Strapi-plugin-fuzzy-search

Register a weighted fuzzy search endpoint for Strapi Headless CMS you can add your content types to in no time.

Uses fuzzysort under the hood: Simple, quick and easy. No need to worry about setting up an instance for a complex search engine.

Table of Contents

• Roadmap 🏗️
• Requirements
• Installation
  • Options/Config
    • General Options
    • Fuzzysort Options
    • Full Example config
  • A note on performance:
• Usage
  • Basic Search
    • Example Requests
      • REST
      • GraphQl
    • Example Responses
      • REST
      • GraphQl
  • Pagination
    • REST
    • GraphQL
  • Filter by Content Type (REST)
• Why use fuzzysort and not something like Fuse.js?
• Found a bug?
• Contributors ✨

Roadmap 🏗️

• Return indices/highlights of matches
• Pass configuration as query params/args
  • Configure fuzzysort through params/args per content type
  • Allow default Strapi filters
• Support Population

Requirements

Strapi Version v4.x.x

Installation

Enable the fuzzy-search plugin in the ./config/plugins.js of your Strapi project.

Make sure to set the appropriate permissions for the search route in the Permissions tab of the Users & Permission Plugin for the role to be able to access the search route.

Options/Config

Mandatory settings are marked with *.

General Options

The plugin requires several configurations to be set in the .config/plugins.js file of your Strapi project to work.

Fuzzysort Options

The fuzzysortOptions allow for some finetuning of fuzzysorts searching algorithm to your needs.

Full Example config

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module.exports = ({ env }) => ({
  // ...

  "fuzzy-search": {
    enabled: true,
    config: {
      contentTypes: [
        {
          uid: "api::author.author",
          modelName: "author",
          transliterate: true,
          queryConstraints: {
            where: {
              $and: [
                {
                  publishedAt: { $notNull: true },
                },
              ],
            },
          },
          fuzzysortOptions: {
            characterLimit: 300,
            threshold: -600,
            limit: 10,
            keys: [
              {
                name: "name",
                weight: 100,
              },
              {
                name: "description",
                weight: -100,
              },
            ],
          },
        },
        {
          uid: "api::book.book",
          modelName: "book",
          fuzzysortOptions: {
            characterLimit: 500,
            keys: [
              {
                name: "title",
                weight: 200,
              },
              {
                name: "description",
                weight: -200,
              },
            ],
          },
        },
      ],
    },
  },

  // ...
});

A note on performance:

A high characterLimit, limit, a low threshold (the lower the value the more matches) as well as setting transliterate: true all hamper the performance of the search algorithm. We recommend that you start out with a characterLimit: 500, threshold: -1000, limit: 15 and work your way from there. The characterLimit especially can be quite delicate, so make sure to test every scenario when dialing in it's value.

Usage

Basic Search

Hitting the /api/fuzzy-search/search?query=<your-query-string> will return an array of matched entries for each content type registered in the config. If no match could be found an empty array will be returned. The endpoint accepts an optional locale=<your-locale> query as well.

Alternatively (and if the graphql plugin is installed), a search query is registered that accepts query: String! and locale: String (optional) as arguments.

IMPORTANT: Please not that in order to query for the locale of a content type, localization must be enabled for the content type.

Example Requests

REST

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await fetch(`${API_URL}/api/fuzzy-search/search?query=deresh&locale=en`);
// GET /api/fuzzy-search/search?query=deresh&locale=en

GraphQl

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query {
  search(query: "deresh", locale: "en") {
    authors {
      data {
        attributes {
          name
        }
      }
    }
    books {
      data {
        attributes {
          title
          description
        }
      }
    }
  }
}

Example Responses

IMPORTANT: Please note that as of now published as well as unpublished entries will be returned by default. Modify this behavior by setting up a queryConstraint in your config.

