoint: "movie_search",
  parameters: { terms: "call me" },
};

try {
  // Fetch the 10 first results of the query
  const results = await api.fetch(query, { count: 10 });
} catch (error: any) {
  console.error(error);
}

You can also fetch other type of responses:

const statistics = await api.fetch(query, { count: 10 }, 'statistics');
const resultsWithCount = await api.fetch(query, { count: 10 }, 'results,count');

You can bring your own RequestInit for fetch:

const requestInit: RequestInit = {
  cache: 'no-cache'
};
const results = await api.fetch(query, { count: 10 }, 'results', requestInit);

Fetching using custom HTTP-library

Getting the URL for a request to fetch it using your own HTTP-library of preference:

import { urlFromQueries } from "@spinque/query-api/utils";

const apiConfig = {
  workspace: "my-workspace",
  config: "default",
  api: "movies",
};

const query: Query = {
  endpoint: "movie_search",
  parameters: { terms: "call me" },
};

const url = urlFromQueries(apiConfig, query, { count: 10, offset: 0 });

// Make the request here using `url`

Authentication

Some Spinque APIs require authentication using OAuth 2.0. The Client Credentials flow (for server applications) and PKCE flow (for browser applications) are provided by @spinque/query-api:

PKCE flow (for browser applications)

import { Api } from "@spinque/query-api";

const api = new Api({
  workspace: "my-workspace",
  config: "default",
  api: "movies",
  authentication: {
    type: "pkce",
    clientId: "abcdefghijklmnopqrstuvwxyz",
    callback: "https://my-domain.com/callback",
  },
});

const query = {
  endpoint: "movie",
  parameters: { id: "https://imdb.com/data/movie/tt0209144" },
};

const response = await api.fetch(queries, { count: 10, offset: 0 });

Note: the Client ID and Callback URL cannot yet be configured from Spinque Desk. Ask your system administrator to help you out.

Client Credentials flow (for server applications)

import { Api } from "@spinque/query-api";

const api = new Api({
  workspace: "my-workspace",
  config: "default",
  api: "movies",
  authentication: {
    type: "client-credentials",
    clientId: "abcdefghijklmnopqrstuvwxyz",
    clientSecret: "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ"
  },
});

const query: Query = {
  endpoint: "movie_search",
  parameters: { terms: "call me" },
};

const response = await api.fetch(queries);

The Client ID and Client Secret can be generated by creating a new System-to-System account in the Settings > Team Members section of Spinque Desk.

It is strongly recommended you use a token cache. @spinque/query-api will log a warning message if you don't use a token cache.

The implementation of the cache is up to you. An example implementation that uses the filesystem:

export const fileSystemTokenCache: TokenCache = {
  get: () => {
    try {
      const data = fs.readFileSync(TOKEN_CACHE_PATH, { encoding: 'utf8' });
      return JSON.parse(data);
    } catch (error) {
      return null;
    }
  },
  set: (accessToken, expires) => {
    try {
      const data = JSON.stringify({ accessToken, expires });
      return fs.writeFileSync(TOKEN_CACHE_PATH, data);
    } catch (e) {}
  },
};

Then during the creation of the API object:

const api = new Api({
  ...,
  authentication: {
    ...,
    tokenCache: fileSystemTokenCache
  },
});

Utility functions

Many utility functions are available for import under @spinque/query-api/utils.

• urlFromQueries, takes an ApiConfig object and an array of Query objects and returns a Spinque Query API request URL.
• pathFromQuery, takes a single Query and returns the path of its Spinque Query API URL.
• pathFromQueries, takes an array of Query objects and returns the path of their Spinque Query API URL.
• join, joints together URL parts into a valid URL.
• stringifyQueries, takes an array of Query objects and returns a string representation that can be used to e.g. store in the address baer.
• parseQueries, takes a string from stringifyQueries and tries to parse it into an array of Query objects.
• stringToTupleList, given a string, try to parse it as a tuple list (array of arrays of numbers or strings, and array of scores).
• tupleListToString, given a tuple list, return a string representation.
• ensureTupleList, takes a value (string, number, array of strings or numbers, or array of arrays of strings or numbers) and normalizes it into a tuple list.

