# Implement Search on 11ty Static Site

In this post, we will walk through the steps of implementing search on an 11ty static site with lunr. This involves the following:

  • Create a search index
  • Implement user input for searching pages

# Approach

We will create the search index during build time and store the index in JSON format. This JSON will be served on an endpoint (e.g. /search-index.json). The browser client can then fetch this index, and allow user to perform a search. This approach of pre-building indexes is preferred to save time generating an index on the client side.

# Create a Search Index

In this example, we want to index all pages with tag: posts. We will make use of 11ty's collection of tag: posts to generate a lunr search index.

# Template File to Store Index JSON

We need a template file to output search-index.json during build time. We will use a Nunjucks file for this:

# src/search-index.njk
---
permalink: /search-index.json
---
{{ collections.posts | buildSearchIndex | safe }}

The basic idea is to start with collection.posts which has all the page data relating to tag: posts. The collection data then passes through a filter function buildSearchIndex which generates a lunr search index in JSON format. Finally, this JSON data passes through the the Nunjucks safe filter to prevent escaping of JSON content.

# buildSearchIndex Filter

In this example, we will create an index based only on the title field, and use the page url as the id or ref of each document. We can add the filter with the following:

eleventyConfig.addFilter('buildSearchIndex', function (arr) {
  const docs = arr.map(function (doc) {
    return {
      url: doc.url,
      ...doc.data,
    };
  });
  const idx = lunr(function () {
    this.field('title');
    this.ref('url');
    docs.forEach(function (doc) {
      this.add(doc);
    }, this);
  });

  return JSON.stringify(idx);
});

The frontmatter data is nested within the data field of each collection item while the url field is at the root, which is why we will need to massage the data beforehand.

At the end of all this, the search index is served as a serialized JSON format. On the client side, lunr will need to load this index before performing a search. This can be done with lunr.Index.load(JSON.parse(searchIndexJson)). See related lunr docs here: https://lunrjs.com/guides/index_prebuilding.html (opens new window)

# Implement User Input for Searching Pages

Coming soon

Tags:
11ty