REST

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{
  "authors": [
    {
      "id": 1,
      "name": "Любко Дереш",
      "description": "As an author, Lyubko has had somewhat of a cult-like following among the younger generation in Ukraine since the appearance of his novel Cult at age eighteen, which was followed almost immediately by the publication of another novel, written in early high school.",
      "createdAt": "2022-05-05T13:08:19.312Z",
      "updatedAt": "2022-05-05T13:34:46.488Z",
      "publishedAt": "2022-05-05T13:22:17.310Z"
    }
  ],
  "books": [
    {
      "id": 1,
      "title": "Jacob's Head",
      "description": "Jacob’s Head by Lyubko Deresh is scheduled to be adapted into a movie in Ukraine in the near future.",
      "createdAt": "2022-05-05T13:08:43.816Z",
      "updatedAt": "2022-05-05T13:24:07.107Z",
      "publishedAt": "2022-05-05T13:22:23.764Z"
    }
  ]
}

GraphQl

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{
  "data": {
    "search": {
      "authors": {
        "data": [
          {
            "attributes": {
              "name": "Любко Дереш"
            }
          }
        ]
      },
      "books": {
        "data": [
          {
            "attributes": {
              "title": "Jacob's Head",
              "description": "Jacob’s Head by Lyubko Deresh is scheduled to be adapted into a movie in Ukraine in the near future."
            }
          }
        ]
      }
    }
  }
}

Pagination

REST

The endpoint accepts query parameters in line with Strapis pagination by page parameters. The difference being that the pagination is scoped for the content types individually.

Important: Please note that if pagination parameters are passed for a content type, it's data will now be available under the key data, whereas the pagination meta data can be found under the key meta.

Request:

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await fetch(`${API_URL}/api/fuzzy-search/search?query=deresh&pagination[authors][pageSize]=2&pagination[authors][page]=3`);
// GET /api/fuzzy-search/search?query=deresh&pagination[authors][pageSize]=2&pagination[authors][page]=3

Response:

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{
  "authors": [
    // ...
  ],
  "books": {
    "data": [
      // ...
    ],
    "meta": {
      "pagination": {
        "page": 3,
        "pageSize": 2,
        "total": 6,
        "pageCount": 3
      }
    }
  }
}

GraphQL

The endpoint accepts pagination arguments in line with Strapis pagination by page and pagination by offset parameters.

IMPORTANT: Please note that in line with Strapis defaults, pagination methods can not be mixed. Always use either page with pageSize or start with limit.

Request:

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search(query: "deresh") {
  books(pagination: { page: 3, pageSize: 2 }) {
    data {
      attributes {
        title
      }
    }
    meta {
      pagination {
        page
        pageSize
        pageCount
        total
      }
    }
  }
}

Response:

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{
  "data": {
    "search": {
      "books": {
        "data": [
          // ...
        ],
        "meta": {
          "pagination": {
            "page": 3,
            "pageSize": 2,
            "pageCount": 3,
            "total": 6
          }
        }
      }
    }
  }
}

Filter by Content Type (REST)

The REST-endpoint accepts an optional parameter to select only some content types the fuzzy search should run for.

Request:

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await fetch(`${API_URL}/api/fuzzy-search/search?query=deresh&filters[contentTypes]=books,authors`);
// GET /api/fuzzy-search/search?query=deresh&filters[contentTypes]=books

Response:

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{
  "authors": [
    // ...
  ],
  "books": [
    // ...
  ]
}

Why use fuzzysort and not something like Fuse.js?

While Fuse.js proofs to be an amazing library, it can yield unexpected results and what is to be perceived as "false positives" (by a human) when searching through longer strings. Fuzzysort aims to solve this problem by introducing the evaluation and scoring of exact matches. Since we had issues with Fuse.js and it's underlying algorithm, we opted for fuzzysearch to do the heavy lifting instead.

Found a bug?

If you found a bug or have any questions please submit an issue. If you think you found a way how to fix it, please feel free to create a pull request!

Contributors ✨

Thanks goes to these wonderful people (emoji key):

Felix Wagner 📖 🎨	wuestefeld 💻	Dominik 💻 📖 🤔 👀	Rotar Rares 💻	Nguyễn Hoàng Vũ 💻	Chris Michael 🐛	Luca Faccio 🐛
aomalik 🐛	Alfred Lau 🐛	Phil Gran 🐛	David Daza 📖	Andre Grossi 🐛

This project follows the all-contributors specification. Contributions of any kind welcome!