See the documentation for a complete list.

Faceted search

Faceted search is a common pattern found in applications built on Spinque. This library provides a FacetedSearch to ease the interaction between queries in a faceted search setup.

The following example shows how a search endpoint 'movie_search' can be used in combination with facet endpoints 'genre' and 'director'.

import { Api, FacetedSearch } from "@spinque/query-api";

const query: Query = {
  endpoint: "movie_search",
  parameters: { query: "call me" },
};

const fs = new FacetedSearch(query);

fs.addFacet("genre", "multiple");
fs.addFacet("director", "single");

// Get results and facet options
let results = await api.fetch(fs.getResultsQuery());
let genreOptions = await api.fetch(fs.getFacetQuery("genre"));
let directorOptions = await api.fetch(fs.getFacetQuery("director"));

// Set the search query parameter (e.g. after the user has typed something)
fs.setParameter("query", "dia");

// Get updated results and options
results = await api.fetch(fs.getResultsQuery());
genreOptions = await api.fetch(fs.getFacetQuery("genre"));
directorOptions = await api.fetch(fs.getFacetQuery("director"));

// Select some facet options
fs.setFacetSelection("genre", [
  "https://imdb.com/data/Drama",
  "https://imdb.com/data/Biography",
]);
fs.setFacetSelection("director", "https://imdb.com/data/PabloLarrain");

// Get results again, now with facets applied
results = await api.fetch(fs.getResultsQuery());

Optionally, you can provide a Query for when the search parameters are empty.

...

const listQuery: Query = { endpoint: 'movies' };

const fs = new FacetedSearch(query, listQuery);

Note that the exact same behavior can also be achieved without the FacetedSearch class (though it's more involved). The following two sections produce equal results:

With FacetedSearch:

const query: Query = {
  endpoint: "movie_search",
  parameters: { query: "call me" },
};

const fs = new FacetedSearch(query);

fs.addFacet("genre", "multiple");
fs.addFacet("director", "single");

let results = await api.fetch(fs.getResultsQuery());
let genreOptions = await api.fetch(fs.getFacetQuery("genre"));
let directorOptions = await api.fetch(fs.getFacetQuery("director"));

fs.setParameter("query", "dia");

results = await api.fetch(fs.getResultsQuery());
genreOptions = await api.fetch(fs.getFacetQuery("genre"));
directorOptions = await api.fetch(fs.getFacetQuery("director"));

fs.setFacetSelection("genre", [
  "https://imdb.com/data/Drama",
  "https://imdb.com/data/Biography",
]);

results = await api.fetch(fs.getResultsQuery());

Without FacetedSearch:

const query: Query = {
  endpoint: "movie_search",
  parameters: { query: "call me" },
};

const genreOptionsQuery: Query = { endpoint: "genre" };
const genreFilterQuery: Query = {
  endpoint: "genre:FILTER",
  parameters: { value: undefined },
};

const directorOptionsQuery: Query = { endpoint: "director" };
const directorFilterQuery: Query = {
  endpoint: "director:FILTER",
  parameters: { value: undefined },
};

let resultsQuery = [query];
if (genreFilterQuery.parameters.value) {
  resultsQuery.push(genreFilterQuery);
}
if (directorFilterQuery.parameters.value) {
  resultsQuery.push(directorFilterQuery);
}

let results = await api.fetch(resultsQuery);
let genreOptions = await api.fetch([...resultsQuery, genreOptionsQuery]);
let directorOptions = await api.fetch([...resultsQuery, directorOptionsQuery]);

query.parameters.query = "dia";

let resultsQuery = [query];
if (genreFilterQuery.parameters.value) {
  resultsQuery.push(genreFilterQuery);
}
if (directorFilterQuery.parameters.value) {
  resultsQuery.push(directorFilterQuery);
}

results = await api.fetch(resultsQuery);
let genreOptions = await api.fetch([...resultsQuery, genreOptionsQuery]);
let directorOptions = await api.fetch([...resultsQuery, directorOptionsQuery]);

genreFilterQuery.parameters.value = tupleListToString([
  "https://imdb.com/data/Drama",
  "https://imdb.com/data/Biography",
]);

let resultsQuery = [query];
if (genreFilterQuery.parameters.value) {
  resultsQuery.push(genreFilterQuery);
}
if (directorFilterQuery.parameters.value) {
  resultsQuery.push(directorFilterQuery);
}

results = await api.fetch(resultsQuery);

Clustered search

Another common pattern in application built on Spinque is clustered search. A group of results (of a certain class) is positioned in the result list. Think of the group of images that's often found in your Google results.

