Scout 2001
Faith Lienhard
Alluring lines, high performance and a history of commitment blended with designs for the future. Our entire family shapes and molds every Scout model with uncanny attention to detail as if it were their own.
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Laravel Scout provides a simple, driver based solution for adding full-text search to your Eloquent models. Using model observers, Scout will automatically keep your search indexes in sync with your Eloquent records.
Currently, Scout ships with Algolia, Meilisearch, Typesense, and MySQL / PostgreSQL (database) drivers. In addition, Scout includes a "collection" driver that is designed for local development usage and does not require any external dependencies or third-party services. Furthermore, writing custom drivers is simple and you are free to extend Scout with your own search implementations.
After installing Scout, you should publish the Scout configuration file using the vendor:publish Artisan command. This command will publish the scout.php configuration file to your application's config directory:
Finally, add the Laravel\Scout\Searchable trait to the model you would like to make searchable. This trait will register a model observer that will automatically keep the model in sync with your search driver:
While not strictly required to use Scout, you should strongly consider configuring a queue driver before using the library. Running a queue worker will allow Scout to queue all operations that sync your model information to your search indexes, providing much better response times for your application's web interface.
Even when the queue option is set to false, it's important to remember that some Scout drivers like Algolia and Meilisearch always index records asynchronously. Meaning, even though the index operation has completed within your Laravel application, the search engine itself may not reflect the new and updated records immediately.
When using the Algolia driver, you should configure your Algolia id and secret credentials in your config/scout.php configuration file. Once your credentials have been configured, you will also need to install the Algolia PHP SDK via the Composer package manager:
Meilisearch is a blazingly fast and open source search engine. If you aren't sure how to install Meilisearch on your local machine, you may use Laravel Sail, Laravel's officially supported Docker development environment.
In addition, you should ensure that you install a version of meilisearch/meilisearch-php that is compatible with your Meilisearch binary version by reviewing Meilisearch's documentation regarding binary compatibility.
Additional settings and schema definitions for your Typesense collections can be found within your application's config/scout.php configuration file. For more information regarding Typesense, please consult the Typesense documentation.
You should also define your Typesense collection schemas in your application's config/scout.php file. A collection schema describes the data types of each field that is searchable via Typesense. For more information on all available schema options, please consult the Typesense documentation.
If you need to change your Typesense collection's schema after it has been defined, you may either run scout:flush and scout:import, which will delete all existing indexed data and recreate the schema. Or, you may use Typesense's API to modify the collection's schema without removing any indexed data.
Each Eloquent model is synced with a given search "index", which contains all of the searchable records for that model. In other words, you can think of each index like a MySQL table. By default, each model will be persisted to an index matching the model's typical "table" name. Typically, this is the plural form of the model name; however, you are free to customize the model's index by overriding the searchableAs method on the model:
By default, the entire toArray form of a given model will be persisted to its search index. If you would like to customize the data that is synchronized to the search index, you may override the toSearchableArray method on the model:
Filterable attributes are any attributes you plan to filter on when invoking Scout's where method, while sortable attributes are any attributes you plan to sort by when invoking Scout's orderBy method. To define your index settings, adjust the index-settings portion of your meilisearch configuration entry in your application's scout configuration file:
If the model underlying a given index is soft deletable and is included in the index-settings array, Scout will automatically include support for filtering on soft deleted models on that index. If you have no other filterable or sortable attributes to define for a soft deletable model index, you may simply add an empty entry to the index-settings array for that model:
After configuring your application's index settings, you must invoke the scout:sync-index-settings Artisan command. This command will inform Meilisearch of your currently configured index settings. For convenience, you may wish to make this command part of your deployment process:
By default, Scout will use the primary key of the model as the model's unique ID / key that is stored in the search index. If you need to customize this behavior, you may override the getScoutKey and the getScoutKeyName methods on the model:
When searching, Scout will typically use the default search engine specified in your application's scout configuration file. However, the search engine for a particular model can be changed by overriding the searchableUsing method on the model:
Scout also allows you to auto identify users when using Algolia. Associating the authenticated user with search operations may be helpful when viewing your search analytics within Algolia's dashboard. You can enable user identification by defining a SCOUT_IDENTIFY environment variable as true in your application's .env file:
If your application interacts with small to medium sized databases or has a light workload, you may find it more convenient to get started with Scout's "database" engine. The database engine will use "where like" clauses and full text indexes when filtering results from your existing database to determine the applicable search results for your query.
Once you have specified the database engine as your preferred driver, you must configure your searchable data. Then, you may start executing search queries against your models. Search engine indexing, such as the indexing needed to seed Algolia, Meilisearch or Typesense indexes, is unnecessary when using the database engine.
By default, the database engine will execute a "where like" query against every model attribute that you have configured as searchable. However, in some situations, this may result in poor performance. Therefore, the database engine's search strategy can be configured so that some specified columns utilize full text search queries or only use "where like" constraints to search the prefixes of strings (example%) instead of searching within the entire string (%example%).
To define this behavior, you may assign PHP attributes to your model's toSearchableArray method. Any columns that are not assigned additional search strategy behavior will continue to use the default "where like" strategy:
While you are free to use the Algolia, Meilisearch, or Typesense search engines during local development, you may find it more convenient to get started with the "collection" engine. The collection engine will use "where" clauses and collection filtering on results from your existing database to determine the applicable search results for your query. When using this engine, it is not necessary to "index" your searchable models, as they will simply be retrieved from your local database.
To use the collection engine, you may simply set the value of the SCOUT_DRIVER environment variable to collection, or specify the collection driver directly in your application's scout configuration file:
Once you have specified the collection driver as your preferred driver, you may start executing search queries against your models. Search engine indexing, such as the indexing needed to seed Algolia, Meilisearch, or Typesense indexes, is unnecessary when using the collection engine.
On first glance, the "database" and "collections" engines are fairly similar. They both interact directly with your database to retrieve search results. However, the collection engine does not utilize full text indexes or LIKE clauses to find matching records. Instead, it pulls all possible records and uses Laravel's Str::is helper to determine if the search string exists within the model attribute values.
The collection engine is the most portable search engine as it works across all relational databases supported by Laravel (including SQLite and SQL Server); however, it is less efficient than Scout's database engine.
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