Built-in search plugin

Built-in search plugin

The search plugin adds a search bar to the header, allowing users to search your documentation. It’s powered by lunr.js, a lightweight full-text search engine for the browser, elimininating the need for external services, and even works when building offline-capable documentation.

Objective

How it works

The plugin scans the generated HTML and builds a search index from all pages and sections by extracting the section titles and contents. It preserves some inline formatting like code blocks and lists, but removes all other formatting, so the search index is as small as possible.

When a user visits your site, the search index is shipped to the browser, indexed with lunr.js and made available for fast and simple querying – no server needed. This ensures that the search index is always up to date with your documentation, yielding accurate results.

When to use it

It’s generally recommended to use the plugin, as interactive search functionality is a vital part of every good documentation. Additionally, the plugin integrates perfectly with several of the other built-in plugins that Material for MkDocs offers:

Configuration

As with all built-in plugins, getting started with the search plugin is straightforward. Just add the following lines to mkdocs.yml, and your users will be able to search your documentation:

yaml
plugins:
  - search

The search plugin is built into Material for MkDocs and doesn’t need to be installed.

General

The following settings are available:


Use this setting to enable or disable the plugin when building your project. It’s normally not necessary to specify this setting, but if you want to disable the plugin, use:

yaml
plugins:
  - search:
      enabled: false

The following settings are available for search:


computed

Use this setting to specify the language of the search index, enabling stemming support for other languages than English. The default value is automatically computed from the site language, but can be explicitly set to another language or even multiple languages with:

Language support is provided by lunr languages, a collection of language-specific stemmers and stop words for lunr.js maintained by the Open Source community.


The following languages are currently supported by lunr languages:

If lunr languages doesn’t provide support for the selected site language, the plugin falls back to another language that yields the best stemming results. If you discover that the search results are not satisfactory, you can contribute to lunr languages by adding support for your language.


computed

Use this setting to specify the separator used to split words when building the search index on the client side. The default value is automatically computed from the site language, but can also be explicitly set to another value with:

yaml
plugins:
  - search:
      separator: '[\s\-,:!=\[\]()"/]+|(?!\b)(?=[A-Z][a-z])|\.(?!\d)|&[lg]t;'

Separators support positive and negative lookahead assertions, which allows for rather complex expressions that yield precise control over how words are split when building the search index.

Broken into its parts, this separator induces the following behavior:


computed experimental

Use this setting to specify the pipeline functions that are used to filter and expand tokens after tokenizing them with the [separator][config.separator] and before adding them to the search index. The default value is automatically computed from the site language, but can also be explicitly set with:

yaml
plugins:
  - search:
      pipeline:
        - stemmer
        - stopWordFilter
        - trimmer

The following pipeline functions can be used:

  • stemmer – Stem tokens to their root form, e.g. running to run

  • stopWordFilter – Filter common words according, e.g. a, the, etc.

  • trimmer – Trim whitespace from tokens

Segmentation

The plugin supports text segmentation of Chinese via jieba, a popular Chinese text segmentation library. Other languages like Japanese and Korean are currently segmented on the client side, but we’re considering to move this functionality into the plugin in the future.

The following settings are available for segmentation:


none experimental

Use this setting to specify a custom dictionary to be used by jieba for segmenting text, replacing the default dictionary. jieba comes with several dictionaries, which can be used with:

yaml
plugins:
  - search:
      jieba_dict: dict.txt

The following dictionaries are provided by jieba:

The provided path is resolved from the root directory.


none experimental

Use this setting to specify an additional user dictionary to be used by jieba for segmenting text, augmenting the default dictionary. User dictionaries are ideal for tuning the segmenter:

yaml
plugins:
  - search:
      jieba_dict_user: user_dict.txt

The provided path is resolved from the root directory.

Usage

Metadata

The following properties are available:


metadata none

Use this property to increase or decrease the relevance of a page in the search results, giving more weight to them. Use values above 1 to rank up and values below 1 to rank down:


metadata none

Use this property to exclude a page from the search results. Note that this will not only remove the page, but also all subsections of the page from the search results:

yaml
---
search:
  exclude: true
---

# Page title
...