An endpoint with clustered search, will return an item of type rdfs:Class where a cluster should be placed. This item represents the cluster but it does not contain the clustered items themselves yet. Encountering it means your application has to fetch the clustered items next. The identifier of this representative item will be the class of the cluster, for example https://schema.org/Photograph. This can be used to fetch the cluster contents. Note: this is an opinionated convention that you could choose to diverge from.

This is what the response of an endpoint with clustered search could look like. Note: results at ranks 2 and 4 represent clusters, the rest do not.

{
  "count": 5,
  "offset": 0,
  "type": ["OBJ"],
  "items": [
    {
      "probability": 1,
      "rank": 1,
      "tuple": [
        {
          "id": "http://example.org/1",
          "class": ["https://schema.org/Thing"],
          "attributes": { "http://example.org/attribute": "value" }
        }
      ]
    },
    {
      "probability": 0.9,
      "rank": 2,
      "tuple": [
        {
          "id": "https://schema.org/Photograph",
          "class": ["http://www.w3.org/2000/01/rdf-schema#Class"]
        }
      ]
    },
    {
      "probability": 0.8,
      "rank": 3,
      "tuple": [
        {
          "id": "http://example.org/2",
          "class": ["https://schema.org/Thing"],
          "attributes": { "http://example.org/attribute": "value" }
        }
      ]
    },
    {
      "probability": 0.7,
      "rank": 4,
      "tuple": [
        {
          "id": "https://schema.org/Person",
          "class": ["http://www.w3.org/2000/01/rdf-schema#Class"]
        }
      ]
    },
    {
      "probability": 0.6,
      "rank": 5,
      "tuple": [
        {
          "id": "http://example.org/3",
          "class": ["https://schema.org/Thing"],
          "attributes": { "http://example.org/attribute": "value" }
        }
      ]
    }
  ]
}

For the clusters at rank 2 and 4, the application requests the contents from the Spinque API.

This library provides some tools to help build this pattern:

• The getClusters function, that identifies clusters in search results.
• The isCluster function, that returns whether an item is a cluster.

An example of a clustered search implementation using these functions:

const api = new Api({
  workspace: "demo",
  config: "default",
  api: "demo",
});

const response = await api.fetch({
  endpoint: "search",
  parameters: { query: "utrecht" },
});

// At this stage, the normal results can already be rendered. The clusters are known but their content not yet, so
// a placeholder or loading indicator should be shown instead.

// Dummy rendering loop:
for (let item of response.items) {
  if (isCluster(item)) {
    // show placeholder for a cluster
  } else {
    // show the full item
  }
}

// Get the clusters in the response and load their contents
const clusters = getClusters(response);

// Map all clusters to a request for their contents using `api.fetch`
const clusterRequests = clusters.map((cluster) =>
  api.fetch < [SpinqueResultObject] > (cluster.query)
);

// Await for the responses to all requests
// Note: it's possible to postpone fetching cluster results until the cluster is scrolled into view
const clusterResponses = await Promise.all(clusterRequests);

for (let [index, cluster] of clusterResponses.entries()) {
  // Replace placeholder with clustered items
}

// Note: more cluster items could be loaded if the user indicates interest

Vanilla JavaScript

This library can also be used without using TypeScript:

const sqa = require("@spinque/query-api");

const api = new sqa.Api({
  workspace: "my-workspace",
  api: "movies",
});

const query = {
  endpoint: "search",
  parameters: { term: "utrecht" },
};

try {
  const results = await api.fetch(query);
  console.log(results);
} catch (error) {
  console.log(error);
}